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Zywave Unveils Winter 2026 Release to Help Brokers Win More Deals Faster

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Business Wire
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Zywave Unveils Winter 2026 Release to Help Brokers Win More Deals Faster

Four new AI agents combined with other technology advancements significantly streamline workflows, empowering producers to focus on driving revenue, not admin tasks

Zywave, a leading provider of insurance technology solutions, debuted its Winter 2026 Release, announcing that the industry’s first insurance-specialized AI agents are rolling out to more than 35 innovative early adopters across a wide range of insurance organizations. In addition, new platform enhancements will help insurance agencies and brokers transform how they work and achieve unprecedented levels of revenue growth and productivity.

With Zywave Agentic AI, we’re enabling our clients to strip away the noise, so the best insurance professionals can spend more time where it matters most: in front of customers.

Zywave helps insurance organizations drive organic growth and efficiency in a complex market. As brokers face flat growth, talent shortages, and rising risks from technology and litigation, Zywave transforms generalists into specialists with integrated data, analytics, content, and AI tools. Its AI agents unify prospecting, content creation, and client engagement, freeing producers to focus on customers instead of systems.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

“With Zywave, I can now have the AI portion running quietly behind the scenes — automating outreach, qualifying responses, and keeping our pipeline active — while I focus my time on the conversations that really matter,” said Chris Whitney, Partner, Sterling Benefits. “This means I can personally engage with warm leads at the same time the system is nurturing new ones. That balance of automation and human connection has made our sales process far more efficient.”

Key enhancements in the Winter 2026 Release include:

  • Smarter, faster, fully connected insurance workflows: Zywave’s Winter 2026 Release rolls out the following four new AI agents to early adopters of all sizes. Now integrated with the Zywave platform, the agents enable seamless information flow across the prospecting workflow.
    • Prospect Identification enriches customer and policy data to surface top prospects and shape ideal customer profiles.
    • Lead Sourcing & Scoring applies those profiles and miEdge intent signals to find and rank verified, high-potential leads.
    • Research & Enrichment gathers detailed household and company insights, identifies coverages, and personalizes outreach in real time.
    • Outreach & Optimization creates tailored email campaigns with Zywave content, automates sequences, tracks engagement, and refines results.
  • Seamless two-way integration between Partner Platform and TurboRater, enabling single sign-on and automatic data exchange. Agents can now push client data from Partner Platform to TurboRater for quoting, then pull completed quotes back for storage, eliminating manual entry and speeding quote generation.
  • Expanded quoting support: Zywave’s Benefits CPQ now streamlines proposals for new market segments and product lines, enabling quotes for individual (“group of one”) medical plans and complete proposals that include group life, AD&D, and short- and long-term disability coverage in a unified workflow.

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“Too often, organizations end up with barriers between themselves and their customers. With Zywave Agentic AI, we’re enabling our clients to strip away the noise, so the best insurance professionals can spend more time where it matters most: in front of customers,” said Eric Rentsch, Chief Product Officer, Zywave. “Winter 2026 Release innovations create a true performance multiplier for businesses by helping our clients streamline workflow, unlock new revenue growth, and deliver exceptional customer service.”

This announcement builds on recent industry recognition, including Zywave being recently recognized by Forrester Research as a leader in Insurance Agency Management Systems. Zywave will continue to roll out new AI agents throughout 2026 focused on new business and renewal quoting automation, as well as benchmarking policy and coverage design.

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ActiveCampaign Backs Autonomous Marketing with Results Guarantee

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ActiveCampaign Backs Autonomous Marketing with Results Guarantee

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The company becomes first in category to guarantee marketing outcomes, signaling strong platform performance & commitment to customer success

ActiveCampaign, the autonomous marketing platform that has redefined its product for the AI era, announced a Results Guarantee for new customers. Unlike traditional money-back policies, ActiveCampaign’s guarantee is focused on instant results, with a full refund available if they don’t see them within their first month for any reason. While most platforms make businesses spend at least 30 days learning the ropes, ActiveCampaign improves marketing outcomes from the start.

The guarantee is available immediately to all new direct customers globally and requires no separate opt-in. To qualify, customers simply need to purchase any subscription plan. They can then begin experiencing the benefits of ActiveCampaign: set up an email campaign with Active Intelligence, create an automation, send their first automated campaign, and more.

“Autonomous marketing delivers results from day one—that’s what we’re guaranteeing,” said Jason VandeBoom, founder and CEO of ActiveCampaign. “Whether it’s creating and sending campaigns in minutes or getting personalized recommendations without prompting, businesses will experience improved marketing performance right away. We’ve seen 88% of surveyed customers achieve faster results with our platform, and this guarantee backs that up. We’re putting our confidence in autonomous marketing to the test, and we believe the results will speak for themselves.”

The guarantee addresses a common friction point for businesses evaluating marketing platforms: the risk of switching costs, migration effort, and learning curves. By offering a full refund to new customers who complete onboarding but don’t find immediate value for any reason, ActiveCampaign aims to make it easier for customers to try the platform.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

Key aspects of the guarantee include:

  • Full access to AI engine: New users have access to all features within Active Intelligence
  • Risk-free period: Full refund of subscription fees within 30 days for new customers
  • Global availability: Open to all new direct customers across all regions who purchase any ActiveCampaign subscription
  • Simple process: No separate opt-in if eligible, just use core features and decide if it’s right for your business, with a hassle-free process to request a refund

The guarantee complements ActiveCampaign’s existing customer success resources, including one-click migration tools, live onboarding support, and comprehensive training materials. According to the company’s data, customers typically see 3x faster campaign creation with Active Intelligence and a 17% improvement in email performance.

Marketing Technology News: Martech Architecture For Small Language Models: Building Governable AI Systems At Scale

Don Purdy, Director of the University at Albany’s MBA for Executives Program, grew enrollments 27% year-over-year as a one-person marketing team. With the addition of Active Intelligence, open rates doubled from 18-20% to 35-40%. “As a one-person marketing team, I don’t have time for tools that promise a lot and deliver little,” said Purdy. “Active Intelligence helped me move from idea to campaign quickly, and the results followed: higher engagement, stronger inquiries, and enrollment growth. It’s been a game-changer for me, and 30 days is plenty of time to feel the difference.”

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AcuityMD Announces AcuityMD for Salesforce on Salesforce AppExchange

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MeasureBoard Launches AI-Powered SEO, Marketing Automation & Analytics Platform

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AcuityMD’s customers can now benefit from a Salesforce integration that unifies market intelligence and rep-centric workflows

AcuityMD announced it has launched AcuityMD for Salesforce on Salesforce AppExchange, the leading enterprise marketplace for partner apps and experts, empowering customers to integrate AcuityMD’s platform directly with Salesforce to help commercial teams identify opportunities, research and prioritize targets, and hit sales goals faster.

This Salesforce partnership empowers MedTech customers to integrate AcuityMD’s platform directly with Salesforce to help commercial teams identify opportunities, research and prioritize targets, and hit sales goals faster.

AcuityMD combines accurate and precise data, AI-powered insights, and intuitive workflows to help commercial teams move faster and win more opportunities. This launch builds on AcuityMD’s existing Salesforce integration capabilities, which include an embedded user experience, and now enables users to move data between AcuityMD and Salesforce.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

AcuityMD is currently available on AppExchange here.

AcuityMD for Salesforce

AcuityMD for Salesforce connects AcuityMD’s MedTech intelligence platform with Salesforce, aligning targeting, account, and opportunity data into a single commercial workflow. Sales reps can operate within their existing Salesforce processes while eliminating manual updates and keeping data consistent across systems, saving valuable administrative time and enabling more time in the field. By syncing AcuityMD and Salesforce, teams can prioritize the right accounts and move opportunities forward with greater clarity and velocity.

Comments on the News

  • “We’re excited to partner with Salesforce to bring AcuityMD for Salesforce to AppExchange,” said Alex Wakefield, Chief Revenue Officer at AcuityMD. “This launch helps MedTech teams work more efficiently in the systems they already use, while giving them clearer visibility into their highest-value opportunities.”

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Salesforce AppExchange, the leading enterprise marketplace for partner apps and experts, enables businesses to power their agentic enterprise with our trusted and open ecosystem. Since its launch in 2006, AppExchange has grown to include more than 9,000 apps and experts, with over 14 million customer installs and 177,000 customer reviews. AppExchange enables customers of all sizes and across industries to extend their agentic enterprise with pre-built, customizable apps and Salesforce-certified consultants to help solve their business challenges and accelerate time to value.

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AdPrompt.ai Marketing and Advertising Agentic Solution Available On x402; Utilizing x402 for Pay-Per-Use Payments, Settled on Base (L2)

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prweb
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Truecaller Expands Global Direct Ad Sales With New Exclusive Reseller Partnerships

AdPrompt.ai, an AI-powered marketing platform for small businesses, has deployed a selection of its agentic capabilities from its intelligence suite to the x402 marketplace. Leveraging Base’s Layer 2 infrastructure and the x402 payment standard, this integration enables businesses to pay per-use for advanced marketing functions without subscriptions or contracts.

The AdPrompt Marketing Platform combines multiple purpose-built AI agents to deliver a comprehensive toolkit that helps small businesses drive brand awareness and sales in their local markets. In minutes, users can generate on-brand creative content, optimize across key marketing channels, and launch campaigns tailored to their location, audience, and voice.

AdPrompt’s intelligence layer is powered by a suite of trained, specialized AI engines, each designed to automate and optimize a specific marketing or advertising task that often overwhelms small business owners. Rather than working in isolation, these engines are orchestrated to operate together as a cohesive system.

This enables seamless handoffs and collaboration among capabilities, such as analyzing a brand’s identity, generating on-brand creative assets, planning and optimizing ad campaigns across multiple channels, dynamically testing and iterating, and converting performance data into actionable insights. As the platform evolves, new engines are introduced, expanding the breadth and depth of automation available to users. Together, these agents handle the heavy lifting so business owners can focus on serving their customers.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

“Our mission is to make marketing and advertising accessible to every business, especially small businesses competing in hyper-local markets,” said Ken Brook, Founder and CEO of AdPrompt. “To accomplish this, we built a new technology stack that brings together specialized AI Agents that learn continuously to deliver smarter actions, recommendations, on-brand creatives, and channel-ready campaigns with clear performance insights so local businesses can focus on driving customer growth.”

x402 AdPrompt Agent API Capabilities

In simple terms, x402 is a programmable micropayment protocol that enables APIs to be accessed and paid for on a per-call basis without the need for subscriptions or billing accounts. x402scan is a discovery layer and marketplace where users can browse resources that use the X402 payment protocol, and pay for calls via web UI or automated tools.

AdPrompt has deployed three purpose-scoped API resources on x402, powered by its specialized AI engines. These resources let users analyze brand properties, generate on-brand creative assets, and receive strategic recommendations, all with a single API call and micro-payment.

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Brand Scan Agent: Delivers a comprehensive analysis of a business’s online presence and brand identity using only a single website URL. In just a few seconds, it produces a structured report that highlights key aspects of the brand’s presence, personality, and marketing profile, helping users understand the visual identity, audience, and market context. Key outputs include:

  • Positioning: How the brand is positioned in its market or category;
  • Target Audience: The core customer segments and their characteristics;
  • Tone & Voice: Guidance on the appropriate brand voice and messaging style;
  • Key Messages: Core messages that align with the brand’s identity;
  • Trust Signals: Elements that reinforce credibility and trust online;
  • Strengths & Risks: Strengths the brand can leverage and risks it should be aware of;
  • Opportunities: Areas where the brand can grow or improve engagement;
  • Next Steps: Actionable recommendations for enhancing marketing effectiveness;
  • Brand Colors: Primary visual palette derived from the site’s design aesthetic.

In addition to the human-readable report, this agent produces a complete raw JSON metadata bundle containing the underlying scraped and analyzed data, making it easy for downstream tools and agents to reuse the full dataset programmatically.

Creative Generation Agent: Produces platform-ready image or short video creatives using a business summary (optionally the output of the Brand Scan Agent) as context. Key outputs include:

  • Asset LIbrary: Generates on-brand creative concepts and finished assets;
  • Auto-Formatting:Automatically formats assets for the selected channel’s platform, dimensions, and orientation;
  • Promo Copy: Delivers compelling caption copy and calls to action;
  • Extensive Integration: Supports major platforms, including Instagram, TikTok, Facebook, YouTube, Pinterest, X, and LinkedIn, with additional platforms available and optional custom size overrides;
  • Report Summary: Each run returns a polished business-ready report;
  • JSON Data: Delivers a comprehensive raw JSON bundle for downstream tools and agents.

Ad Strategy Agent: Analyzes and recommends a comprehensive ad strategy based on numerous data inputs to guide business objectives and spend priorities. Generates a structured paid media campaign plan from a business summary, target country, and optional budget;Key outputs include:

  • Outline of Approach: Recommends a clear objective, provides practical budget ranges (daily/monthly);
  • Plan Overview: Outputs a platform plan with channel-specific formats, targeting inputs, and KPIs tailored to the business and market;
  • Spend Options: Displays multiple spend tiers that show how pacing and platform allocation evolve as the budget scales, giving non-experts the concrete guidance they need to launch and manage a successful campaign without deep advertising experience;
  • Extensive Integration: Supports a broad set of advertising channels (including Facebook/Instagram, Google Search, LinkedIn, TikTok, Pinterest, Reddit, Nextdoor, Amazon, and more) and returns a polished report view;
  • JSON Data: Delivers a comprehensive raw JSON bundle for downstream tools and agents.

“AdPrompt shows how x402 can make advanced marketing tools available on demand,” said Erik Reppel, Head of Engineering at Coinbase Developer Platform and founder of x402. “By running on Base, agents can make fast, low-cost payments feel seamless in the background so business owners can just focus on getting results.”

x402 and Shifts to the Agentic Advertising and Attention Economy Landscape

Part of AdPrompt’s mission is to automate the discovery and connection between local small businesses and relevant targeted local advertising opportunities. As the advertising ecosystem evolves beyond traditional programmatic workflows, the industry is moving toward an agentic model, where interoperable agents can identify opportunities, generate creative, execute campaigns, and continuously optimize performance.

“As the advertising industry rapidly becomes ‘agentic’, the tools around it must become agentic too. Unlike legacy systems, agentic systems work continuously with a seamless user experience: discovering opportunities, generating creatives, testing variations, optimizing spend, and reacting in near real time,” said Brook. “x402 brings a missing piece to the internet: a way to attach payments directly to an API call. Instead of requiring subscriptions, contracts, billing accounts, and complicated onboarding flows, x402 turns access into something much more natural: pay only for what you use, when you use it.”

With x402, a small business can invoke a capability, pay a micro-fee, and receive an output instantly. At the same time, enterprises and autonomous systems can run the same workflow at scale, executing thousands of paid calls per day with minimal friction.

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From Dallas to Chicago to Austin: How JPLoft Is Powering the Next Wave of Mobile Innovation in the USA

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MTS Staff Writer
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UpCodo Digital Introduces AI-Powered Web and Mobile App Development Services for Businesses

JPLoft

JPLoft expands mobile development operations across Dallas, Chicago, and Austin, strengthening architecture-driven solutions for enterprises.

JPLoft, a global mobile and software development company, has expanded its operational focus across several major U.S. technology markets, reinforcing its commitment to supporting businesses navigating accelerated mobile transformation.

By strengthening our presence in Dallas, Chicago, and Austin, we design scalable digital solutions and AI-powered platforms for next-generation businesses.”

— Rahul Sukhwal

With active engagements spanning enterprise organizations and high-growth startups, the company’s continued expansion reflects rising demand for structured mobile engineering solutions in innovation-driven regions.

By strengthening its presence across US innovation hubs, i.e., Dallas, Chicago, and Austin, JPLoft aims to align its development capabilities with regional business ecosystems that are investing heavily in scalable digital infrastructure.

The expansion builds upon JPLoft’s broader U.S. strategy of delivering architecture-first mobile applications designed to support long-term operational efficiency, secure data frameworks, and adaptable system performance.

Strategic Expansion Across Key U.S. Innovation Corridors

The company’s expansion strategy across Dallas, Chicago, and Austin reflects a deliberate effort to align operations with regions, demonstrating sustained business investment in mobile technology and digital infrastructure.

Their growth model is structured around strengthening engineering capabilities within established and emerging technology ecosystems rather than operating through isolated, location-specific initiatives.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

JPLoft’s regional presence is designed to support organizations navigating modernization initiatives across these markets.

The firm has expanded engineering resources and client collaboration models to address both enterprise-level transformation and product-focused innovation.

By maintaining consistent architectural standards across all three regions, JPLoft aims to deliver:

• Structured backend development frameworks
• Cloud-native infrastructure planning
• Secure API integrations
• Long-term scalability and performance optimization

The company’s leadership stated that regional diversification strengthens operational resilience while improving proximity to client decision-makers.

This approach allows JPLoft to remain responsive to evolving market demands without compromising engineering consistency or delivery governance.

Rather than positioning expansion solely on geographic scale, the strategy reflects a broader commitment to supporting sustained mobile innovation across interconnected U.S. technology corridors.

Responding to Enterprise and Startup Mobile Demand

As organizations across the United States continue to digitize customer experiences and operational workflows, mobile platforms are increasingly viewed as long-term infrastructure investments rather than short-term product launches.

JPLoft’s service offerings across key innovation markets reflects this structural shift in how businesses approach application development.

Enterprises typically require mobile systems that integrate securely with existing enterprise resource planning platforms, customer management tools, and cloud environments.

These projects often involve regulatory considerations, data governance standards, and performance requirements that demand early-stage architectural planning.

JPLoft has structured its engineering workflows to address these factors during initial discovery phases, emphasizing documentation, system mapping, and scalability modeling before development begins.

Growth-stage startups, by contrast, often prioritize rapid deployment, product validation, and user acquisition.

However, even in early-stage environments, technical sustainability remains critical. JPLoft’s development framework incorporates modular architecture and cloud-native infrastructure to help startups scale without significant system restructuring as user demand increases.

Chicago is a market that is considered to be primarily led by financial services and healthcare organizations that continue investing in mobile modernization initiatives.

In such a market, JPLoft, as a leading mobile app development company Chicago, engages with modern enterprises for structured, compliance-aware application builds.

This regional engagement reflects the company’s broader objective of aligning development methodologies with sector-specific operational requirements.

By balancing enterprise-grade engineering with adaptive development cycles, JPLoft aims to support diverse business models while maintaining consistent quality standards across U.S. markets.

The company’s approach centers on long-term system reliability, secure integration, and measurable performance outcomes, reinforcing mobile development as a foundational business capability rather than a standalone digital initiative.

Regional Technology Momentum and Business Infrastructure

Technology investment across major U.S. metropolitan areas continues to reshape how organizations prioritize digital infrastructure.

Dallas, Chicago, and Austin each contribute to this broader momentum through distinct economic strengths, workforce development patterns, and sector-driven innovation.

Businesses in this environment often require applications capable of integrating with legacy platforms while maintaining performance across distributed teams.

Chicago’s diversified economy, particularly within financial services, healthcare networks, and transportation logistics, has contributed to steady demand for secure and regulation-conscious mobile ecosystems.

Austin has transformed into a prominent growth market shaped by startup acceleration, venture capital activity, and corporate relocations within the technology sector.

This is a place where businesses are actively looking for an experienced Mobile App Development Company in Austin, like JPLoft. Such an association is significant in ensuring speed-to-market and long-term infrastructure planning.

Across these interconnected innovation corridors, mobile platforms are increasingly designed to serve as operational anchors rather than supplementary tools. Businesses are prioritizing:

• Cloud-native deployment strategies
• Secure data management and encryption standards
• API-driven interoperability
• Performance optimization across device ecosystems

JPLoft’s distributed operational model allows for consistency in engineering standards while adapting to the structural drivers shaping each region.

By aligning its technical execution with regional business dynamics, the company aims to support sustained mobile innovation without fragmenting delivery governance across markets.

Engineering-First Mobile Development Philosophy

JPLoft’s operations across major U.S. innovation markets is supported by a development philosophy centered on structured engineering practices rather than design-first or feature-driven execution.

The company’s methodology emphasizes architectural planning, performance modeling, and infrastructure forecasting at the earliest stages of project engagement.

Before development begins, technical teams conduct system mapping exercises to evaluate integration points, user load expectations, data security requirements, and long-term scalability projections.

This approach is intended to reduce technical debt and limit the need for structural reconfiguration as applications evolve.

By embedding governance checkpoints throughout the development lifecycle, JPLoft maintains standardized quality controls across all U.S. engagements.

The company’s development model typically incorporates:

• Cloud-native backend configuration
• Modular code architecture to support iterative scaling
• Secure API integration with enterprise systems
• Performance testing across device environments
• Compliance-aware data handling protocols

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This engineering-first perspective enables the company to work with both regulated enterprises and growth-stage startups while maintaining consistent delivery standards.

Rather than adapting quality thresholds by market or sector, JPLoft applies uniform architectural benchmarks across Dallas, Chicago, and Austin operations.

Consistent engineering governance has contributed to the company’s recognition as a top mobile app development company in Dallas within enterprise-focused engagements.

By prioritizing long-term system sustainability, the company positions mobile development as a strategic capability embedded within broader business transformation initiatives.

The objective is not only application deployment, but a structured digital infrastructure capable of supporting measurable growth over time.

Scalable Mobile Solutions Supporting Business Growth

JPLoft’s service framework across U.S. markets is structured to support organizations at varying stages of digital transformation while maintaining consistent engineering standards.

The company approaches mobile development as long-term infrastructure planning rather than short-term feature deployment.

1) Custom Mobile Application Development

JPLoft delivers custom-built mobile platforms aligned with defined business objectives and operational requirements.

Each engagement begins with technical discovery and architectural mapping to ensure that user-facing features are supported by scalable backend systems.

Development models are selected based on performance needs, integration complexity, and projected growth patterns rather than uniform deployment templates.

2) Cross-Platform and Native Engineering

The company applies both native and cross-platform development methodologies depending on application scope and user demographics.

Native builds are typically utilized where device-level performance optimization is required, while cross-platform frameworks support broader deployment efficiency across operating systems.

Engineering decisions are documented during early planning stages to preserve long-term maintainability.

3) Cloud-Native Infrastructure Planning

Cloud-aligned architecture forms a foundational component of JPLoft’s development framework.

Applications are structured to operate within distributed cloud environments that support scalability, data redundancy, and performance monitoring.

Infrastructure stress testing and load forecasting are incorporated before production deployment to reduce scaling friction as user demand increases.

4) Enterprise Integration and Modernization

For organizations transitioning from legacy systems, JPLoft incorporates structured modernization strategies.

This includes API mapping, phased database migration, and synchronization planning designed to preserve operational continuity.

Integration frameworks are engineered to maintain compatibility with existing enterprise tools while supporting future digital expansion.

5) Security, Compliance, and Performance Governance

Security protocols and compliance alignment are embedded throughout the development lifecycle.

JPLoft implements encryption standards, secure authentication mechanisms, and regulatory-aware data handling processes tailored to industry-specific requirements.

Performance validation across device ecosystems ensures consistent functionality in diverse operating environments.

By applying these service pillars consistently across its U.S. operations, JPLoft reinforces its objective of delivering mobile systems that function as adaptable business infrastructure rather than temporary digital assets.

Long-Term Commitment to Mobile Innovation in the United States

JPLoft’s expansion across Dallas, Chicago, and Austin reflects a broader long-term commitment to strengthening its role within the U.S. mobile technology landscape.

Rather than approaching regional growth as short-term market penetration, the company has positioned its strategy around sustained engineering investment, operational stability, and long-term client partnerships.

Mobile applications continue to serve as foundational components of digital business models across industries.

Organizations are increasingly integrating mobile platforms with analytics systems, cloud infrastructure, and enterprise resource planning tools to support end-to-end operational visibility.

JPLoft’s leadership has indicated that future development efforts will continue emphasizing scalability, interoperability, and security alignment as core architectural priorities.

The company’s multi-market presence is intended to support businesses navigating evolving regulatory environments, rising user expectations, and performance demands associated with distributed digital ecosystems.

By embedding structured governance models and standardized engineering frameworks across U.S. operations, JPLoft aims to maintain delivery consistency while adapting to sector-specific innovation cycles.

Looking ahead, the company plans to continue refining its development methodologies in response to advancements in cloud computing, device ecosystems, and enterprise integration standards.

Investment in technical talent, infrastructure modernization, and compliance-ready development processes remains central to this roadmap.

Through disciplined expansion across interconnected innovation corridors, JPLoft positions mobile development as a durable component of long-term business infrastructure.

The company’s U.S. growth strategy reflects a measured approach focused on architectural integrity, operational resilience, and sustained collaboration with enterprises and product-driven organizations.

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Ada Launches the Industry’s First Unified Reasoning Engine, A Single Intelligence Layer to Power Agentic Customer Experiences in Any Channel

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Mktg.Tech Launches Independent Ranking and Evaluation Platform for Marketing Technology

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Patent-Pending Innovation Reduces AI Agent Management Workload for Internal Teams, Accelerates Automation for Complex Use Cases

Ada, the trusted AI-native customer experience company and creator of the Agentic Customer Experience (ACX) Operating Model, announced its new unified Reasoning Engine™. This patent-pending breakthrough fundamentally changes how AI agents operate at enterprise scale, and dramatically accelerates the opportunity for more complex, longer-horizon task automation. For the first time, AI agents are powered by a single, unified intelligence: one “brain” that engages consistently across all modalities to deliver fast, accurate, and compliant customer experiences.

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A New Foundation for Enterprise Agentic Customer Experience: Design once. Manage in one place. Engage everywhere.

As customer expectations rise and service channels multiply, enterprises struggle with fragmented AI systems that create operational and change management hurdles. Ada’s new unified Reasoning Engine delivers a single AI foundation, enabling AI agents to efficiently determine the next best action and automate even the most complex customer interactions without sacrificing speed, accuracy, policy adherence, or brand integrity.

For ACX teams, this unified view makes it faster and easier than ever to create, manage, and optimize their AI agent. A single instruction can now be deployed once and dynamically replicated in all channels and languages. Whether a customer chooses to engage over voice, messaging, social, or email, the AI agent draws from the same knowledge, policies, and brand standards. The result is a dramatic reduction in the manual effort required to maintain, coach, and evolve AI agents, and a significant boost in ACX manager productivity.

Customers also benefit from reduced handling time and more empathetic service, while enterprises realize lower cost-per-contact, higher automated resolution rates, and the ability to transition increasingly sophisticated, high-impact interactions to AI agents with confidence.

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Unlocking New Levels of Performance and Value for Voice AI

With this release, Ada also extends powerful new automation capabilities to voice—traditionally the most expensive and highest-volume enterprise channel. Playbooks and Coaching are now widely available on voice, enabling AI agents to follow standard operating procedures, handle complex multi-step calls, and continuously improve over time by incorporating granular feedback from past interactions.

“Voice has always been the hardest channel to transform,” said Brian Gilman, VP of Customer Support at workforce payments platform Branch. “With Ada’s unified Reasoning Engine, that’s changed. Our AI agents can now reason through complex, high-stakes voice conversations with the same intelligence that powers our digital channels. That means faster, more accurate support when our users need it most, especially in moments that directly impact their pay. By elevating the voice experience, we’re reducing friction, resolving issues more efficiently, and ensuring workers get the clarity and confidence they deserve.”

Dual Reasoning Architecture for Speed and Depth

Ada’s unified Reasoning Engine features a patent-pending dual-reasoning architecture, improving the customer experience by providing immediate, empathetic responses while simultaneously handling complex tasks in the background. This unified approach unlocks a new class of agentic customer experience, enabling AI agents to resolve complicated, multi-step workflows.

“Customer service doesn’t happen in silos, and AI agents shouldn’t either,” said Mike Gozzo, Chief Product and Technology Officer at Ada. “With the launch of our unified Reasoning Engine, Ada has established a new standard for agentic customer experience while improving how our customers’ internal ACX teams perform and scale. We now have one ‘brain’ behind every AI agent, applying the same context, logic, and safeguards, regardless of the channel. But these improvements aren’t just about scale–they’re also about depth. Customers will see a significant step improvement across the board with this new engine, allowing them to realize a more accurate and deeper resolution rate, even for the most complex inquiries. That’s what allows enterprises and ACX teams to move faster, with less risk, entrusting AI with even more real-world interactions.”

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Reltio: New Harvard Business Review Analytic Services Survey Reveals Massive Readiness Gap for Agentic AI

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Reltio: New Harvard Business Review Analytic Services Survey Reveals Massive Readiness Gap for Agentic AI

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The report, sponsored by Reltio, finds only 15% of organizations have the necessary data foundation

Reltio®, the context intelligence platform providing trusted business understanding for the enterprise AI era, announced the release of a new pulse survey by Harvard Business Review Analytic Services (HBR-AS), “Unlocking the Data Advantage in the Age of Intelligence.” The survey, sponsored by Reltio, finds that while 94% of organizations are exploring or implementing AI, a stark disconnect remains between enterprise AI aspirations and data readiness.

“Agentic AI represents a step-change in how work gets done, but its autonomy depends on something most enterprises still struggle to scale: unified, real-time, trustworthy data,” said Manish Sood, CEO and Founder of Reltio.

The survey of 325 global business and technology leaders highlights that while “trust in the reliability of data” is ranked as the most critical capability for AI success (94%), only 39% of organizations say they are highly proficient in this area. Furthermore, only 15% of respondents consider their data foundation “very ready” for the shift toward Agentic AI—autonomous systems that can act, decide, and execute workflows with minimal human supervision.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

Bridging the Readiness Divide

As organizations move beyond traditional automation toward the “Age of Intelligence,” the report identifies data silos as the top barrier to progress, cited by 46% of respondents. Other significant hurdles include insufficient data talent (42%) and unclear data strategies (39%).

“Agentic AI represents a step-change in how work gets done, but its autonomy depends on something most enterprises still struggle to scale: unified, real-time, trustworthy data,” said Manish Sood, CEO and Founder of Reltio. “This research confirms that the ‘plumbing’—the data foundation—is still the primary bottleneck. At Reltio, we believe that context is the decisive ingredient. Without a connected, governed, and real-time understanding of every entity and relationship, even the most advanced AI agents will fall short of their promise.”

Marketing Technology News: Martech Architecture For Small Language Models: Building Governable AI Systems At Scale

Key Findings

  • The Trust Gap: Despite its importance, 34% of leaders describe their data investment management as “very ad hoc and fragmented.”
  • Strategic Misalignment: Only 16% of respondents say their organization’s data investments are very organized and aligned with their business strategy.
  • The Shift to Context: Experts interviewed in the report emphasize the need for “semantic layers” that act as translation guides for AI, defining core business concepts and mapping relationships across systems.
  • Governance as an Advantage: 89% of leaders say data governance is highly important, but only 37% say their organization is highly proficient, suggesting that governance must evolve from a back-office compliance function to a strategic differentiator.

“We are entering an era where AI agents won’t just analyze data; they will act on it autonomously to resolve customer issues, optimize supply chains, and drive growth. However, an agent is only as effective as the context it is given,” said Sood. “If your data is fragmented or conflicting, your AI will be too. The leaders who win in the Age of Intelligence will be those who move beyond experimentation and treat data readiness not as a one-time project, but as a core organizational evolution. Reltio is committed to providing the context intelligence that allows these systems to reason, act, and deliver value with absolute confidence.”

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Complete SEO Expands Managed SEO Services with Proprietary AI Tools to Strengthen Client Performance

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Webtage LLC Sets a New Industry Standard with AI, GEO, and AEO-Integrated SEO Solutions for Local and Global Businesses

Complete SEO

Complete SEO, a long-standing leader in search marketing, announced the expansion of its Managed SEO Services, introducing proprietary AI-powered tools designed to enhance campaign precision, scalability, and measurable growth for businesses operating in competitive local and B2B markets.

The expansion reflects Complete SEO’s continued investment in modern search strategy as the digital landscape becomes more complex. Search results are increasingly shaped by frequent algorithm updates, evolving ranking signals, and higher competition across nearly every industry category. For business owners, this often means that “set it and forget it” SEO is no longer effective—ongoing optimization, content refinement, and technical oversight have become essential to maintaining visibility over time.

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Complete SEO’s enhanced managed SEO model strengthens the agency’s ability to execute sustained performance improvements for clients that rely on consistent inbound demand. While the company supports campaigns nationally, its client base is largely made up of local businesses and B2B companies—organizations that need clear ROI, steady pipeline impact, and a strategy built around competitive realities rather than generic best practices.

“Our focus has always been practical, sustainable growth,” said Kyle Sanders, Co-founder of Complete SEO. “We work with businesses that depend on consistent visibility—local service providers, regional brands, and B2B companies competing in tight niches. The AI tools we’ve developed allow us to analyze patterns across years of campaign data and anticipate shifts before they fully impact performance. That gives our clients a strategic advantage.”

The company’s proprietary internal tools integrate automation and predictive analytics into a single managed workflow. These systems help Complete SEO’s team identify keyword opportunities, map content gaps, detect technical friction points, and evaluate link-profile health with greater speed and consistency. Rather than relying solely on third-party platforms, the agency has built a customized internal environment that supports decision-making, prioritization, and quality assurance.

Importantly, these tools are not offered as a public product. They are designed specifically to support Complete SEO’s internal operators and processes—helping campaigns move faster from insight to execution while maintaining a high standard of review. The goal is not automation for its own sake, but intelligent acceleration: improving the human strategy loop by validating assumptions, reducing wasted effort, and surfacing opportunities that might otherwise be missed.

“There’s a lot of noise around AI in marketing right now,” Sanders added. “For us, it’s not about hype. It’s about using smarter internal infrastructure to support transparency, accountability, and better outcomes. Automation only matters when it improves the decisions behind the strategy.”

Marketing Technology News: From Data to Impact: How AI is Transforming Interactive CTV Ads

Complete SEO’s expanded Managed SEO Services program is built around structured execution across the core pillars of modern organic search: technical optimization, content strategy, authority development, and performance analytics. Campaigns are supported through ongoing technical monitoring, intent-driven keyword research, on-page and internal linking enhancements, content calibration aligned to real search behavior, and link acquisition strategies designed to build authority without sacrificing quality.

The expansion also reflects a growing market demand for managed programs that deliver consistency. Many businesses recognize that “SEO services” often vary dramatically by region and provider—while managed SEO services increasingly signals a more complete, ongoing strategy with measurable performance tracking. Complete SEO’s approach is designed to meet that expectation with clear planning, transparent reporting, and continuous refinement as search conditions change.

As more industries face rising search volatility and increasingly crowded SERPs, Complete SEO’s updated managed offering is designed to help small and mid-sized organizations benefit from enterprise-level methodology without losing the responsiveness and hands-on attention of a specialized agency partner. The company emphasizes sustainable ranking growth rather than short-term spikes, aligning search strategy with long-term brand and revenue outcomes.

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NEWMEDIA.COM Announces Expanded Retail Authority Acceleration Framework

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NEWMEDIA.COM Announces Expanded Retail Authority Acceleration Framework

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NEWMEDIA.COM Announces Expanded Retail Authority Acceleration Framework

NEWMEDIA.COM announced the continued expansion of its proprietary RankOS™ platform with a focused Retail Authority Acceleration framework designed specifically for B2B packaging, manufacturing, and supply chain leaders operating within major retail ecosystems.

The framework integrates earned media, trade visibility, AI citation reinforcement, and measurable attribution tracking into a single performance model, enabling industrial and retail-facing companies to increase Share of Voice with board-ready reporting clarity.

The launch comes at a time when retail ecosystems are experiencing leadership transitions, increased trade competition, and rising expectations around measurable marketing accountability.

Why It Matters

Many established B2B companies possess strong operational credibility but limited external visibility. Traditional PR models often fail to provide clear attribution, making marketing investment difficult to justify in industrial environments.

Marketing Technology News: MarTech Interview with Liat Barer, Chief Product Officer @ Odeeo

RankOS™ addresses this gap by:

  • Establishing baseline Share of Voice across trade media
  • Securing high-credibility industry placements
  • Reinforcing authority signals across search and AI systems
  • Tracking measurable visibility movement within days, not months

“Industrial brands don’t need hype; they need measurable authority,” said Steve Morris, Founder & CEO of NEWMEDIA.COM.

“RankOS™ transforms third-party validation into structured visibility growth that leadership teams can see, measure, and act on.”

How the Retail Authority Acceleration Framework Works

The framework follows a five-phase model:

  1. Baseline Audit: Trade presence, search authority, and AI citation benchmarking
  2. Strategic Positioning: Executive thought leadership aligned to commercial priorities
  3. Prime Placement: Targeted retail and supply chain trade media visibility
  4. Authority Amplification: Structured reinforcement through trusted third-party citations
  5. Impact Measurement: Share of Voice movement and visibility lift reporting

Unlike traditional PR campaigns that measure impressions alone, RankOS™ tracks visibility shift across:

  • Trade media authority
  • AI recommendation presence
  • Organic search movement
  • Referral traffic patterns

Key Performance Indicators

Recent B2B industrial deployments of RankOS™ have demonstrated:

  • 3–6x increase in trade Share of Voice within 90 days
  • Measurable AI system recommendation appearance for targeted industry queries
  • 20–40% lift in brand search activity following amplification cycles
  • Increased validation mentions during enterprise sales conversations

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Designed for Retail & Supply Chain Leaders

The Retail Authority Acceleration framework is particularly suited for:

  • Corrugated packaging manufacturers
  • POP display providers
  • Retail-ready packaging specialists
  • Integrated logistics operators
  • Private equity portfolio companies in industrial verticals

As retail ecosystems continue to evolve, measurable authority – not just media presence – is becoming a strategic growth lever.

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Kustomer Launches AI Setup Assistant to Prevent AI Failures in CX Teams

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V2 Communications Launches AI Authority and Earned Media Scaling Capabilities to Help Tech Brands Win in the Age of AI Search

The word “kustomer” in lowercase black letters; the u has two dots above it, resembling eyes and creating a smiley face within the text.

New industry perspective highlights the hidden risk undermining AI adoption in CX teams

Many CX leaders are discovering an uncomfortable truth: the biggest barrier to AI success isn’t the model, it’s the foundation beneath it.

In an AI-first CX environment, teams need a responsible way to replatform. That’s why Kustomer built the AI Setup Assistant – designed to help teams configure AI without guessing or relying on brittle, manual setup. AI Setup Assistant connects directly to Zendesk, analyzes an organization’s existing configuration, and intelligently translates it into a new Kustomer environment — surfacing risks, preserving critical logic, and guiding teams through migration with confidence.

“The industry has been asking whether AI is ready for CX,” said Brad Birnbaum, CEO of Kustomer. “What we’re seeing is that AI is ready but many systems aren’t. AI Setup Assistant is about helping teams build the foundation AI needs to perform reliably. Because when AI fails, it’s rarely the model. It’s the configuration underneath it. We believe configuration intelligence will become a core requirement for every AI-first CX organization.”

Across high-growth companies and enterprise CX organizations alike, AI initiatives are stalling not because the technology is immature, but because underlying system configuration quietly breaks at scale. Routing, permissions, automation logic, and data models, long treated as backend “admin work”, are now determining whether AI builds trust or destroys it.

This pattern is showing up consistently where experienced operators are sharing hard-won lessons from AI rollouts that didn’t go as planned.

The AI Myth Holding Teams Back

For years, AI challenges in CX have been framed as model problems: hallucinations, poor accuracy, or lack of sophistication. But in practice, many failures stem from something more mundane, and more dangerous.

AI systems amplify whatever foundation they’re given. When routing is misaligned, permissions are incomplete, or automation fires out of order, AI doesn’t quietly fail. It produces decisive, inconsistent outcomes that erode trust with agents, customers, and leadership.

As one CX leader put it: “AI didn’t fail — our system did.”

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

The Rise of Invisible Setup Debt

Modern CX platforms are no longer simple ticketing tools. They are deeply interconnected systems where one configuration decision can affect multiple downstream outcomes.

The problem is that this complexity compounds invisibly. Setup debt builds quietly over time, often introduced by well-intentioned changes made under pressure, a new queue, a new automation, a quick permissions tweak.

Teams don’t feel the impact immediately. They feel it weeks or months later, during volume spikes, migrations, or AI launches, when diagnosing root cause is hardest and stakes are highest.

Why AI Raises the Cost of Getting This Wrong

Before AI, configuration issues were painful but survivable. Teams could patch problems manually, explain away inconsistencies, or absorb inefficiencies with headcount.

AI changes that equation.

When AI underperforms, leadership rarely attributes the failure to setup. The conclusion is simpler, and more damaging: “AI doesn’t work for us.” Momentum stalls, confidence drops, and future investment becomes harder to justify.

In an AI-first world, a clean setup is no longer operational hygiene. It’s a prerequisite for credibility.

What’s often missing from this conversation is that CX setup now serves two workforces, not one.

Historically, configuration decisions were made to support human agents, ensuring the right tickets landed in the right queues, with the right tools and permissions. But as AI agents become part of the CX stack, those same setup decisions – especially the data model choices to ensure well-structured, well-described data in your system – increasingly determine whether AI can act responsibly, accurately, and consistently.

A well-configured CX platform doesn’t just help human reps do their jobs better; it provides the structure, data and context AI agents rely on to reason correctly. Even for teams not deploying AI agents today, the foundation they build now will directly shape what AI can, and can’t, do when they’re ready.

This shift is exactly why the training, tools and processes teams have historically relied on to manage setup risk are no longer sufficient.

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Why Traditional Fixes No Longer Scale

Many teams attempt to manage setup risk with tools and processes designed for a simpler era:

  • Static checklists that age instantly
  • Expensive audits or professional services reviews
  • Automation tools that auto-fix without explaining impact

These approaches fail for the same reason: they don’t keep pace with systems that are constantly changing.

Worse, black-box automation introduces a new problem: fear. Admins remain accountable for outcomes, but lose confidence when they don’t fully understand what’s happening under the hood.

What High-Confidence Teams Do Differently

The CX teams navigating AI successfully aren’t moving slower. They’re moving with fewer surprises.

  • They validate before they automate.
  • They look at systems, not isolated settings.
  • They keep humans accountable, but supported.

Instead of reacting to failures after launch, they invest in understanding configuration risk before it becomes customer-facing.

The New Requirement: Configuration Intelligence

What’s emerging is a new category of capability: configuration intelligence.

Not automation that takes control away from teams, but setup intelligence that:

  • Understands how settings interact
  • Surfaces second- and third-order risk
  • Explains impact in plain language
  • Keeps humans firmly in control

In an AI-first CX environment, teams need a responsible way to replatform. That’s why we built the AI setup assistant at Kustomer. Designed to help teams configure AI without guessing or relying on brittle, manual setup.

From Setup as Admin Work to Setup as Strategy

The shift is already underway. Setup is no longer a backend concern delegated to a few experts. It’s a strategic capability that determines whether AI delivers on its promise or becomes another stalled initiative.

This is the exact problem Kustomer built AI Setup Assistant to address: helping CX teams surface hidden risk, understand system-level impact, and build confidence in their foundation before AI and scale expose the cracks.

Not by replacing human judgment, but by supporting it.

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Enverus Launches Marketplace for Buying and Selling Minerals, Backed by Industry-Leading Data and Analytics

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Enverus Launches Marketplace for Buying and Selling Minerals, Backed by Industry-Leading Data and Analytics

Data‑driven platform allows buyers and sellers direct access to exclusive off‑market deals with no transaction fees

Enverus, the leading energy SaaS and analytics platform, announced the launch of Enverus Minerals Marketplace, a centralized and secure platform that connects buyers and sellers of mineral and non-operated interests. Unlike broker‑led or auction‑driven mineral marketplaces, Enverus’ marketplace supports private, one‑to‑one engagement between buyers and sellers through in-app live chat within a secure environment. By replacing competitive bidding with direct market access, the platform enables a more streamlined transaction experience focused on control, efficiency, and trust.

Enverus Minerals Marketplace is supported by Enverus data covering more than 250,000 mineral owners and representing approximately 85% of U.S. royalty revenue processed through EnergyLink®,providing unmatched visibility into cash flow and ownership performance. This depth of coverage gives customers the confidence to identify, evaluate, and transact opportunities faster than traditional broker-led processes.

Built for mineral investors, Enverus Minerals Marketplace enables sellers to easily list mineral and non-operated interests while maintaining control of their transactions. Buyers can connect directly with a curated network of listings not broadly marketed elsewhere, enriched with Enverus production, ownership, permitting insights, alongside revenue and JIB statement data to support confident evaluation.

“By enabling direct communication within a system and organization control (SOC 2) compliant environment, we’ve created a safer, more efficient marketplace that removes friction, reduces costs, and aligns incentives for both sides of the transaction. Enverus’ Minerals Marketplace fundamentally changes how mineral assets are bought and sold. For the first time, sellers can list mineral assets through an automated, secure platform while maintaining control of their transaction, and buyers gain direct access to verified, off‑market opportunities—without transaction fees distorting value,” said Phil Dunning, Director of Product at Enverus.

Enverus Customers like Jake Dobkins, Director of Acquisitions & Divestment at Tower Rock Oil & Gas have been quick to praise Enverus for its past work around minerals and transactions. “As mineral rights become increasingly fractionalized, education and transparency are key, especially for owners who lack basic knowledge. The ease with which we can access, analyze, and act upon high quality data is critical. Enverus has empowered us to make informed decisions at the speed demanded by our industry.”

Marketing Technology News: MarTech Interview with Lee McCance, Chief Product Officer @ Adverity

Key benefits of Enverus Minerals Marketplace:

  • No transaction or listing fees, promoting a more balanced exchange between buyers and sellers.
  • Direct, private communication between buyers and sellers through in-app live chat, enabling faster and more transparent deal discussions.
  • Trusted Enverus data to support asset valuation and confident decision making.

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Caterpillar Bolsters Mining Technology Solutions with RPMGlobal Acquisition

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Caterpillar Bolsters Mining Technology Solutions with RPMGlobal Acquisition

Caterpillar Inc. has acquired RPMGlobal Holdings Limited, an Australian-based mining software company. The acquisition expands Caterpillar’s portfolio of data-driven mining technology and software solutions that help customers plan, operate and manage their sites more efficiently.

Headquartered in Brisbane, Australia, RPMGlobal has deep domain expertise in mining technology enablement, providing customers with data-driven software solutions across the mining value chain. Caterpillar announced an agreement to acquire RPMGlobal in October 2025.

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“Acquiring RPMGlobal is a notable milestone supporting our strategy to solve the challenges our mining customers face every day,” said Denise Johnson, group president, Caterpillar Resource Industries. “By combining RPMGlobal’s software capabilities with Caterpillar’s proven equipment and technology solutions, we will unlock new opportunities to help customers improve mine site performance, while advancing the future of mining technology in a way that is practical, scalable and grounded in their needs.”

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“Given the complementary nature of the two companies’ technology offerings, Caterpillar is an ideal home for both our people and our software products,” said Richard Mathews, chief executive officer, RPMGlobal. “By deeply integrating our solution sets, we will be able to better solve the most difficult challenges mining companies grapple with daily. The team and I are looking forward to working with the Caterpillar team for the benefit of our customers.”

RPMGlobal will continue to offer products and services under the RPMGlobal brand.

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Krisp AI Note Taker Raises the Bar for Meetings by Expanding Its AI Meeting Suite With Accent Conversion

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Krisp AI Note Taker Raises the Bar for Meetings by Expanding Its AI Meeting Suite With Accent Conversion

Krisp raises the bar in the AI note-taking market by going beyond transcription and summaries. While most tools document meetings after they happen, Krisp improves how conversations sound in real time through noise cancellation and accent conversion, helping businesses get far more value than a traditional note taker can provide.

Krisp is a voice AI company known for pioneering Voice AI solutions, and Krisp AI Note Taker extends a voice-first approach into meeting documentation.

Krisp has been recognized by TIME magazine as one of the Best Inventions of 2020, included in the Forbes AI 50 and Forbes Cloud 100 Rising Stars, and won Webby Awards for its innovative use of AI in audio technology.

Instead of treating audio as a fixed input, Krisp focuses on making speech clearer and easier to understand in real time through Noise Cancellation and Accent Conversion. This matters because meeting notes are only as dependable as what the AI can hear and comprehend.

By reducing background noise and normalizing accents for better clarity, Krisp helps ensure that spoken ideas are captured as intended.

Teams spend less time rewatching recordings, correcting misunderstandings, or repeating decisions, and more time acting on what was agreed. To date, Krisp AI Note Taker has transcribed more than 130 million calls, reflecting the scale at which these conversations are captured and understood.

Marketing Technology News: MarTech Interview with Miguel Lopes, CPO @ TrafficGuard

Krisp AI Note Taker Key Features

  • AI-generated notes with accurate and real-time transcripts, summaries, and action items that teams can trust and act on
  • Bot-free, natural meeting experience with meetings captured without bots or disruption
  • Seamless workflow integration with conferencing apps, CRMs, and project management tools for easy adoption
  • Enterprise-grade security and compliance supporting established standards to keep data protected
  • Background noise removal powered by award-winning noise cancellation for clearer speech and more reliable meeting outputs
  • Accent conversion that clarifies diverse accents in real time, helping teams understand each other and produce more accurate meeting notes

Marketing Technology News: Disrupt or Be Disrupted: The AI Wake-Up Call for B2B Marketers

“Building voice AI at Krisp has shown us how closely the quality of meeting notes is tied to the quality of what is heard in the moment. When conversations are affected by noise or unclear audio, teams lose time revisiting recordings, correcting notes, or re-aligning on decisions. This is not a problem that starts after the meeting. It starts during the meeting. By improving how conversations sound in real time, Krisp enables more accurate transcripts, summaries, and action items, so teams can trust their notes and focus on execution instead of reconstruction”, said Arto Minasyan, Co-founder and President of Krisp.

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Amplitude Introduces Agentic AI Analytics for the Next Era of Product Experiences

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Amplitude Introduces Agentic AI Analytics for the Next Era of Product Experiences

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Real-time analysis and continuous monitoring help teams move faster from insight to impact

To help companies close the gap between shipping software and knowing what to build next, Amplitude, Inc. announced a series of AI agents that continuously analyze product usage, identify what’s working and what isn’t, and recommend actions to take in real time.

The news comes as AI coding assistants from companies like Anthropic, OpenAI, Cursor, and Lovable have made it exponentially easier to create software. But as teams can ship features faster than they can learn what is working for users, the need for AI-first behavioral analytics tools becomes more important than ever.

“We’re entering a new era of analytics—one where AI can monitor your product around the clock, and free up your team to focus on improving the experience,” said Spenser Skates, co-founder and CEO at Amplitude. “ we’re launching the first fully autonomous analytics agent. It’s going to reinvent how product decisions get made.”

As part of the launch, Amplitude announced a Global Agent, four specialized Agents, and MCP updates that bring behavioral data to where people already work—such as tools from Anthropic, OpenAI, Cursor, Figma, Lovable, Notion, and GitHub. Combined, they make it possible for companies of all sizes to move from insight to action in minutes instead of months.

With Global Agent, teams can ask complex questions in plain language and get instant answers. The agent analyzes data, builds dashboards, investigates root causes, and explains what’s driving changes across funnels, experiments, segments, and customer journeys. It then recommends what to do next and takes action directly in Amplitude.

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Four specialized agents—focused on monitoring dashboards, reviewing user sessions, running experiments, and processing feedback—handle the tasks that typically bog product teams down.

  • Dashboard Monitoring Agent – Detects meaningful metric changes within hours, investigates why they happened, and delivers insights and recommended actions via Slack or email.
  • Session Replay Agent – Reviews hundreds of user sessions continuously, spots hidden friction, quantifies revenue impact, and recommends specific fixes.
  • Web Experimentation Agent – Designs and launches experiments, analyzes results, and makes rollout or iteration decisions, all while keeping a human in the loop.
  • AI Feedback Agent – Turns unstructured feedback from surveys and support tickets into actionable insights by mapping themes to actual user behavior.

Unlike AI tools that simply query a data warehouse, Amplitude’s AI agents operate inside a system that is purpose-built for behavioral analytics. This means the agents understand context, not just data, leading to clearer, more accurate, and more actionable insights.

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  • AI Assistants: Ask Claude or ChatGPT to summarize user behavior, pull charts, and answer product or campaign questions using Amplitude data.
  • Development: Validate, debug, and track impact with product context inside Cursor or Claude Code. Add behavioral context to GitHub pull requests. Build and ship AI features with integrated product insights in AWS Kiro.
  • Design & Prototyping: Validate and refine Lovable concepts with product performance and feedback. Identify user friction and generate data-backed prototypes in Figma Make.
  • Product & Collaboration: Analyze and surface product opportunities with Notion agents. Make Amplitude charts and analytics searchable in Atlassian Rovo.
  • Sales & Engagement: Personalize messaging and targeting in Outreach with behavioral signals.

Early customers and partners are already seeing impactful results with Amplitude’s fully agentic AI analytics platform.

“Amplitude has helped NTT DOCOMO scale self-serve analytics to more than 1,000 active users and significantly reduce the time required to analyze campaign effectiveness,” said Takashi Suzuki, SVP and GM of the Data Platform Department at NTT DOCOMO. “With Amplitude AI Agents, our teams can streamline analysis directly from existing dashboards, helping us move faster while improving conversion rates and lowering cost per acquisition.”

“Increasing our users required more than just access to data. It required structure and automation,” said Matias Caratti, Product Shipping Supervisor, Mercado Libre. “Dashboards provided a single source of truth, and AI Agents enabled us to find data on our own. We didn’t have to rely on manual reports, and we were provided with automatic insights on funnel performance, countries with the best conversion, and fluctuations in contact rate.”

“Amplitude MCP and Skills bring user insights directly into agent context in Cursor,” said Joshua Ma, Engineering Lead at Cursor. “This allows teams to quickly ship features, measure impact, and build smarter experiments for the next release.”

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New Clutch and Conductor Data Reveals 87% of Content Marketers Increasing Budgets in 2026 as SEO Expands Into AI Search

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Announcing peerspot.ai: Your AI Marketing Agent that Creates High-Quality Content Using Customer Proof

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One in Four Now Write Primarily for LLMs as AI Becomes a Strategic Growth Lever

Clutch, the leading global marketplace of B2B service providers, in partnership with Conductor, released its 2026 State of Content Report, revealing that content marketing investment is accelerating as SEO expands to include AI search and large language model visibility.

Rather than pulling back in response to AI disruption, organizations are doubling down. Nearly nine in ten content marketers plan to increase budgets in 2026, and one in four now say large language models are the primary audience for the majority of their content. The data signals a structural shift in how content teams define visibility, performance, and audience in a discovery landscape shaped by both traditional search engines and AI-generated answers.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

The findings are based on a January 2026 survey of more than 450 marketing professionals responsible for producing content, spanning organizations from growing SMBs to large enterprises. Respondents represent a wide range of seniority levels, from hands-on practitioners to directors and C-suite leaders, offering a comprehensive view of how content strategy is evolving in the age of AI.

Key findings from the report include:

  • 81% of content marketers feel positive about the state of content marketing in the era of LLMs
  • 67% view LLMs as more of an opportunity than a risk for their content strategy
  • Nearly 25% of respondents say LLMs are now the primary audience for a majority of their content, rising to 32% among enterprise organizations
  • 87% plan to increase content marketing budgets in 2026, and more than 55% expect to increase content output
  • 75% already use AI-powered tools as part of their standard content creation workflow
  • Proprietary research and original reports rank as the top written content priority for increasing visibility in AI-generated answers

“These findings reflect a clear inflection point for content marketing,” said Mike Beares, Clutch CEO. “Teams understand that AI search is reshaping how buyers discover information, and they’re responding by investing in higher-quality, more authoritative content that can earn trust, citations, and visibility across emerging discovery surfaces.”

Marketing Technology News: Martech Architecture For Small Language Models: Building Governable AI Systems At Scale

Beyond budget increases, the research highlights an evolution in how marketers define success. While referral traffic remains a familiar performance metric, many teams acknowledge it no longer captures the full impact of content in AI-driven discovery, where influence and visibility often occur before a click. As a result, marketers are expanding their measurement frameworks to account for brand mentions, citations, and presence within AI-generated responses.

“The most striking shift is how quickly LLMs have become a first-class audience for content teams,” said Seth Besmertnik, CEO and co-founder of Conductor. “Just one to two years into AI search, nearly a quarter of marketers say LLMs are now their primary content audience. That’s a massive change in a short amount of time, and it reinforces why original, trustworthy content is becoming the currency of visibility in AI-generated answers.”

The report also finds that while video and social platforms are rising in importance for authority-building and audience engagement, content teams increasingly recognize that durable AI visibility is driven by structured, extractable, and authoritative assets, particularly original research and long-form reference content that LLMs can reliably cite.

Together, the data paints a picture of a discipline in transition: optimistic, proactive, and increasingly strategic, yet navigating a landscape where visibility often influences outcomes without driving direct clicks.

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Expert AI Prompts Releases Specialized SEO and Content Toolkit for Independent E-Commerce Sellers

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From Traffic to Transactions: Wytlabs' ROI-Driven Ecommerce SEO Framework

Expert AI Prompts logo

Expert AI Prompts releases “Etsy Edition,” a specialized AI toolkit designed to automate SEO, content creation, and operations for independent sellers.

Expert AI Prompts, a digital publishing house specializing in artificial intelligence workflows, has announced the release of “AI Prompt Power: Etsy Edition.” This new digital toolkit is designed to assist independent artisans and small business owners in navigating search engine optimization (SEO) and content creation within the 2026 e-commerce landscape.

Handmade sellers face million-dollar competitors. This toolkit gives solo makers the enterprise firepower to finally win that battle.”

— Founder, Expert AI Prompts

The release comes as the retail sector experiences a shift toward Generative Search, creating new technical requirements for product visibility. The “Etsy Edition” is engineered to standardize the “Context-First” framework, allowing users to utilize Large Language Models (LLMs)—including ChatGPT, Claude, and Gemini—to optimize product listings without requiring technical coding knowledge.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

Addressing Market Disparities: The toolkit was developed in response to market analysis highlighting the resource gap between major retail conglomerates and independent makers. While large-scale retailers often utilize enterprise-grade automated marketing, individual sellers frequently face “time poverty” regarding administrative tasks.

“The narrative of the artisan economy is facing a ‘David vs. Goliath’ scenario regarding digital infrastructure,” stated the Founder of Expert AI Prompts. “Independent sellers are competing in a digital marketplace dominated by complex algorithms. This release is intended to provide the necessary prompt engineering infrastructure to help solo operators align with current SEO standards.”.

Marketing Technology News: Martech Architecture For Small Language Models: Building Governable AI Systems At Scale

Technical Specifications: The “Etsy Edition” package includes 50 specific prompts designed to address three core operational areas:

– Search Optimization: Generating long-tail keywords and tags aligned with 2026 search trends.

– Content Development: Converting technical product specifications into narrative-driven descriptions.

– Operational Efficiency: Automating standard communications, including shop policies and customer service responses.

Availability and Compatibility: This release is part of the company’s “Vertical Domination” roadmap, focusing on specific industry applications for AI. The toolkit is available for immediate download and is compatible with major generative AI platforms.

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TopQuadrant Launches Enterprise Context Platform to Build Trusted AI

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MTS Staff Writer
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TopQuadrant Launches Enterprise Context Platform to Build Trusted AI

Build a Trusted, AI-Ready Data Foundation | TopQuadrant

TopQuadrant, a pioneer in semantics, data management and AI, announced the launch of TQ Data Foundation, the context layer for trusted, autonomous agents. The new offering extends TopQuadrant’s position as the knowledge graph platform of choice for Fortune 500 enterprises to provide the contextual foundation needed to power AI applications.

The AI Context Gap

Enterprises are investing heavily in AI, yet many remain stuck in pilot mode. The common assumption is that the bottleneck lies in the model or the data platform. In reality, the constraint is more fundamental: AI lacks access to the context that governs how the enterprise actually works.

Traditional data platforms were built for reporting and analytics, helping teams analyze trends and answer known questions. AI changes the mandate. Modern AI systems interpret, synthesize, recommend, and increasingly act. AI must reason across systems, apply business rules, and trigger workflows with speed and autonomy—a capability which requires more than data. It requires shared meaning.

In most organizations, business meaning is fragmented—definitions vary across systems, logic is hard-coded in pipelines, policies live in static documents, and institutional knowledge resides in people. Humans compensate through experience and judgment. AI systems cannot.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

When context is implicit or scattered, AI fills in the gaps with confident approximation—a risk no organization can afford.

Introducing TQ Data Foundation

TQ Data Foundation is the enterprise context platform to build trusted AI, operationalizing context so AI systems can reason, act, and govern with confidence.

“TopQuadrant provides the missing link that scales trustworthy AI,” said Amar Doshi, Chief Product Officer at TopQuadrant. “The TQ Data Foundation answers our enterprise customers’ needs as they progress from building data foundations for people, to securing trusted, context-driven foundations for AI.”

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The TQ Data Foundation platform stands on four key pillars using knowledge graph technology to connect and power context for humans and AI:

– Models – Encode how core business concepts interact so AI can answer questions correctly the first time (commonly implemented as ontologies)
– References – Align critical terms across teams so AI produces consistent answers across systems (products, customers, suppliers, policies)
– Metadata – Ingest metadata from sources such as data lakes, data catalogs and content management systems to describe information in a consistent, discoverable way
– Business Logic – Express unique rules, governance and compliance “as code” to activate context into AI and other applications

Managing the Context Lifecycle

TopQuadrant’s TQ Data Foundation manages the full lifecycle of foundational data and context, from build to change management:

– CAPTURE: Capture and unify business context across people, systems, and documents leveraging AI
– ACTIVATE: Deliver shared context wherever AI is built and deployed (tools, agent frameworks, platforms)
– EVOLVE: Continuously govern and improve context so AI stays aligned, accurate, and trusted over time

The result is one comprehensive platform to build and manage the context layer in order to deliver AI that is accurate, scalable and trustworthy.

“I am excited to deliver the next stage of data and AI maturity for our customers with the new TQ Data Foundation,” said Nimit Mehta, CEO of TopQuadrant. “As we partner with the world’s largest and most complex enterprises to solve the context gap in AI governance, it is very rewarding to witness the business outcomes of safe, accurate and scalable AI.”

Powered by internal agents, embedded directly into AI pipelines, and actively listening to self-enrich, TQ Data Foundation ensures a scalable data foundation built for the promise and ambitions of Enterprise AI.

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

Spokenote Launches the First Video Platform Built to Scale Authentic Interaction

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MTS Staff Writer
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0
Spokenote Launches the First Video Platform Built to Scale Authentic Interaction

Next-generation Platform Blends Automation with Authenticity, Introducing a New Era of Dynamic Video Personalization

Spokenote redefined the boundaries of the modern marketing stack with the introduction of the first and only solution that allows organizations to scale authentic video interactions and human trust with the speed of modern automation on the Spokenote platform. By enabling organizations to deliver personalized, short-form video at an infinite scale without the need for manual editing or AI-generated impersonations, Spokenote is defining a new category in marketing technology focused on human engagement.

Spokenote’s dynamic video capability reimagines traditional connections by creating a video experience that adapts to each viewer, using modular components that are assembled based on audience interests and segmentation. The platform ensures every message feels personal, relevant, and human, not automated or mass-produced.

Unlike traditional Content Marketing Platforms (CMPs) or Personalization Engines, Spokenote translates data into human experiences, complementing multichannel marketing hubs by creating “one-to-one” moments that drive measurable action.

Marketing Technology News: MarTech Interview with Nicholas Kontopoulous, Vice President of Marketing, Asia Pacific & Japan @ Twilio

“The world is saturated with automated, soulless noise. People don’t want more information; they want more connection,” said John Wechsler, Founder and CEO of Spokenote. “Spokenote is the first and only platform that allows a brand to look a thousand different customers in the eye and deliver a unique, authentic message in seconds. We aren’t just launching a product; we are launching a movement to make ‘yes’ inevitable by bringing the human element back to the center of the customer journey.”

Spokenote is built for high-impact moments where trust and connection matter most, including student recruitment, donor engagement, customer appreciation, and other mission-critical communications. Teams connect data, upload or record video clips, and instantly generate thousands of personalized, trackable video experiences. The resulting experiences are ready to deploy through existing CRM workflows via SMS, email, or direct mail, and utilize performance analytics to measure  the customer journey.

Marketing Technology News: The ‘Demand Gen’ Delusion (And What To Do About It)

Dynamic video capabilities are available now on the Spokenote platform (patent pending).

Spokenote is a video engagement platform that transforms everyday touchpoints into powerful, trackable video experiences. By pairing physical and digital channels with personalized video, Spokenote makes human connection scalable and effortless, helping marketers, educators, and nonprofits accelerate their customer journeys. From enrollment journeys and donor campaigns to sales enablement, marketing communications and commemorative tickets, Spokenote empowers organizations to inspire measurable action and build relationships that last. In every case, our mission is simple: to turn moments into movements and make “yes” inevitable

Write in to psen@itechseries.com to learn more about our exclusive editorial packages and programs.

Why AI Search Is Forcing CMOs to Rethink What “Visibility” Really Means

By
Patrick Reinhart
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0
Why AI Search Is Forcing CMOs to Rethink What “Visibility” Really Means

For years, marketing leaders treated search visibility as a straightforward contest. Rank well, earn the click, capture the visit, and convert the customer. That model built entire SEO programs, reporting dashboards, and budget allocations. But a structural change is now underway. Discovery is increasingly happening inside AI-driven answer experiences, not on traditional results pages. Visibility is no longer only about traffic. It is about whether your brand appears in the answers shaping decisions before traditional result engagement.

Recent enterprise research into Answer Engine Optimization (AEO) / Generative Engine Optimization (GEO) shows how quickly this shift is taking hold. Generative AI and answer engines are changing how customers discover, evaluate, and build trust in brands. In response, answer engines have become a performance channel in their own right, signaling which organizations’ AI systems are considered credible enough to include in responses. Marketing investment follows that change.

Enterprises now allocate, on average, 12% of digital marketing budgets to AEO and GEO initiatives. More than half report already having a high or significant investment, and an overwhelming majority plan to increase spending again in the year ahead. High-maturity organizations are accelerating faster than their peers, widening the gap between early leaders and late adopters.

Influence is moving faster than traffic

One of the most important findings from current benchmarks is the distinction between volume and impact. AI referral traffic remains a small share of overall website visits (just over 1%). However, influence is shifting much faster than these raw traffic numbers suggest.

AI-generated answers now appear in roughly a quarter of Google searches. In trust-heavy sectors such as healthcare and financial services, exposure is significantly higher. That means a growing share of category discovery is happening inside AI summaries and answer interfaces, before users scroll through organic results. Even when users ultimately click through to a website, perception and shortlists are increasingly formed upstream, inside the answer layer.

By the time AI traffic becomes large enough to impact analytics dashboards, leaders who invested early will already hold the advantage.

New KPIs for a discovery layer

This is forcing CMOs to reconsider how success is measured. Historically, rankings, sessions, and click-through rates defined SEO performance. Those metrics remain useful, but they no longer reflect the full scope of digital visibility.

As such, AI-native metrics are becoming increasingly important. Brand mentions, domain citations, share of AI-generated answers, and exposure inside AI overviews are increasingly tracked as leading indicators of trust and presence.

In enterprise research, nearly all surveyed leaders report a positive impact on the funnel from AEO and GEO efforts. AI-driven visitors convert in fewer sessions, mainly because education and trust-building occur before the website visit. This means that visibility is no longer only about attracting clicks. It is about being recognized as a trusted source inside AI systems that synthesize and present answers.

Marketing Technology News: MarTech Interview with Omri Shtayer, Vice President of Data Products and DaaS at Similarweb

Budget strategy is shifting accordingly

As measurement evolves, so does investment strategy. Traditional paid search remains a priority for short-term ROI and predictable acquisition. SEO continues to provide foundational crawlability, site health, and content infrastructure. But AEO and GEO have emerged as top strategic priorities for the coming year, outpacing several established digital channels in executive planning.

High-maturity organizations are not treating AEO as an experiment. They are building internal capabilities, upskilling existing teams, and hiring specialized roles. Nearly two-thirds of enterprises plan to develop in-house expertise rather than outsource. This is because AI search is rapidly evolving, and internal teams can test, iterate, and adapt more quickly when knowledge resides within the organization.

Under-investment early creates a gap that becomes more expensive to close later. CMOs are beginning to recognize that AI-driven discoverability behaves more like a long-term capability build than a campaign-based tactic.

Content strategy is being rebuilt around machine understanding

Another critical shift is happening in content planning. High-performing organizations are treating content ecosystems as reference layers rather than click destinations. AI systems favor sources that provide deep, structured, authoritative information they can reliably parse, interpret, and cite.

Effective strategies prioritize long-form explanatory content, cohesive topic clusters, structured data, clear authorship, and technically reliable site architecture. Exclusive research, benchmarks, and proprietary insights provide strong citation references because they offer original information rather than restating existing knowledge. These assets serve dual purposes. They earn visibility inside AI-generated answers and strengthen credibility across PR, analyst relations, and sales enablement.

Execution remains the primary challenge. Scaling AI-optimized content requires strong editorial standards, reliable data, and technical hygiene. Teams also struggle to gain visibility into whether content is being crawled and interpreted correctly by AI systems. Without that feedback loop, optimization becomes reactive. Leading organizations are addressing this by investing in continuous monitoring and durable measurement approaches aligned to how modern language models retrieve and surface information.

A new definition of marketing visibility

None of this signals the end of traditional search. Billions of searches still occur daily, and organic traffic remains a meaningful driver of site visits. The change is additive. A new discovery layer now sits alongside conventional channels. CMOs who understand this are balancing SEO and AEO investments rather than choosing between them.

Visibility is now defined by whether your brand appears in the answers shaping perception before the click. That requires new metrics, new content structures, new team capabilities, and new budget logic.

The organizations adapting early are responding to a measurable structural shift in how trust and discovery are formed.

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