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Kochava Unveils Creative Services Workspaces on StationOne, Featuring Leading Partners Higgsfield, Luma, and Spaceback by Rembrand

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Kochava Unveils Creative Services Workspaces on StationOne, Featuring Leading Partners Higgsfield, Luma, and Spaceback by Rembrand

Kochava is the leading real-time data solutions company for omnichannel outcomes. Through multi-touch attribution, modern marketing mix modeling, end-to-end campaign management, and AI-driven workflows, all backed by our acclaimed customer success team, Kochava helps clients verify results, predict what’s next, and take informed action.

Empowering Creative Teams to Move Faster, Personalize Deeper, and Focus on What Matters Most

Kochava, the leading real-time data solutions company for omnichannel outcomes, announces the expansion of StationOne by Kochava with new, purpose-built workspaces for marketers and creative professionals, powered by top AI partners Higgsfield, Luma, and Spaceback by Rembrand. The announcement signals a new era of creative workflow: one where campaign assets are not just rapidly produced and adapted, but strategically optimized for every segment, every screen, and across every channel—unlocking new value for creative teams and marketers alike.

The New Creative Imperative: Speed, Fidelity, and Human Focus
Modern campaigns demand unmatched speed, personalization, and creative excellence—yet creative leads and teams are still too often burdened with busy work, manual resizing, and repetitive adaptation for dozens of formats and audiences. With StationOne’s new workspaces, all that changes. By seamlessly integrating industry-defining creative tools from Higgsfield, Luma, and Spaceback by Rembrand, StationOne synthesizes model-driven creative iteration directly into the workflows of activation and optimization.

“Our vision for StationOne is simple: unlock creative possibilities, eliminate repetitive barriers, and amplify what human teams do uniquely well,” said Charles Manning, CEO at Kochava. “With these workspaces, AI doesn’t replace creativity—it embeds it into accelerated ad operations workflows natively.”

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

Higgsfield: Unmatched Customization, Effortless Asset Creation

Higgsfield pushes creative boundaries further with AI-driven video and image generation built for marketers seeking distinctive, hyper-customized content.

With direct integration into StationOne, creative leaders can harness Higgsfield to produce, test, and refine dynamic creative assets at scale, making true content personalization not just viable, but effortless.

“Higgsfield exists to turn every brand’s vision into personalized creative at the speed and quality modern campaigns demand. Together with StationOne, we’re giving creative teams a faster path from idea to finished work, with each asset built for the audience it needs to reach,” said Taz Patel, Vice President of Platform Partnerships at Higgsfield.

Luma: Fastest Path from Idea to Impact

Luma is renowned among creative pioneers for delivering game-changing speed, model-level brand intelligence, and absolute creative control.

Teams can explore ten creative directions before the morning standup and deliver fifty on-brand variants by end of day. By bringing creative generation and workflow orchestration closer together, Luma and StationOne enable teams to spend less time managing processes and more time focused on strategy, storytelling, and creative development.

“Creative teams are under growing pressure to produce more content, adapt campaigns faster, and maintain brand consistency across channels. By bringing Luma’s generative AI capabilities into StationOne, we’re helping creatives move from concept to execution more efficiently while giving greater control over the final outcome,” said Caroline Ingeborn, COO, Luma

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

Spaceback by Rembrand: Social Creative Intelligence, Built for the AI Age

Spaceback’s AI-native Social Creative Intelligence platform helps marketers identify what resonates with audiences, uncover competitive opportunities, and turn those insights into high-performing creative. Through its integration with StationOne, brands can generate, activate, and measure multiple creative variants across programmatic and CTV, bringing the impact of social beyond walled gardens and from insight to activation in the same day.

“Generative AI makes creativity limitless, but social shows marketers what’s worth making,” said David Wiener, Chief Product Officer at Rembrand. “StationOne and Spaceback turn those signals into creative that can be generated, activated, and measured across programmatic and CTV, helping marketers move from insight to outcomes faster.”

StationOne: The Creative Orchestration Layer Marketers Demand

More than a toolkit, StationOne connects marketing’s critical operations—creative, analytics, attribution, and more—into a single, open, collaborative platform designed for creative excellence and team-wide productivity. By unifying leading AI partners, StationOne offers:

For Creative Leads:
No more creative grunt work, endless resizing, or workflow silos. Reclaim your team’s energy for strategy, concept, and inspiration—unlocking outcomes at the new intersection of human vision and intelligent automation.

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InboxAlly Launches Deliverability Hub With 11 Free Tools

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InboxAlly Launches Deliverability Hub With 11 Free Tools

InboxAlly

New no-signup suite helps senders investigate spam placement, authentication, blocklist, content, list-quality and warmup issues in one place

InboxAlly, the email deliverability platform trusted by more than 20,000 brands, announced the launch of its expanded Email Deliverability Hub, combining the company’s reputation-improvement platform with a suite of 11 free tools.

The new tools help senders investigate why emails are landing in spam, uncover authentication and infrastructure problems, evaluate inbox placement and address potential issues before sending a campaign. Each tool works with any email service provider or sending platform and can be used without creating an account.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

Email deliverability problems rarely have a single cause. A sudden decline in performance can result from authentication errors, blocklist entries, list quality, campaign content, sending-volume changes or provider-specific filtering. The InboxAlly Deliverability Hub brings the tools for investigating these problems together in one place.

The free suite is organized into three areas:

  • Testing and Analysis: The Email Spam Checker, Spam Word Checker, Email Placement Tester, Spam Database Lookup and Email Header Analyzer help senders evaluate message content, authentication, routing, blocklist status and placement across Gmail, Outlook and Yahoo.
  • Planning and List Quality: The Warmup Planner creates a personalized 30-day sending ramp based on a sender’s volume and current conditions. Email List Verification identifies invalid, disposable and potentially risky addresses, with bulk verification for complete lists available within the InboxAlly platform.
  • Email Authentication: The SPF Record Generator, DMARC Record Generator, DKIM Checker and BIMI Record Generator help senders create, inspect and validate the DNS records that support authenticated email and brand identification.

“Email deliverability has been treated like a black box for too long,” said Darren Blumenfeld, founder and CEO of InboxAlly. “Senders should be able to determine whether a problem involves authentication, content, blocklisting, list quality or inbox placement without stitching together multiple services. The InboxAlly Deliverability Hub gives them that visibility in one place, and our platform is there when active reputation improvement is the next step.”

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

The free tools complement InboxAlly’s paid platform, which generates consistent, positive engagement signals through InboxAlly-managed inboxes. Senders can include InboxAlly email addresses in their existing campaigns or use Adaptive Autowarmup to automate the process. InboxAlly works alongside the sender’s existing email platform, so no migration or replacement of sending infrastructure is required.

InboxAlly customers have used the platform to produce measurable improvements in sender reputation and inbox placement. Seido Knives, for example, increased its Klaviyo sender score from approximately 45 to an all-time high of 75. Over eight months, its spam-folder placement fell from more than 20% to under 2%, while its Google Postmaster domain reputation improved from Low to High.

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New Measurement Data: AI Engines Disagree by 2× on Which Brands to Recommend, Treyci Analysis Finds

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New Measurement Data: AI Engines Disagree by 2× on Which Brands to Recommend, Treyci Analysis Finds

Treyci — AI Visibility Intelligence

Analysis of more than 1,200 scored AI answers shows the same brands, asked about with the same buying questions in the same month, were mentioned in 81% of one AI engine’s answers and just 43% of another’s — a gap invisible to companies that only spot-check ChatGPT.

Treyci, an AI visibility intelligence platform, released measurement data showing that major AI engines disagree sharply about which brands to mention and recommend when buyers ask for purchasing guidance. In one measured B2B software category, one AI engine referenced the tracked brands in 81 percent of its answers while another referenced the same brands in only 43 percent — a nearly two-fold visibility gap between engines that buyers use interchangeably.

The findings come from Treyci’s measurement methodology, which runs approximately 100 buying-intent questions per category — “best X for mid-size teams,” “X alternatives,” pricing comparisons — across ChatGPT, Perplexity, Gemini, and Grok, repeating every prompt three times per engine each month and scoring more than 1,200 resulting answers for brand mentions, recommendations, and citations.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

Additional findings from Treyci’s recent measurement work include:

  • AI answers are probabilistic. The same engine, asked the same buying question in separate sessions, routinely returns different vendor lists — meaning single-run brand checks capture an anecdote rather than a measurement.
  • AI engines cite third parties, not vendors. When engines answer buying questions, cited sources are dominated by review platforms, comparison articles, and industry publications rather than company websites — reshaping where brand-visibility work actually pays off.
  • Adoption is ahead of measurement.  In a Treyci scan of 100 B2B SaaS companies, 41 published an llms.txt file for AI crawlers, yet few companies can quantify whether any of their AI visibility work has changed how often engines recommend them.

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

“Marketing teams are making decisions about AI search based on one screenshot of one answer from one engine,” said Keith Schilling, founder of Treyci and previously an AEO/GEO practitioner at PayPal. “The data says that’s a coin flip wearing a suit. The engines disagree with each other, and they disagree with themselves from one asking to the next. Until a brand measures the distribution of answers — across engines, on repeat runs — it doesn’t know its own numbers.”

The shift matters because AI assistants increasingly produce the first shortlist in B2B purchasing decisions. When a brand is absent from an AI answer, the company’s analytics show nothing: no impression, no session, and no record that a buying conversation occurred.

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ByteBrew Brings Live Operations into App Developers’ AI Workflows, Closing the Agentic Loop From Insight to Action

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ByteBrew Brings Live Operations into App Developers' AI Workflows, Closing the Agentic Loop From Insight to Action

ByteBrew_Logo_Black.png

Find the friction, tune it in chat, and ship personalized updates worldwide, all within ByteBrew’s Shift AI

ByteBrew, the leading all-in-one mobile platform to analyze, operate, and grow mobile apps, today announced that Operate, its live operations stack, now runs natively inside Shift AI, the company’s real-time app intelligence Model Context Protocol (MCP) server.

With Operate built in, the conversation that surfaces a problem is now the same conversation that fixes it. A studio points Shift AI at what needs to change, and a single message deploys live updates through ByteBrew’s Remote Configs and A/B Tests to users everywhere. This makes it possible to agentically define a distinct experience for every cohort and ship all of them at the same time.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

What’s New

  • A native Operate layer inside Shift AI: Studios run live operations directly through Shift AI, turning recommendations grounded in real-time, first-party app intelligence into deployed change inside the same conversation.
  • Personalization at scale, defined agentically: Every value, variant, and targeting condition a studio can express in Operate is now reachable from a single message. A team can define a different experience for each segment, down to pricing, offers, onboarding, and the screen itself, and ship each version at once.
  • Worldwide the moment it ships: A change reaches every user simultaneously rather than waiting on a review process that can take up to 48 hours. No staggered rollout, no store submission, no version fragmentation to manage afterward.
  • A closed, end-to-end agentic loop: Integration Assistant MCP deploys ByteBrew across a portfolio, Shift AI turns that data into real-time intelligence, and Operate acts on it. Deploy, reason, ship, all without leaving the developer’s workflow.
  • A full workday returned every week: Metric assembly, config edits, experiment setup, segment building, and quality assurance on in-app changes now run through a single conversation, saving roughly eight hours a week.

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

Why It Matters

Getting the right experience to the right user at the right moment is one of the hardest problems in mobile, and it is also one of the biggest revenue levers. An onboarding flow that loses users in its first minute, a checkout step that quietly drains conversion, a difficulty curve pitched a notch too steep, rewards spaced too far apart to keep a new user moving: these problems hide in the data, and every day they go unfixed, more users lose interest and move on.

With Operate inside Shift AI, a studio can define that experience by segment, down to the screen itself, and ship it instantly, instead of waiting on a review process that can take up to 48 hours. Some studios maintain 250 different configurations for a single app, and run more than 100 active titles at once. Handled manually, personalization stops being a strategy and becomes an operations problem. Handled through a conversation with Shift AI, it is one more message.

That transformation changes what is economically worth doing. A studio can tune a first-time user experience for one cohort, adjust pricing or offers for another whose elasticity is different, and move a lower-spending user toward ad-supported monetization instead. Each result gets measured, and the pattern repeats across dozens of configurations. Optimizing at that scale stops being a resourcing question and starts being a competitive advantage.

Details

Shift AI is not simply a connector. It is a domain-grounded intelligence layer that interprets a developer’s intent, activates ByteBrew’s native agent mesh to retrieve the right data, and enriches the results through a proprietary-trained, multi-model Context Engine before streaming the results back to the AI platform of choice. Until now, that path ended at insight. The Operate layer extends it through to execution, completing an agentic loop that runs from integration to intelligence to live change across a studio’s entire portfolio.

Remote Configs and A/B Tests are the surface. Behind them sits everything a studio builds with them: difficulty and economy curves, reward pacing, offer and paywall placement, pricing tiers, subscription upgrade prompts, onboarding flows, checkout and cart steps, feature gates, and the config conditions that decide which users see which version of the experience. All of it is now addressable from a message, which means a studio can define distinct experiences for distinct cohorts agentically, test them against each other, and roll the winner out globally without touching a dashboard or waiting on a release.

None of that works unless the model is reasoning on data deep enough to trust with a live change. ByteBrew’s AI engines are grounded in one of the most robust first-party datasets in mobile, analyzing more than 3.8 trillion app events a month connected to every in-app user interaction across billions of live users. With Operate inside Shift AI, that same data now both diagnoses the problem and drives the fix, closing the long-standing gap between moving fast and reasoning on complete data.

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TwelveLabs Launches Compliance by TwelveLabs to Find Potential Content Violations Quickly, Accurately, and Easily Across Any Region

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TwelveLabs Launches Compliance by TwelveLabs to Find Potential Content Violations Quickly, Accurately, and Easily Across Any Region

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The first application built on TwelveLabs’ video intelligence platform gives compliance teams a new level of control in content moderation

TwelveLabs, a leading video intelligence company, today announced the general availability of Compliance by TwelveLabs, a new SaaS solution that helps media, entertainment, and broadcast teams screen video content against compliance standards. Now any violations can be rapidly identified, with a rationale provided, so that teams can take appropriate action. Compliance by TwelveLabs debuts on the heels of the company’s $100 million Series B announcement. It marks the first application to be built on TwelveLabs’ video intelligence platform, the company’s full-stack agentic system for video that enables AI to understand the content, context, and meaning of video, rather than simply identifying what appears on screen.

“Video compliance review is broken, and TwelveLabs is uniquely capable of fixing it,” said Jae Lee, CEO and co-founder of TwelveLabs. “Our compliance app is all about your compliance rules, not ours. We surface potential violations and give reviewers the power to make decisions faster and easier than ever before.”

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

Compliance by TwelveLabs was designed to target four of the most complex issues plaguing global content teams: effort, variance, access, and media authenticity. Traditional manual compliance review has long been a bottleneck, as screening a single two-hour master for potential violations can take a human reviewer at least a week. Compliance by TwelveLabs takes this time spent down to minutes, saving companies both hard and soft costs.

On the variance front, every market carries its own standards (i.e. the MPA in the U.S., Ofcom in the UK, CNC in France, Gmedia in Saudi Arabia, ClassInd in Brazil, and ACB in Australia). This is on top of each studio’s internal policies. Compliance by TwelveLabs adapts to any defined standard, dramatically simplifying workload and reducing the risk of errors.

In terms of accuracy, existing AI moderation tools have promised relief but tend to generate so many false positives that reviewers end up re-scrubbing the entire timeline anyway, erasing the time savings they were meant to deliver. Compliance by TwelveLabs is designed to target reviewer rejection (false-positive) rates of 15% or lower, so flagged moments are worth a reviewer’s time.

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

A fourth risk is compounding fast: media authenticity. In the era of generative AI, synthetic content is growing rapidly, making verifying video authenticity critical. Compliance by TwelveLabs addresses this by integrating NVIDIA Synthetic Video Detector for real-time content scoring. Combining NVIDIA’s frame-level detection with TwelveLabs’ contextual reasoning delivers a unified workflow to catch policy violations and flag synthetic media seamlessly.

“As generative video becomes cheaper, better, and more prevalent, broadcasters need the speed and scale to verify what’s real. TwelveLabs’ integration of NVIDIA’s Synthetic Video Detector into its compliance workflow gives content teams frame-level authenticity checks without slowing review.”
— Richard Kerris, Vice President of Media and Entertainment, NVIDIA

A Smarter Compliance Workflow
Compliance by TwelveLabs specifically assists compliance teams in the following ways:

  • Ingests video and runs analysis against regional or fully custom rule packs. Compliance by TwelveLabs gives compliance leads and operations teams direct control over the rules themselves, with full versioning as those rules change.
  • Generates findings with context, not just labels. Returns evidence, not just labels. Every flag includes written justification (timecode, visual/audio context, and applied rules), allowing reviewers to confirm findings in seconds.
  • Provides a clear reviewer workflow, updated in real time. Compliance by TwelveLabs presents a flagged-moment timeline, with the choice to accept, reject, or annotate. Reviewers can mark a false-positive for reclassification. They can also track status progression (needs review → under review → reviewed), all from the dashboard.
  • Flags AI-generated video. Powered by NVIDIA Synthetic Video Detector, Compliance by TwelveLabs screens footage for synthetic manipulation in real time, delivering confidence scores alongside findings to flag fabricated content before broadcast.
  • Supports rule pack authoring. Teams can build via form, auto-generate from imported PDFs, or start from 40+ pre-configured regional packs, making setup and ongoing management remarkably simple.
  • Includes quality telemetry and versioning. This consists of approval/rejection metrics, non-regression validation, and side-by-side pack or model comparisons.
  • Offers exports and API-first access. TwelveLabs delivers signed JSON, PDF, and CSV reports. It also gives full API access to compliance data and actions.
  • Delivers a fully managed SaaS solution. TwelveLabs handles hosting and updates, so teams get easy deployment and minimal ongoing maintenance.

TwelveLabs has simplified compliance since the introduction of its models, but the new SaaS solution significantly enhances capabilities to make global video compliance seamless. And as the first application built on TwelveLabs’ video intelligence platform, it lays the groundwork for future advancements. Its shared foundation of tenant isolation, asset management, indexing, orchestration, and reviewer tooling means the company can ship new video workflow applications faster than ever.

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AI SEO and GEO Tools: What Brands Need as the EU Officially Classifies ChatGPT as a Search Engine

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AI SEO and GEO Tools: What Brands Need as the EU Officially Classifies ChatGPT as a Search Engine

Azoma - InternetRetailing

The European Commission has designated ChatGPT a Very Large Online Search Engine, placing it alongside Google and Bing. Azoma explains what AI SEO and GEO tools should deliver as AI search goes mainstream

Azoma, the Agentic Commerce Optimisation platform that helps brands drive revenue through AI shopping agents like ChatGPT, Google Gemini, Amazon Rufus and Walmart Sparky, today set out what brands should look for in AI SEO and generative engine optimisation (GEO) tools, as the European Commission officially classifies ChatGPT as a search engine.

On August 31, the European Commission designated ChatGPT a “Very Large Online Search Engine” under its Digital Services Act, placing it in the same legal category as Google and Bing. With over one billion weekly active users globally, ChatGPT is now both the largest AI platform and, officially, a search engine. The classification puts a regulatory stamp on a shift brands have been watching closely: a growing share of product discovery is happening inside AI-generated answers rather than on traditional search results pages, and the platform where it is happening fastest now carries the same legal designation as Google. AI SEO and GEO are the disciplines built to address this shift.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

Key Facts

  • AI SEO and GEO: the practice of optimising brand information, content and product data so AI platforms discover, understand and recommend a brand’s products. AI SEO uses search-familiar language for the same discipline GEO (generative engine optimisation) describes.
  • EU classification (European Commission, August 31, 2026): ChatGPT designated a Very Large Online Search Engine under the Digital Services Act, alongside Google and Bing.
  • Scale: ChatGPT has surpassed one billion weekly active users globally (OpenAI, August 2026).
  • Each agent cites differently (Azoma analysis, Q2 2026): ChatGPT 41% earned media / 37% retailer; Gemini 41% retailer / 37% earned media; Sparky 36% earned media / 30% brand.com / 27% retailer; Alexa for Shopping 73% affiliate / 16% earned media.
  • Implication: there is no single AI SEO or GEO strategy that works across all agents. Brands need tools that track and optimise per agent.

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

What are the best AI SEO and GEO tools?

There is no independently established universal best AI SEO or GEO tool. Brands evaluating platforms should look for five core capabilities: prompt-level visibility tracking across multiple AI agents, citation-source analysis showing which sources each agent cites in a brand’s category, competitive benchmarking, content and product-data optimisation workflows, and the ability to act on findings rather than just report them. Azoma combines these capabilities in a single platform covering ChatGPT, Gemini, AI Overviews, Perplexity, Amazon Rufus, Alexa for Shopping and Walmart Sparky.

Which AI SEO or GEO platform should I use?

The right platform depends on which AI agents matter most for a brand’s category and what the tool can do beyond reporting. Some platforms track visibility but leave the optimisation to the brand. Others provide the tracking and the workflows to close the gaps in one place. Azoma provides both, with prompt-level tracking across all major AI shopping agents and the content, product-data and citation workflows to act on what the tracking reveals.

Why isn’t traditional SEO enough for AI search?

Traditional SEO targets rankings on a search results page, where every brand competes for a click from a list. AI platforms work differently: they return a synthesised recommendation or short list, assembled from cited sources, before the shopper has visited a single brand or retailer site. With the EU now classifying ChatGPT alongside Google as a search engine, the distinction is no longer theoretical. A brand that ranks well in traditional search is not automatically visible in AI answers, because each AI agent cites a different balance of sources. Azoma’s analysis of millions of shopping agent citations found no two agents cite the same source mix, so optimising for search alone leaves a growing share of product discovery unaddressed.

How can I track my brand’s visibility across AI search platforms?

Because each AI agent generates a different answer for each phrasing of a question, a brand’s presence varies from one prompt to the next. A single spot-check tells very little. Azoma runs a brand’s category prompts across ChatGPT, Gemini, AI Overviews, Perplexity, Amazon Rufus, Alexa for Shopping and Walmart Sparky at scale and reports, prompt by prompt, where the brand appears, where competitors appear instead, how share of voice compares, and how all of that changes over time.

Max Sinclair, Founder and CEO of Azoma

“The EU just classified ChatGPT as a search engine, alongside Google and Bing. That makes official what brands have been seeing for months: AI platforms are where a growing share of product discovery now happens. AI SEO and GEO are how brands stay visible in that shift. The challenge is that every AI agent cites different sources, so there is no one-size-fits-all strategy. You need to know what each agent trusts in your category and earn your way into it.”

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AI Assistants Used to Answer Questions. Now They Want to Run the Business

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AI Assistants Used to Answer Questions. Now They Want to Run the Business

File:Hostinger Logo.png - Wikimedia Commons

AI chat assistants learned to answer questions. Then, they learned to solve problems. Now, companies are extending those conversations beyond support.

Customer support AI used to have a clear job: answer the question, or send the customer to someone who could. Newer AI assistants can complete routine tasks themselves, from resetting access to updating account details. The next shift is bigger – AI that stays useful after the support issue is solved.

Research firm Gartner predicts that by 2028, 60% of brands will use agentic AI across marketing, sales, and support to provide more continuous, personalized interactions.

Zendesk’s 2026 report points in the same direction from the customer side: 81% of consumers want conversations to continue without backtracking, and 74% are frustrated when they have to repeat information.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

The common thread is context. An AI that knows what a customer owns, what they were trying to do, and what happened before can do more than answer a ticket.

Hostinger, an AI-first online business growth platform with over five million customers worldwide, is now applying that idea at scale. Its new Hostinger Agent combines customer support with specialized AI for marketing, SEO, content and visuals, analysis, and recurring tasks.

The AI behind it handles roughly 1.5 million conversations each month – or around 35 requests every minute – and resolves 91% without human intervention.

“The first challenge was getting AI to answer correctly. Then it was getting AI to actually solve the problem,” said Emilis Strimaitis, Head of Product Innovation at Hostinger. “Now that the vast majority of issues are resolved automatically, the more interesting question is why the conversation should stop there.”

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

A customer can come with a broken DNS record and leave with the launch campaign written and the weekly report scheduled. Another can come asking how to get more traffic and leave with an email campaign created and sent.

The reason this is possible has less to do with another leap in chatbot intelligence than with what the AI can already see and use. A customer’s website or store, domain, hosting, business email, email marketing, previous conversations, and ongoing work can all sit within Hostinger. That removes much of the setup required by standalone AI agents: connecting tools, granting permissions, and repeatedly explaining the business before the agent becomes useful.

Hostinger is taking the same approach inside AI Builder, where Hostinger Agent is available while customers create websites, stores, apps, and other online projects. Someone can build a project and simultaneously ask for technical help, discuss SEO, plan a launch, or analyze performance without moving between an editor, a support center, and several dashboards.

“The AI industry has spent the past two years giving people more assistants, copilots, and agents to choose from. We want customers to stop choosing between them,” Strimaitis said. “When the AI already knows what the customer is building and what they are trying to achieve, fixing the immediate problem is only part of the job. The real value is helping them grow online.”

Hostinger has also changed what happens when the AI cannot confidently resolve a technical issue alone. Instead of automatically transferring the customer to a live-chat queue, a Customer Success specialist can step in when needed to add context and validate the response, while the same conversation continues.

Hostinger calls the role AI CX Engineer. Since the model was introduced at the end of the second quarter, the share of specialist-guided AI conversations resolved without escalation has risen from 41% to 72%, while the share requiring live chat has fallen from 10% to 4.5%. Median resolution time for those AI conversations is around three minutes, compared with more than 50 minutes for live chats.

Customer support has traditionally been somewhere people go when the product stops working. Agentic AI is beginning to turn it into something broader: a persistent interface that knows what the customer is doing, fixes what went wrong, and stays useful for whatever comes next.

If that model spreads, the important measure of AI support may no longer be how many tickets it can deflect. It may be how much useful work it can carry forward without making the customer start over.

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PwC and Palantir Expand Strategic Alliance to Help Organizations Scale Enterprise AI

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PwC and Palantir Expand Strategic Alliance to Help Organizations Scale Enterprise AI

PricewaterhouseCoopers – Wikipedia

Expanded collaboration can help organizations build intelligent enterprises through scaled enterprise AI, M&A transformation, and ERP modernization

PwC US and Palantir Technologies Inc. announced an expansion of their strategic alliance to help organizations use data and AI to transform critical business operations and deliver measurable enterprise value. The alliance will initially focus on three priority transformation areas: scaling enterprise AI, transforming mergers and acquisitions, and modernizing enterprise resource planning (ERP) systems.

The expanded collaboration combines Palantir’s artificial intelligence and data platforms with PwC’s industry, engineering, and business transformation experience. Together, PwC and Palantir will bring AI deeper into their clients’ enterprise — transforming how decisions are made, how work gets done and how organizations address complex business challenges.

The investment reflects a renewed focus by PwC and Palantir on areas where AI is helping reshape how complex transformations are delivered, including data migrations, agentic workforce solutions, and technology integrations and separations. PwC is also investing in expanding its technical and functional talent across these areas.

“AI’s greatest opportunity isn’t in isolated use cases — it’s in fundamentally changing how enterprises operate,” said Patrick Pugh, Global Alliances & Ecosystem Leader, PwC. “By bringing together PwC’s business transformation and industry experience with Palantir’s technology, we’re helping clients transform critical operations, make better decisions and deliver measurable results.”

“Palantir enables institutions to preserve and expand their alpha,” said Sameer Kirtane, Head of US Commercial at Palantir. “We’re proud to expand our alliance with PwC, pairing Palantir’s platforms with PwC’s business transformation expertise to turn complex data and regulatory challenges into real business outcomes.”

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

Scaling enterprise AI through engineering and managed services

PwC and Palantir can help organizations move AI from pilots into production through joint engineering, implementation and managed services capabilities. By combining Palantir’s technology with PwC’s engineering, industry and business transformation experience, the alliance can help clients accelerate implementation, scale AI across critical business functions and build the capabilities required to sustain transformation over time.

PwC was recently named a leader in the Palantir ecosystem for its strengths in AI engineering and managed services. This recognition was driven by success helping its clients deliver measurable outcomes, including improving supply chain operating efficiency up to 10% for a food manufacturer, increasing forecasting accuracy to 90-95% for a grocery retailer and reducing out-of-service vehicles by 40% for a car rental company.

Building on that momentum, the expanded alliance can help clients scale AI into critical business functions, including supply chain and logistics, customer lifecycle management, cyber and digital risk, capital project planning and real estate management.

Transforming M&A through an AI-native deals platform

PwC and Palantir are introducing the industry’s first AI-native deals IT platform enabled by Palantir Foundry and Palantir’s AI Platform (AIP) to help organizations execute mergers, acquisitions and divestitures with greater speed and confidence. The platform is designed to help organizations execute deals up to 50% faster while reducing one-time transaction costs up to 45%. By accelerating integration and separation activities, organizations can unlock synergies sooner, divest or spin off businesses faster and ultimately drive greater deal value and stronger shareholder returns.

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Modernizing ERP with AI-enabled data transformation

PwC and Palantir are helping organizations address one of the biggest sources of risk in ERP transformation: getting the data right before implementation. By combining PwC’s deep SAP expertise and industry experience with Palantir’s AIP, they can help clients identify process inefficiencies, improve data quality and assess transformation decisions earlier — reducing risk while creating a faster, more predictable path to transformation.

This approach can help organizations across industries, including telecommunications, utilities and consumer products, accelerate SAP transformation, improve data readiness and establish a stronger foundation for AI-driven innovation.

Across these areas, PwC and Palantir can help organizations move beyond isolated AI use cases to embed AI into the systems, workflows and operations that power their businesses — connecting technology transformation with measurable enterprise value.

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Tech Mahindra Launches AWS Agentic Process Transformation CoE to Redefine AI-Led Business Operations

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Tech Mahindra Launches AWS Agentic Process Transformation CoE to Redefine AI-Led Business Operations

Tech Mahindra Unveils Refreshed Brand Identity to Mark 39 Years of Innovation and Impact

Tech Mahindra, a leading global provider of technology consulting and digital solutions to enterprises across industries, announced the launch of its Amazon Web Services (AWS) Agentic Process Transformation (APT) Center of Excellence (CoE), a strategic initiative designed to accelerate enterprise adoption of Agentic AI through scalable, outcome-driven business transformation. The AWS APT CoE will deliver scalable AI solutions that drive measurable results for customers across industries.

The CoE combines Tech Mahindra BPS’ deep process expertise with AWS cloud and Agentic AI capabilities to help organizations move from AI experimentation to measurable business impact. Built as a scalable AI execution engine, the AWS APT CoE will allow enterprises to deploy industry-specific AI solutions that improve operational efficiency, reduce costs, enhance decision-making, and accelerate pilot-to-production cycles. The initiative reinforces Tech Mahindra’s collaboration with AWS while strengthening its ability to deliver governed, enterprise-scale AI transformation across industries including telecom, healthcare, banking and financial services, retail, and manufacturing.

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“Enterprises are moving quickly on AI, but many still struggle to scale beyond pilots and fragmented use cases,” said Birendra Sen, President – Business Process Services, Tech Mahindra. “With the AWS APT CoE, we are bringing together Tech Mahindra BPS’ process expertise and AWS-native AI capabilities to help customers operationalize Agentic AI with stronger governance, faster execution, and measurable business impact.”

Katie Pender, Chief Operating Officer, Target Group, said, “Since introducing the Collections Guru agent, we’re seeing encouraging early results, including anticipated efficiency gains of around 40% in the areas where it’s been rolled out. It’s been a valuable step in how we’re modernising our operations.”

Chandra Pinapala, GSI Director, AWS, said, “In a time of rapid technological change, a Center of Excellence becomes the anchor that helps partners and customers learn together, deliver value faster, and reimagine business processes with confidence.”

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The APT CoE is already delivering measurable business impact through its first jointly developed solution. Collections Guru — an agentic AI-powered collections agent co-developed by Tech Mahindra and AWS as part of the APT CoE — was deployed by Target Group, a leading UK-based financial services outsourcing provider, to transform arrears management operations. Built on AWS cloud and AI infrastructure, the solution delivered approximately 40% efficiency gains by autonomously optimizing collection strategies through agentic AI, representing the type of production-grade, jointly engineered offering the CoE is designed to scale across industries.

The launch further strengthens Tech Mahindra BPS’ go-to-market strategy for AWS-powered AI services by expanding customer opportunities, enabling scalable delivery models, and accelerating AI engagements through industry-focused innovation and execution.

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PlayTiger Brings Agentic Orchestration to Roblox Through ChatGPT and Claude

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PlayTiger Brings Agentic Orchestration to Roblox Through ChatGPT and Claude

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130 agent-ready API operations enable AI agents to analyze performance, configure measurement, manage Roblox advertising and coordinate studio workflows beyond standard Roblox APIs.

Toya announced PlayTiger connectors for ChatGPT and Claude, bringing its analytics, marketing and studio capabilities into the AI tools teams already use. Through a secure, permissioned connection to PlayTiger, AI agents can move beyond answering questions to help carry out actions across Roblox growth workflows.

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Roblox APIs provide essential platform-level capabilities. PlayTiger adds a higher-level orchestration layer built for the commercial, creative and technical work of growing a Roblox experience. Its API exposes 130 agent-ready operations spanning audience and acquisition analytics, attribution, chat and sentiment intelligence, funnel and attention analysis, measurement configuration, Roblox advertising management, reporting and studio workflows.

This allows an agent to work across a continuous cycle: identify a change in performance, investigate its cause, recommend a response, execute the response and measure the result. Teams could ask an agent to define markers or funnels, generate deep links and promotional codes, launch surveys, manage Roblox advertising, schedule reports or coordinate selected development workflows—all from a ChatGPT or Claude conversation.

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“Most AI integrations stop at insight,” said Anat Shperling, CEO of Toya. “By making PlayTiger’s measurement, advertising and studio capabilities available inside ChatGPT and Claude, we are enabling AI agents to help teams move from analysis to action and continuous optimization within one workflow. The goal is to make AI genuinely useful in the day-to-day work of growing a Roblox experience or while running a campign.”

The connectors are designed to operate within PlayTiger’s privacy framework, with privacy-conscious data handling intended to help customers address applicable obligations under COPPA and GDPR. This is especially important on Roblox, where useful audience intelligence must coexist with strong protections for younger users.

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S-Docs Gives Regulated Enterprises a Governed Path to AI-Powered Document Automation

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S-Docs Gives Regulated Enterprises a Governed Path to AI-Powered Document Automation

S-Docs Introduces New 2024 Rebrand Campaign

New capabilities help compliance-driven organizations move faster on templates, signatures, and agentic workflows, without losing control of the record

S-Docs, a market leader in document automation and e-Signature for Salesforce, announced a major expansion of its platform built for the industries that can least afford to get documents wrong. Public Sector and other highly regulated industries depend on a contract, disclosure, or signed form to establish compliance, authorization, and accountability. This platform expansion gives compliance-driven enterprise teams a faster, more visual way to build documents and brings signature collection into the same workflow as document generation. It also opens the door for AI assistants and agentic platforms to initiate document requests, all while keeping every action securely governed within Salesforce.

AI is already showing up in how enterprises create and manage documents. New data found that 72% of regulated organizations have deployed AI in at least one document workflow, but only 30% have the governance in place to do it safely. For industries where documents create the auditable record of critical business activity, that’s not a small gap. S-Docs built this capability to close it: giving enterprises the speed of AI-driven tools without asking them to give up control over the underlying process.

“Enterprises in regulated industries want the speed and accessibility that AI-driven interfaces promise,” said Brian Stimpfl, CEO of S-Docs. “But they can’t afford to lose control of the business process those interfaces sit on top of. This feature lets our customers move faster and open up document creation to more of their teams, while every document is still generated, tracked, and governed the way their compliance function requires.”

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What’s new:

  • A visual, point-and-click way to build templates. The new Visual Template Editor lets business users design documents on a page, see changes live, and add Salesforce data and conditional logic without writing code. Template creation used to require an admin or a developer. But now it’s something any trained team member can do, cutting the time it takes to launch or update a document.
  • Generate and send for signature in one motion. S-Docs e-Signature is now built into the core platform. Teams can create a document and route it for signature in a single workflow, from a finished PDF or a reusable template with signers already mapped. It’s one less handoff and one less place for a document to stall, which means contracts and disclosures get signed faster.
  • AI Template Agent. The agent converts any business document — a contract, an invoice, a disclosure — into a live, Salesforce-driven template in minutes. It preserves the logos, fonts, colors, and layout, and the organization’s approved language word-for-word. It also maps dynamic content to the appropriate Salesforce fields and places signature and form fields wherever a customer needs to sign, initial, or fill in information. What used to take a team days to update now takes minutes, with no rekeying and no risk of drifting from approved language.
  • Built to work with the AI tools your teams already use. With Headless 360, S-Docs extends governed document generation and e-Signature into AI assistants and agentic platforms — from Salesforce’s Claudeforce to other MCP-enabled experiences — while ensuring document requests initiated in those interfaces still run through Salesforce governance. An AI assistant can understand what a user needs and kick off the request. S-Docs generates the document. Salesforce controls who’s allowed to ask for what. However the request starts, the outcome is the same: a governed document.

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“We’re entering an era where work shifts from static dashboards to conversational AI, and the future of enterprise execution is distributed across whatever interface someone’s already working in — Claudeforce, another AI assistant, or a custom agent,” said Anand Narasimhan, CTO of S-Docs. “Headless 360 lets AI interpret the intent while S-Docs handles the actual document execution, all within the secure boundary of Salesforce. The interface can change. The governance never does.”

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Quickplay Launches Live Operations, Bringing AI-Enriched Orchestration and Operational Control to Live Broadcast Channels

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Quickplay Launches Live Operations, Bringing AI-Enriched Orchestration and Operational Control to Live Broadcast Channels

QUICKPLAY BRINGS GENERATIVE AI TO PROGRAMMERS TO OPTIMIZE STOREFRONT SEARCH AND DISCOVERY TOOLS

Operators can now control distributed stations, enforce standards network-wide, transform newscasts into social and vertical content, correct station errors in real-time all via a single console

Quickplay, the Content to Value Operating System for media and entertainment, announced Live Operations, a cloud-native, centralized management control plane for managing live broadcast and OTT channels. With it, operators can now manage scheduling, signal control, ad decisioning, clip production, and monitoring and observability from one console. AI is distributed across entire live broadcast workflows, enabling newsrooms to apply intelligence in completely new ways including across editorial. Quickplay will publicly debut Live Operations at IBC 2026, Hall 5.G86.

Ideal for broadcasters and streaming operators running live-linear and FAST channels, news organizations managing distributed stations without full-time on-site engineering staff, sports rights holders with regional blackout requirements, and multi-channel operators running multiple simultaneous channels, Live Operations provides operational control at scale. At a time when broadcasters spend approximately 75% of their time on technical workflows, this capability unchains them from those responsibilities so they can focus on delivering the high-quality live programming viewers depend on.

Most operators manage live across a stack of tools that don’t share signals: scheduling in one system, signal control in another, ad break management in yet another, with clipping handled as a separate post-production workflow entirely. When something breaks, teams find out late and must work across multiple systems to fix it.

“Many broadcasters today use AI to do smart things in metadata, in packaging, in ad decisioning, each creating individual value, yet completely disconnected from the others. With live programming, the time needed to connect these dots is time operators simply don’t have. Viewers will have moved on, as will the revenue,” said Paul Pastor, Co-Founder and Chief Business Officer, Quickplay. “AI at a single step creates value. But AI orchestrated across every step, across an entire broadcast network, creates compounding value. At IBC, we’re showcasing the power of this live AI workflow and highlighting the success Television New Zealand (TVNZ) and Gray Media are seeing with it.”

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What Live Operations Does

Live Operations is the operator-facing control plane inside the Content to Value Operating System. From a single console, operators control:

  • Scheduler and EPG Management: Enables operators to manage metadata, and build and manage all content from one, centralized location including live events, VOD assets, slates, and replays. Unscheduled gaps and schedules conflicts are flagged and corrected before going live.
  • Live Channel & Signal Control: Gives users control over what’s on air at each moment including input switching, slate insertion, fallback triggering, stream acquisition, and channel start and stop operations, all from a single dashboard.
  • Ad Break and SCTE-35 Management: Enables users to automate ad break timing through SCTE-35 cues. Users can also view real-time metadata to improve ad decisioning, a revenue protection feature for ad-supported channels.
  • Live Disruption and Fallback: Delivers automated and manual fallback protection for signal loss and unexpected disruptions. When the live input drops below configured health thresholds, the platform automatically routes output to a pre-configured looped VOD fallback asset without operator intervention. Fallback at any time can proactively be triggered at any time, and is local to the Quickplay platform, never dependent on an external signal source.
  • Live-to-VOD and Clip Factory: Transforms each newscast into a catalog of distributable content automatically. AI analyzes live event recordings and packages it into a series of branded short clips, complete with new metadata, ready for verticalization and syndication, removing the burden of responsibility from producers and reporters.
  • Monitoring & Observability: Ensures real-time visibility into every layer of the live delivery chain via a unified dashboard.

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“Live has no margin for error,” said Juan Martin, Co-Founder and Chief Technology Officer, Quickplay. “Live Operations challenges today’s status quo by eliminating the need for disconnected systems so that if something breaks down during a live broadcast, teams are notified and a fix is in process in real-time. No dead air, no missed SCTE cues, no failed signals. This is AI doing what it should do, backed by the assurance of a Content to Value Operating System purpose-built to support transformation.”

Live Operations is a part of Quickplay’s Content to Value Operating System which connects every step of digital media production and monetization into one smart system, built on five engines: Stream, Enrich, Activate, Engage, and Maximize. Live Operations lives within Stream, which delivers broadcast-grade, scalable streams for live, VOD, catch-up, and virtual channels. As a part of the larger system, Live Operations is inherently connected to other engines, bringing the value of true orchestration to the entire workflow of a broadcast network.

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Mobisoft Infotech Launches AI-Native Modernization Services to Help Businesses Upgrade Their Legacy Software

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Mobisoft Infotech Launches AI-Native Modernization Services to Help Businesses Upgrade Their Legacy Software

Digital Branding Solutions | Mobisoft

The new approach combines AI-powered application discovery, code analysis, modernization, and testing with experienced engineers to reduce transformation risk.

Mobisoft Infotech, an AI-native product engineering and software development company, today announced the launch of its AI-assisted legacy modernization services. It’s a new offering designed to help businesses upgrade aging software systems into platforms ready for artificial intelligence adoption. The service combines AI-powered product discovery, code analysis, modernization, and testing with experienced engineering teams to reduce risk and speed up transformation timelines.

Modernization isn’t just about updating code; it’s about unlocking the data and agility that AI adoption requires, turning legacy barriers into competitive advantages.”

— Ritesh Patil, Founder and Chief Delivery Officer at Mobisoft Infotech

For years, legacy software modernization has given businesses a real opportunity to unlock value trapped in aging systems, even though it has also ranked among the most difficult technology decisions they face. Organizations often know their aging applications need attention. The software may be expensive to maintain, difficult to integrate, dependent on outdated technologies, or increasingly hard to support as experienced developers retire or move on. Yet replacing these systems can be equally risky.

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The reason is simple. Legacy applications often contain years, sometimes decades, of valuable business logic. That has traditionally made modernization a costly and time-consuming undertaking. A well-planned application migration and modernization can preserve that business logic while removing the constraints holding it back, but engineering teams first needed to understand large and often poorly documented codebases, identify dependencies, map business processes, and ensure that changes did not disrupt critical operations.

Artificial intelligence is beginning to change that equation.

AI Is Reducing the Discovery Challenge:

One of the biggest challenges in legacy modernization has always been understanding what already exists. In many organizations, the people who originally built critical systems are no longer with the company. Documentation may be incomplete or outdated, while important business rules remain buried deep within thousands or millions of lines of code.

AI-assisted engineering tools are now helping technology teams analyze codebases, identify dependencies, generate documentation, detect patterns, and support the understanding of complex applications significantly faster than traditional approaches.

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Modernization Becomes More Accessible to Mid-Market Businesses:

Large enterprises have traditionally been better positioned to undertake multi-year modernization programs with significant budgets and large internal technology teams.

Mid-market organizations often face a more difficult situation. They may depend on mission-critical applications built years ago but lack the resources to fund a complete rewrite. As a result, modernization projects are frequently delayed until maintaining the existing system becomes increasingly expensive or risky.

AI-assisted development and modernization are beginning to change the economics. By accelerating activities such as application discovery, code analysis, documentation, testing and refactoring, AI can help engineering teams reduce the time required for some of the most labor-intensive stages of modernization.

That does not mean modernization can simply be automated. It still requires experienced people to make decisions.

The AI Readiness Problem:

The growing interest in artificial intelligence is also creating a new reason for companies to modernize. Many businesses want to introduce AI assistants, intelligent automation and AI agents into their operations. But these initiatives often depend on access to reliable data and connected systems.

Legacy applications can become a significant barrier. Older systems may have limited APIs, fragmented databases, outdated architectures, and disconnected workflows. Even when a company has identified valuable AI use cases, its underlying technology infrastructure may not be ready to support them.

This is creating a growing connection between legacy modernization and AI adoption. Before organizations can fully take advantage of AI, many first need to make their existing systems more accessible, connected, and scalable.

Industry research has repeatedly shown that a large share of enterprise IT budgets goes toward maintaining existing systems rather than building new capabilities. Analysts have long pointed out that many organizations spend the majority of their technology budgets simply keeping legacy applications running. That leaves limited room for innovation, including AI initiatives that leadership teams increasingly view as a competitive necessity.

For mid-market businesses, this tension is often sharper. Smaller IT teams mean less capacity to run parallel projects. A team maintaining a legacy application often has little bandwidth left to explore new AI use cases, even when leadership wants to move faster.

Mobisoft’s approach to AI-assisted discovery aims to directly address this bottleneck. Instead of requiring weeks or months of manual documentation review, the company’s AI-powered analysis tools scan codebases to map dependencies, flag outdated components, surface embedded business rules, and generate structured documentation. Engineering teams can then review these outputs and prioritize which parts of a system to preserve, refactor, or replace.

“Discovery used to be the slowest and most expensive part of any modernization project,” Ritesh Patil said. “Teams would spend months just trying to understand what a system actually did before they could make any real decisions. AI has compressed that timeline substantially, which changes what is realistically possible for a mid-market company.”

Modernize, Don’t Automatically Rebuild:

One of the biggest misconceptions around legacy technology is that every old application needs to be replaced. In reality, different applications require different strategies. Some may benefit from cloud migration. Others may need API enablement, user experience modernization, database upgrades, or selective refactoring. In certain cases, rebuilding may be the right decision.

The key is determining the right approach before significant investment is made. Mobisoft structures its engagements around this principle. Each modernization effort begins with an AI-assisted assessment phase, where automated analysis tools work alongside engineers to evaluate an application’s architecture, code quality, security posture and integration points. The output is a prioritized modernization roadmap rather than a single prescribed solution.

This approach allows businesses to sequence their investments. A company might choose to modernize a customer-facing module first, while leaving a stable backend system untouched until a later phase. Another might prioritize API enablement so that AI tools can safely access data trapped inside an older application, without undertaking a full rebuild.

A New Modernization Model:

As AI capabilities continue to evolve, software modernization is likely to become increasingly data-driven and intelligent.

AI can help teams understand complex applications faster. It can support documentation, identify potential issues, assist developers with refactoring, and generate testing scenarios. At the same time, experienced engineers remain essential for architectural decisions, security, compliance, and validating business-critical functionality. The result is a new model for modernization.

AI for Speed, Human Expertise for Judgment:

Mobisoft’s launch of these services reflects a broader shift happening across the technology industry. Vendors and service providers are increasingly building AI directly into engineering workflows, rather than treating it as a separate tool. For modernization specifically, this means faster assessments, more accurate testing, and a shorter path from initial analysis to deployed changes.

The company said its services are designed to scale across a range of engagement types, from targeted modernization of a single application to broader, multi-system transformation programs. Each engagement includes both AI-powered tooling and a dedicated engineering team responsible for validating changes before they reach production.

For mid-market businesses that have postponed modernization because of cost, complexity, or risk, this combination could create new opportunities. A project that once required a multi-year commitment and a large budget may now be achievable in a shorter timeframe, with more predictable outcomes.

The question may no longer be whether a company can afford to modernize its legacy software. The more important question may be whether it can afford to wait.

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Securityplus FCU Embraces Agentic CRM to Deliver More Connected Member Experiences

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Securityplus FCU Embraces Agentic CRM to Deliver More Connected Member Experiences

Creatio

Baltimore-based credit union connects member data and AI to deliver more intelligent, personalized service

Creatio, an AI CRM and workflow platform where people and AI agents work together — with no limits on users, agents, or scale — announced that Securityplus Federal Credit Union has selected Creatio to embed agentic, no-code technology across the organization, unifying disparate systems into a single, connected view of each member to better understand and meet their financial needs.

Securityplus Federal Credit Union is a member-owned financial cooperative headquartered in Baltimore, offering a range of financial products and services centered on personalized service and seamless experiences. This member-first approach has made the consistency and quality of every interaction a strategic priority, prompting Securityplus to seek a technology partner that could bring that vision to life across the organization.

Like many financial institutions, Securityplus had accumulated a fragmented technology environment. Communications and service requests moved across multiple channels and departments, making ownership and follow-up difficult to track. Employees often had to navigate several systems to piece together a member’s history, from previous interactions and products to service requests. The result was an incomplete view of the member relationship and added complexity for employees trying to deliver consistent service.

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To address its immediate operational needs, Securityplus FCU set out to implement a banking CRM, conducting an in-depth evaluation of multiple providers. Creatio stood out for its combination of no-code technology, automation, integration capabilities, and agentic AI — meeting the credit union’s needs today while providing room to evolve. Securityplus leadership saw particular potential in technology that can help employees navigate information, automate routine activities, and surface relevant insights, freeing up more time for what technology cannot replace: building meaningful relationships with members.

Securityplus is deploying Creatio to give employees a unified 360-degree view of each member and put that insight to work in delivering more personalized, and proactive experiences. The platform will bring member service, relationship management, referrals, and lead management into a single environment, replacing fragmented tools and manual handoffs with consistent workflows for managing requests and identifying opportunities to deepen member relationships. For Securityplus, success will ultimately be measured not by CRM adoption alone, but by whether the technology helps create better experiences and stronger relationships with members.

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“This is more than an investment in technology for Securityplus. It represents an investment in how we want to serve our members and empower our employees in the future. We are intentionally building an organization where technology makes human experience better, not less personal. The right technology should remove friction, provide insights, and give employees more time to have meaningful, impactful conversations. Our partnership with Creatio is an important part of creating that future.”

— Jeffrey Gehris, CCE, Executive Vice President, Chief Strategy and Experience Officer, Securityplus FCU

Securityplus sees tremendous potential for AI in financial services. The credit union is approaching it with the same purpose and responsibility it brings to everything member-facing — using AI to help employees summarize member interactions, surface relevant information, recommend next steps, automate routine activity, assist with service requests, and identify opportunities to better meet a member’s financial needs. Over time, Securityplus expects AI to help the organization recognize patterns and anticipate member needs, moving from reactive to proactive.

“For us, the future is not about choosing between digital innovation and human connection. It is about bringing the two together to create a simpler, smarter, and more personalized member experience.”

— Jeffrey Gehris, CCE, Executive Vice President, Chief Strategy and Experience Officer, Securityplus FCU

Credit unions are built around member relationships rather than shareholder returns, making personal service central to how they compete with larger banks. Securityplus’s deployment reflects a broader shift among community-based financial institutions toward agentic, no-code technology that can modernize member engagement without losing that human connection.

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Genesys Enhances Agentic Virtual Agent Amid Growing Enterprise Adoption

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Genesys Enhances Agentic Virtual Agent Amid Growing Enterprise Adoption

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Faster development, advanced AI reasoning, new voice innovations and deepened enterprise connectivity enable virtual agents to act across business systems and resolve more complex customer requests

Genesys®, a global leader in agentic orchestration for customer experience (CX), announced advancements to Genesys Cloud™ Agentic Virtual Agent that will help organizations automate more complex customer interactions with greater speed, reliability and natural engagement. New enterprise connectivity and interoperability will also expand the ability of Agentic Virtual Agent to securely work with business systems and other AI agents to drive customer outcomes across the enterprise.

Since becoming generally available last March, continual enhancements for Agentic Virtual Agent are making it easier to build, test and optimize autonomous customer experiences alongside the new Scaled Cognition APT-2 large action model as well as new native voice capabilities and integrations with ElevenLabs and Deepgram. Agentic Virtual Agent will also provide deeper Model Context Protocol (MCP) connectivity and Agent2Agent (A2A) interoperability with enterprise platforms.

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Organizations including Global Payments, MTN South Africa, Utility Warehouse, UOL and Charles Sturt University are choosing Agentic Virtual Agent to advance beyond traditional automation. For some organizations, that impact is translating into multimillion-dollar annualized savings. Customers are also reporting improved satisfaction and Net Promoter Score gains of more than 70 points, with some deployments going live in as little as a few weeks.

Increasing the reliability of automated experiences

Genesys is expanding the intelligence behind Agentic Virtual Agent through the latest Scaled Cognition APT-2 large action model, designed to improve reasoning accuracy, factual grounding and execution reliability.

APT-2 supports richer agent specifications, longer and more complex workflows, faster response times and improved multilingual performance. These enhancements help Agentic Virtual Agent reason through sophisticated customer requests and carry work toward resolution within enterprise-defined guardrails, all while helping reduce experience failures that can erode trust.

Creating best-in-class voice experiences

New voice capabilities for Agentic Virtual Agent are designed to enable more natural, responsive conversations. Through End-of-Turn Detection, Agentic Virtual Agent will understand when a customer has finished a thought, helping conversations flow with fewer awkward pauses and interruptions. With Contextual Tuning, Agentic Virtual Agent will automatically adapt its terminology, tone and speaking style to reflect an organization’s business and brand as well as the context of each interaction.

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Genesys is also providing greater customer choice through new integrations with ElevenLabs and Deepgram across voice generation and conversational speech recognition.

  • Through ElevenLabs, organizations will be able to access expressive, natural-sounding voices for engaging virtual agent interactions while maintaining Genesys Cloud governance and enterprise controls.
  • Deepgram will bring real-time speech recognition built for conversational AI, helping Agentic Virtual Agent understand interruptions, turn-taking and changing intent as people speak. Richer, more timely context gives the agent stronger inputs for reasoning and action, supporting faster responses and more reliable task completion.

These new capabilities can make voice interactions with Agentic Virtual Agent feel more fluid and natural, helping organizations deliver engaging customer experiences that increase successful self-service and reduce unnecessary escalations to human agents.

Building trusted agentic experiences faster

Across the development lifecycle, organizations can more rapidly build and deploy Agentic Virtual Agent experiences. With spec-driven development, teams can describe desired customer experiences and outcomes using existing materials such as process documentation, standard operating procedures and interaction transcripts, which AI helps translate into deployable configurations. Development teams can also use a range of tools such as Anthropic’s Claude Code, OpenAI Codex, Cursor and Kiro to create specifications that can be brought into Genesys Cloud for testing and governance, providing flexibility while maintaining enterprise oversight.

Genesys is introducing new AI-assisted authoring that analyzes how Agentic Virtual Agents are designed, identifies opportunities to improve their effectiveness and recommends ways to drive better customer outcomes. New AI-powered testing, expanded reporting and detailed auditability will also help organizations validate Agentic Virtual Agents before deployment, understand their actions and continuously improve performance over time.

Creating the most connected Agentic Virtual Agent

Building on orchestration capabilities from its recent acquisition of Pinkfish, Genesys is expanding Agentic Virtual Agent with more than 500 enterprise integrations and access to over 25,000 MCP-compatible tools, making it easier to connect to the business context, systems and tools behind customer interactions. This will enable Agentic Virtual Agent to securely access CRM, ERP, IT service management, knowledge, collaboration, billing and other business applications to gather context and take action to help resolve customer requests.

Progressing multi-agent enterprise Action

A2A interoperability will enable Agentic Virtual Agent to securely collaborate with specialized AI agents across platforms such as Salesforce and ServiceNow, delegating tasks and coordinating work across multistep business processes. Combined with MCP-based access to enterprise tools, A2A will connect customer conversations to the systems and AI agents needed to reach resolution.

For example, Agentic Virtual Agent will be able to coordinate with specialized AI agents across enterprise platforms to resolve a billing issue, from retrieving account information and evaluating policies to completing backend tasks, while maintaining context throughout the customer interaction.

Agentic Virtual Agent will also support customer engagement across digital channels, including WhatsApp, enabling organizations to bring agentic experiences to customers through the channels they choose while A2A and MCP provide interoperability with the enterprise systems and AI agents behind those interactions.

Global customer momentum

Around the world, organizations are realizing measurable business impact with Agentic Virtual Agent, including:

  • Riachuelo, one of Brazil’s largest fashion retailers, replaced its traditional chatbot with Genesys Agentic Virtual Agent, increasing customer retention from 30% to 84%, improving its CSAT by 60 points within the first year and boosting productivity by more than 400% without adding staff.
  • Zeppelin Rental GmbH, a leading provider of rental and construction support services, is enhancing its digital customer experience with the Genesys Agentic Virtual Agent. By enabling customers to describe their job site needs in natural language instead of having to search through product catalogs, the solution makes relevant products, services and information easier to find. This creates a simpler, more intuitive self-service experience while helping to reduce pressure on traditional service channels.

“Enterprise AI is entering a new phase defined by what it can accomplish for customers,” said Mike Szilagyi, senior vice president and head of product at Genesys. “We’re further strengthening Genesys Cloud Agentic Virtual Agent with more context, intelligence and capabilities to act across the enterprise, work with other AI agents and carry increasingly complex customer requests through resolution. This is how businesses can turn customer intent into meaningful outcomes at scale.”

Genesys Cloud Agentic Virtual Agent capabilities announced today, including the Scaled Cognition APT-2 model, new development tools and the Deepgram integration, are available now with ElevenLabs expected to be available in the third quarter of the company’s fiscal year (Aug 1-Oct. 31, 2026). Additional capabilities, including native voice enhancements, A2A interoperability and AI-assisted authoring, are expected to become generally available in the fourth quarter of the company’s fiscal year (Nov. 1, 2026-Jan. 31-2027).

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Roomvu Launches ‘Found’ to Help Agents & Brokers Rank on AI Search

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MTS Staff Writer
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0
Roomvu Launches 'Found' to Help Agents & Brokers Rank on AI Search

Roomvu logo

The free AI visibility tool helps real estate professionals rank high on ChatGPT and Gemini

Roomvu, the AI-driven video marketing platform that automates social media for real estate professionals, launched Found by Roomvu. It’s a free visibility tool that not only shows professionals how they appear across Google and AI assistants, but hands them a prioritized plan to fix it.

We built Found to give professionals total clarity on how AI engines see them and a roadmap to start winning searches in their local market.”

— Sam Mehrbod, CEO of Roomvu

Search has fundamentally changed. Before a client picks up the phone, they research and increasingly ask AI engines and search platforms questions like: “Who’s the best real estate agent near me?” or “Top mortgage broker in my city.” While most professionals can be found when a client searches their exact name, the vast majority of professionals remain invisible during these discovery searches where new client leads are now generated.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

“In the past, having a simple website and a few online reviews was enough to survive. Today, when clients look for an expert, they ask AI tools for direct recommendations,” said Sam Mehrbod, Chief Executive Officer of Roomvu. “If you only show up when someone types your exact name, you’re missing out on the vast majority of new business. We built Found to give professionals total clarity on how AI engines see them and a roadmap to start winning searches in their local market.”

Google and AI models like ChatGPT, Gemini, and Claude now actively scrape social platforms to evaluate a professional’s local authority, profile alignment, and recent activity before making a recommendation.

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

Found by Roomvu measures all of these signals in about 60 seconds, analyzing profile consistency across channels, total review presence, and current search footprint. Critically, it turns that diagnosis into immediate action. Alongside a channel-by-channel scorecard and a read on how AI tools describe them, each report returns a prioritized action plan.

The tool identifies conflicting details across profiles to ensure consistent entity indexing, highlights review gaps that keep AI models from trusting a profile and generates a localized list of the exact questions local buyers and sellers are searching for, giving professionals the precise content roadmap needed to earn top AI recommendations.

“A report that only tells you you’re invisible isn’t worth much, and most SEO tools just dump a wall of confusing metrics on your lap,” added Mehrbod. “Found is built to be actionable: zero fluff, zero friction, and a clear checklist starting with the exact questions your local clients are asking.”

The insight behind the tool is simple: AI assistants recommend the professionals who show up consistently and answer real client questions across all channels. That is exactly what the core Roomvu platform automates — creating unique, local content for each of a professional’s channels and posting it every week, so the authority that drives AI recommendations compounds automatically over time without added effort.

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Wayne County Businesses Now Have a Local Partner for Web Design, SEO & Marketing That Tracks Real Results

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MTS Staff Writer
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0
Wayne County Businesses Now Have a Local Partner for Web Design, SEO & Marketing That Tracks Real Results

INSTANT WEB TOOLS | Instant Web Tools, LLC

Instant Web Tools, LLC helps local businesses stop guessing which marketing works — by putting their website in front of ready-to-buy customers and tracking…

Local businesses across Wayne County looking to attract more customers who are already searching for their products and services now have a dedicated partner in Instant Web Tools, LLC, a Richmond, Indiana-based web design, SEO, and digital marketing company.

Instant Web Tools specializes in building high-performing websites and putting them directly in front of the right audience — shoppers and clients who are actively looking to buy, not just browsing. Unlike marketing approaches that rely on guesswork, Instant Web Tools equips every client website with tracking on the metrics that matter most: phone calls, appointment bookings, and website traffic, giving business owners clear, actionable data on what’s actually driving new customers through their doors.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

“Too many small businesses invest in marketing without ever knowing what’s working,” said Dennis Alejo, founder of Instant Web Tools, LLC. “Our goal is simple — get the right customers to a business’s website, and then prove it with real numbers: real calls, real bookings, real traffic. No guessing, just results.”

Instant Web Tools’ services include:

Custom Web Design — professionally built, mobile-friendly websites designed to convert visitors into customers
Search Engine Optimization (SEO) — helping local businesses rank higher and get found by nearby customers actively searching for their services
Call & Appointment Tracking — proprietary tracking tools that measure phone calls and booking activity generated directly from a business’s website and marketing campaigns
Digital Marketing Strategy — data-driven campaigns built around what is measurably working, not assumptions

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

The company operates under three focused brands: instantwebtools.co, the central hub for its full suite of services; rwebdesigns.com, dedicated to custom web design; and instantseo.me, focused on local search engine optimization.

Instant Web Tools is currently serving businesses throughout Wayne County, Indiana, with plans to expand its reach into neighboring markets in the coming months.

Business owners interested in learning how Instant Web Tools can help them attract more ready-to-buy customers — and finally see clear proof of what their marketing is doing — are encouraged to reach out directly.

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NameHero Launches HeroicGuard, Email Security That Stops Phishing Before It Hits the Inbox

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prweb
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NameHero Launches HeroicGuard, Email Security That Stops Phishing Before It Hits the Inbox

About Us - NameHero®

Protect every mailbox on a domain starting at $2.96 a month. No message cap. No mailbox move. One MX change.

NameHero today announced HeroicGuard, the company’s email security and spam filtering service. HeroicGuard sits in front of existing mail (HeroicMail, Google, Microsoft, or another provider), scans inbound and outbound traffic in real time, and stops spam, phishing, ransomware, and malware before they reach the inbox.

Founder and CEO Ryan Gray said he built the announcement around a problem he actually had. A NameHero catch-all address, public since 2015, was taking more than 1,000 junk messages a day. Spam filters were already in place. The box was still unusable.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

“I’m the owner of a web hosting company. Surely we offer something better than what I’m doing,” Gray said. NameHero manager James Hart told him to enable inbound mail filtering. Setup was one DNS change. Hart had it live in minutes.

“Since that day I haven’t worried about that email address once,” Gray said. “I spend a couple of minutes on it instead of hours.”

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

NameHero has offered the filtering stack for nearly three years. HeroicGuard is the product name, with four packages: Sidekick, Hero, Legend, and MSP Reseller. There is nothing to install. After order, the domain’s MX records point at HeroicGuard. Mail is cleaned, then delivered to the mailboxes the customer already has.

HeroicGuard starts at $2.96 per month with no cap on messages. SuperHero support is available 24/7 by phone, chat, and email.

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Moore and RMI Direct Marketing Announce Strategic Alliance

By
PRNewswire
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0
Moore and RMI Direct Marketing Announce Strategic Alliance

Moore

RMI recommends clients transition list management and brokerage services to Moore’s AudienceFirst Media.

Moore, the leading constituent experience management (CXM) company, and RMI Direct Marketing announced a strategic alliance through which RMI is recommending that its clients transition their list management and brokerage services to AudienceFirst Media, a division of SimioCloud, a Moore company. This isn’t an acquisition.

As a result of this alliance, RMI concluded operations on Sept. 1. Client notifications began last week, with a transition process put in place to provide continuity of service as clients move their list management and brokerage services to AudienceFirst Media.

Marketing Technology News: MarTech Interview with Mark Listes, CEO @ Pendulum Intelligence

“For more than 40 years, RMI has been focused on helping our clients succeed, and that commitment was at the center of our decision about the future,” said Rich Leary, president of RMI Direct Marketing. “We selected Moore and AudienceFirst Media because of the strong alignment between our companies and their deep expertise in list management, brokerage and data-driven audience strategies. AudienceFirst Media understands this business and our clients’ needs, and I am confident they are the right team to carry this important work forward.”

AudienceFirst Media is an established industry leader in data solutions, creating data-driven integrated strategies for nonprofits, publishers, catalog and retail clients across a wide range of verticals. Its team specializes in identifying audiences to optimize performance and marketing investment while helping organizations maximize the value of their data assets. These capabilities closely align with the list management and brokerage services RMI has provided its clients.

Marketing Technology News: How MarTech Is Enabling Autonomous Brand Engagement Across Channels?

“RMI has built strong client relationships and an impressive business over decades, and we are honored that they selected Moore and AudienceFirst Media as the right partner for their clients,” said Gretchen Littlefield, CEO of Moore. “AudienceFirst Media brings the experience, data expertise and strategic capabilities to provide continuity for RMI clients without a break in service. We look forward to building on the strong foundation RMI has established.”

Several RMI account representatives have joined Moore as part of the AudienceFirst Media team and will continue supporting their clients. This continuity of people and expertise provides RMI clients with a seamless transition.

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