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RegEd Expands AI-Powered Advertising Review with the Launch of AI Compliance PreCheck for Broker-Dealers

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Globe Newswire
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RegEd Expands AI-Powered Advertising Review with the Launch of AI Compliance PreCheck for Broker-Dealers

New pre-review capability, RegEd PreCheck powered by Eddie AI, helps broker-dealers identify compliance risk and improve content quality before formal compliance review begins.

RegEd, the leading provider of compliance solutions for financial services firms, announced the launch of AI Compliance PreCheckSM for Broker-Dealers, a new capability within its AI-Powered Advertising Review solution. By embedding AI-driven compliance intelligence earlier in the advertising content lifecycle, AI Compliance PreCheck enables firms to quickly identify potentially problematic language, validate required disclosures, and receive AI-driven revision suggestions before materials are formally submitted for compliance review.

As regulatory expectations continue to evolve and marketing teams move faster across digital channels, broker-dealers face growing pressure to balance speed-to-market with consistent compliance oversight. In this context, the traditional submit-review-revise cycle does not scale. AI Compliance PreCheck introduces a proactive, AI-assisted layer of compliance that helps content creators and compliance teams identify risk earlier, align content with firm policies and FINRA requirements, and submit higher-quality, compliance ready materials.

AI Compliance PreCheck helps broker-dealers significantly reduce rework, accelerate approvals, and improve the overall quality and compliance readiness of marketing content – delivering cleaner submissions, fewer review cycles, and faster time to market without sacrificing compliance rigor.

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AI-Enabled Compliance Across the Advertising Review Lifecycle, Powered by Eddie

AI Compliance PreCheck builds on the AI-driven intelligence Eddie already delivers within RegEd’s Advertising Review solution, including AI-assisted reviews, disclosures management, media transcription, and advanced document comparison. Eddie applies regulatory guidance, firm policy, and workflow automation consistently across the full advertising review lifecycle.

With AI Compliance PreCheck, that intelligence now extends upstream to the point of submission. Content submitters can now receive immediate, actionable AI-driven compliance feedback prior to entering the formal review process, gaining early visibility into potential compliance risk, disclosure gaps, and misalignment with firm policies. By introducing guidance earlier in the process, firms can reduce avoidable review cycles, improve submission quality, and maintain strong governance across the full content lifecycle.

“AI Compliance PreCheck reflects how we’re continuing to embed AI where it creates the most value for our customers,” said Ethan Floyd, Chief Product Officer at RegEd. “By extending compliance guidance upstream to the point of submission, firms can help both compliance and marketing teams move faster without sacrificing compliance rigor.”

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Key capabilities extended to the point of submission:

  • Problematic language detection – Identifies potentially misleading, promissory, exaggerated, or non-compliant statements aligned with FINRA advertising standards.
  • Suggested revisions – Provides AI-generated recommendations to help content authors remediate issues before submission.
  • Disclosure alignment – Flags missing or insufficient disclosures and suitability language based on regulatory expectations and firm-defined requirements.
  • Policy and brand consistency – Supports alignment with firm-approved messaging, disclosures, and internal advertising standards.

Through these capabilities, AI Compliance PreCheck delivers measurable benefits for broker-dealers by:

  • Cutting rework before it starts through earlier identification of compliance risk
  • Improving submission quality with actionable, AI-driven feedback for content creators
  • Accelerating approval timelines by increasing first-pass approval rates
  • Scaling compliance oversight without adding manual effort as content volume grows

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Oracle Expands AI Agent Studio for Fusion Applications with Agentic Applications Builder and New Intelligent Workflow Tools

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PRNewswire
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Oracle Expands AI Agent Studio for Fusion Applications with Agentic Applications Builder and New Intelligent Workflow Tools

Latest additions to AI Agent Studio for Fusion Applications help organizations scale adoption of outcome-driven AI and measure value

Oracle announced the latest updates to Oracle AI Agent Studio for Fusion Applications, a complete development platform for building, connecting, and running AI automation and agentic applications. The latest updates to Oracle AI Agent Studio include a new agentic applications builder as well as new capabilities that support workflow orchestration, content intelligence, contextual memory, and ROI measurement.

“As organizations move beyond pilots and begin operationalizing AI across the enterprise, they need the ability to tailor AI to their unique workflows, expertise, and operational priorities,” said Chris Leone, executive vice president of Applications Development, Oracle. “With AI Agent Studio for Fusion Applications, we are helping customers and partners build the foundation for a more autonomous enterprise. Builders can create AI automations and agentic applications using natural language that are powered by enterprise AI agents capable of reasoning, taking action across business systems, and continuously executing processes. This enables organizations to move beyond dashboards and copilots to AI-powered applications that actively run the business, with the governance, trust, and security that enterprises require.”

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The latest updates to Oracle AI Agent Studio support the new Fusion Agentic Applications and rapidly growing Fusion Applications AI ecosystem. With Oracle AI Agent Studio, organizations can now build, connect, and run AI automation and agentic applications using reusable Oracle, partner, and external agents without traditional application development. In addition, built-in observability, ROI measurement, security, auditability, and governance ensure agents deliver measurable value and operate responsibly at scale.  The latest updates include:

  • Agentic Applications Builder: Helps organizations build outcome-focused agentic applications from Oracle, partner, and external agents. The AI-powered, natural language-based environment helps users select agents, compose workflows, and connect enterprise data without traditional coding or application development requirements.
  • Workflow orchestration: Helps organizations ensure reliable, enterprise-grade execution at scale across complex business processes. With the new orchestration capabilities, customers can coordinate multi-step, multi-agent execution with rules that control how work moves between steps, built-in logic, and human oversight.
  • Content intelligence: Helps organizations bring together unstructured first- and third-party data with transactional data to expand automation, improve decision-making, and unlock greater value from enterprise information. This helps organizations transform unstructured content into usable, contextual signals that agents can understand and act on.
  • Contextual memory: Helps organizations automate end-to-end processes, not just single tasks, and reduce repetition and friction by enabling agents to remember context across interactions, workflows, agent collaboration as well as learn from user behavior. Only relevant memories are retrieved for a specific task, and agents can share context to improve coordination of tasks and outcomes.
  • LLM multimodal capabilities: Help organizations unlock insights and automate decisions using all forms of enterprise data by enabling agents to process and generate non-text inputs and outputs, including images, audio, and video.
  • Monitoring, observability, and prompt playground: Helps organizations build trust in agent deployments, iterate quickly, adjust prompts, and successfully scale agents in production by enabling real-time visibility, testing, and debugging of agent behavior and performance.
  • Agent ROI dashboard: Helps organizations understand the business impact of AI initiatives by enabling them to measure the outcomes and value delivered by agents. This includes insights on the time saved, cost savings, and productivity gains per agent across workflows, teams, and business functions.

Growing network of Oracle-certified experts helps customers optimize AI

With 63,000-plus certified experts trained in Oracle AI Agent Studio, customers can work with experienced partners to identify high-value use cases, accelerate deployments, and optimize AI performance and governance across the enterprise.

Available at no additional cost, Oracle AI Agent Studio delivers easy-to-use tools, including orchestration, advanced testing, robust validation, and built-in security, to help Oracle Fusion Applications customers and partners create and manage AI agents and agentic applications.

By leveraging the same technology that Oracle uses to create AI agents and agentic applications, Oracle AI Agent Studio enables users to easily extend pre-packaged agents and applications, and/or create new ones, then deploy and manage them across the enterprise. AI agents and agentic applications designed in the Oracle AI Agent Studio seamlessly integrate with Oracle Fusion Applications and can collaborate with third-party agents to complete complex and multi-step processes.

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Oracle PartnerNetwork support

“Organizations are recognizing that one-size-fits-all AI is not enough, and they need the flexibility to choose the right large language model for each use case while configuring solutions to match unique business requirements,” said Lan Guan, chief AI and Data officer at Accenture. “The latest updates to Oracle AI Agent Studio expand the options available to our clients and help them compose customized agentic applications.”

“Enterprise AI is evolving quickly from task-based assistance to outcome-driven automation, and Deloitte clients want that shift delivered with the controls and accountability their business requires,” said Mauro Schiavon, Deloitte Global Chief Commercial Officer, Oracle Business. “Oracle and Deloitte are working together to help organizations build and run agentic applications at scale – connecting data, workflows, and governance with Oracle AI Agent Studio and new Agentic Applications Builder.”

“To deliver real value, AI should be built into the systems companies already run their business on,” said Rob Fisher, Global Head of Advisory, KPMG International. “By connecting trustworthy AI agents directly into everyday workflows, Oracle is helping organizations put AI to work at scale and drive meaningful change across the business.”

“As customers move from isolated AI use cases to outcomes-focused AI across the enterprise, they need a development platform that can orchestrate workflows, manage context, and measure impact,” said Kevin Sullivan, Oracle Global Alliance Leader, PwC. “We’re excited that the expanded Oracle AI Agent Studio—including the new Agentic Applications Builder—creates a faster path to bring PwC’s Agent Powered Performance engine to life for our customers, so they can quickly activate our existing assets and accelerators, streamline adoption, and measure value across Fusion-powered workflows at scale.”

About Oracle Fusion Cloud Applications
Oracle Fusion Cloud Applications provide an integrated suite of AI-powered cloud applications that enable organizations to execute faster, make smarter decisions, and lower costs. Oracle Fusion Applications include:

  • Oracle Fusion Cloud Enterprise Resource Planning (ERP): Provides a comprehensive suite of AI-powered finance and operations applications that help organizations increase productivity, reduce costs, expand insights, improve decision-making, and enhance controls.
  • Oracle Fusion Cloud Human Capital Management (HCM): Provides a unified AI-powered HR platform that connects all people-related processes and data to help organizations automate tasks throughout the employee lifecycle, improve the employee experience, and give HR leaders actionable workforce insights.
  • Oracle Fusion Cloud Supply Chain & Manufacturing (SCM): Provides a unified AI-powered platform that integrates supply chain and operations processes and helps organizations enhance resilience and quickly adapt to market changes.
  • Oracle Fusion Cloud Customer Experience (CX): Provides a suite of AI-powered applications that helps organizations manage marketing, sales, and service processes to win business, build stronger customer relationships, and improve customer experiences.

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Oracle Unveils AI Database Agentic Innovations for Business Data

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PRNewswire
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Oracle Unveils AI Database Agentic Innovations for Business Data

New agentic AI capabilities designed for business data accelerate enterprise innovation and help defend enterprises from AI-era threats 

Available on all platforms from multicloud to on-premises

Oracle announced new agentic AI innovations for Oracle AI Database that will help customers rapidly build, deploy, and scale secure agentic AI applications that are suitable for full-scale production workloads. Oracle AI Database architects agentic AI and data together across operational databases and analytic lakehouses. It enables AI agents to securely access real-time enterprise data wherever it resides and easily use business data with LLMs trained on public data to provide business insights. Customers can choose AI models, agentic frameworks, open data formats, and deployment platforms. In addition, customers running on Oracle Exadata further benefit from Exadata Powered AI Search, which enables agentic AI at the highest scale with accelerated AI queries for high-volume, multi-step agentic workloads.

“The next wave of enterprise AI will be defined by customers’ ability to use AI in business-critical production systems to safely deliver breakthrough innovations, insights, and productivity,” said Juan Loaiza, executive vice president, Oracle Database Technologies, Oracle. “With Oracle AI Database, customers don’t just store data, they activate it for AI. By architecting AI and data together, we help customers quickly build and manage agentic AI applications that can securely query and act on real-time enterprise data with stock exchange-level robustness in every leading cloud and on-premises.”

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Innovate faster with AI designed for data
With agentic AI capabilities architected for data, Oracle AI Database helps eliminate the need to build and maintain data-movement pipelines that add complexity and security risk, and may produce worse outcomes. New capabilities include:

  • Oracle Autonomous AI Vector Database provides the simplicity of a vector database with the full power of Oracle AI Database. It enables developers and data scientists to quickly and easily build vector-powered applications using intuitive APIs and an easy-to-use web interface. Built on top of Oracle Autonomous AI Database, it combines an easy-to-use developer experience with enterprise-grade security, reliability, and scalability. Currently in limited availability, Autonomous AI Vector Database is accessible through either the Oracle Cloud free tier, or a developer tier with low-cost pricing. Customers can seamlessly upgrade with one click to the full power of Oracle Autonomous AI Database when their requirements grow, with full support for graph, spatial, JSON, relational, text, and parallel SQL—eliminating the need for separate databases and complex cross-database agentic workflows.
  • Oracle AI Database Private Agent Factory enables business analysts and domain experts to rapidly build and safely deploy data-driven agents and workflows. The AI Database Private Agent Factory provides a no-code AI agent builder that runs as a container in public clouds or on-premises, maintaining data security by enabling customers to build, deploy, and manage AI agents without having to share data with third parties. AI Database Private Agent Factory includes multiple pre-built AI agents specialized for data, including a Database Knowledge Agent, a Structured Data Analysis Agent, and a Deep Data Research Agent. Other approaches rely on external agent orchestration or must make calls to different types of databases. Oracle has simplified agentic AI for business users by architecting it into its AI Database, providing consistency and simplicity—with enterprise-grade security, resiliency and scalability for every agentic workload.
  • Oracle Unified Memory Core lets users store context for AI agents in a single system. It uniquely enables low-latency reasoning across vector, JSON, graph, relational, text, spatial, and columnar data in one converged engine, with consistent transactions and security.

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Minimize AI data risk
Oracle AI Database helps customers safeguard data from external attacks, insider misuse, accidental disclosure, and unintended exposure to LLMs across multicloud, hybrid, and on-premises environments. New capabilities include:

  • Oracle Deep Data Security implements powerful end-user-specific data access rules in the database. Each end-user or AI agent acting on behalf of an end-user can only see the data that the end-user is allowed to see. It can implement sophisticated persona and function-based rules. For example, what parts of a customer account specific sales reps, finance reps, shipping clerks, executives, support reps, and customer relatives are allowed to see. This provides unique end-user data security capabilities to protect against new AI-era threats, such as prompt injection, using declarative, database-native controls that implement least-privilege access. By centralizing and decoupling security from application code, it enables customers to easily determine who can see what data and continuously update access rules as new threats emerge, and it effectively provides guardrails for agents working within Oracle AI Database. Security at the source of the data – the database – offers superior protection when AI agents directly access data on behalf of end-users.
  • Oracle Private AI Services Container enables customers with stringent security requirements to run private instances of AI models while avoiding sharing of data with third-party AI providers, or sending data outside of their firewall. In addition, it helps mitigate performance bottlenecks by allowing customers to securely offload compute-intensive AI tasks, such as vector embedding generation, outside the database, helping keep all data secure within their environment. The container can be deployed in the public cloud, on private clouds, or on-premises, including in air-gapped environments.
  • Oracle Trusted Answer Search provides enterprises with an accurate, testable, and deterministic way to use AI to provide answers to end-users. Instead of directly using an LLM to answer an end-user question, Trusted Answer Search uses AI Vector Search to match the question to a previously created report. This helps mitigate the risk that probabilistic LLMs may occasionally hallucinate or misunderstand a query.

End AI data lock-in with open standards and frameworks
Running in all leading cloud providers, in hybrid deployments, and available on-premises, Oracle AI Database gives customers the flexibility to choose the AI model and application-tier agentic framework that best fits their needs. They can build, deploy, and run agentic AI applications using open standards and data formats. New capabilities include:

  • Oracle Vectors on Ice provides customers with native support for vector data that is stored in Apache Iceberg tables. AI Vector Search can read vector data directly from Iceberg tables, create vector indexes to accelerate vector search, and automatically update these indexes as the underlying vector data changes. Oracle Vectors on Ice allows AI search on data lake data and enables unified search across business data in the database and vectors stored in a data lake. This enables customers to achieve unified intelligence across databases and data lakes.
  • Oracle Autonomous AI Database MCP Server enables external AI agents and MCP clients to securely access Autonomous AI Database and its capabilities without custom integration code or manual security administration. It complements the Oracle SQLcl MCP Server for Oracle AI Database, available via the Oracle SQL Developer VS Code extension.

“In the era of agentic AI, a unified memory core is essential for agents to maintain context across diverse data types, such as vector, JSON, graph, columnar, spatial, text, and relational, without the latency or staleness of external syncing,” said Steven Dickens, CEO and principal analyst, HyperFRAME Research. “Only Oracle AI Database delivers this in a single, mission-critical engine with concurrent transactional and analytical processing, high availability, and ironclad security, enabling real-time reasoning over live business data. Organizations without this foundation will struggle with fragmented, unreliable agents, while those leveraging Oracle gain a decisive edge in scalable AI deployment.”

Customers and developers can leverage the new agentic AI capabilities for Oracle AI Database now, to start developing and deploying game-changing agentic AI applications without moving data, learning new skills, or struggling with database scalability and the lack of agentic AI security guardrails.

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Stop AI from Guessing: Appier Enables Agents to Assess Confidence Before Acting Appier Company Logo

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PRNewswire
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Stop AI from Guessing: Appier Enables Agents to Assess Confidence Before Acting Appier Company Logo

New Framework Boosts Reliability, Cost Efficiency, and Scalability for Enterprise AI

As an AI-native Agentic AI-as-a-Service (AaaS) company, Appier announced its latest research paper, On Calibration of Large Language Models: From Response to Capability, as part of its ongoing investment in advanced AI innovation. The study introduces Capability Calibration[1]—a new framework designed to address the overconfidence and hallucination challenges of large language models (LLMs) by enabling AI systems to better assess their own ability to solve a given task.

This research equips AI agents with a critical capability: estimating the likelihood of solving a problem before generating an answer. By introducing a quantifiable self-assessment mechanism, AI systems can make more reliable decisions and allocate computational resources more efficiently—improving the reliability, cost efficiency, and scalability of enterprise AI deployments.

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From Response Accuracy to Problem-Solving Capability
Traditional LLM calibration focuses on response-level confidence, estimating whether a single generated answer is correct. However, because LLM outputs are inherently stochastic, the same query may produce different responses across multiple attempts. Therefore, a single response often fails to reflect the model’s true capability.

In practice, organizations are less concerned with whether one answer is correct and more interested in whether a model can consistently solve the task. Appier’s capability calibration framework addresses this by shifting evaluation from single-response confidence to the model’s expected success rate for a given query. This moves the evaluation target from a single answer to the model’s broader problem-solving capability, providing a more practical measure of real-world performance.

Teaching AI Agents to “Know Their Limits”
“AI agents should not only generate answers but also understand the limits of their own capabilities,” said Chih-Han Yu, CEO and Co-Founder of Appier. “With capability calibration, an agent can estimate its probability of success before responding and allocate resources intelligently. Simple queries can be handled quickly, while complex tasks can automatically leverage stronger models or additional compute. This transforms AI from a passive tool into a system that actively manages resources, optimizes costs, and improves decision quality—an essential foundation for scaling enterprise-grade AI agents.”

Experimental Results: High-Quality Calibration at Low Cost
The research clarifies the theoretical relationship between capability calibration and traditional response calibration[2], and evaluates multiple confidence estimation approaches across three large language models and seven datasets covering knowledge-intensive and reasoning-intensive tasks. Methods tested include:

  • Verbalized confidence[3]: The model explicitly states its confidence, in text or as a percentage.
  • P(True)[4]: Estimates the probability that the answer is correct based on generation signals.
  • Linear probes[5]: Use internal model signals to assess whether it truly understands.

Results show that the linear probe method provides the best balance between cost and performance, with computational cost even lower than generating a single token while maintaining reliable confidence estimation.

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Two Key Applications: Improving Inference Efficiency and Resource Allocation
The framework enables two practical use cases. First, pass@k[6] prediction, a widely used metric for evaluating LLMs in complex tasks. Capability-calibrated confidence estimates the probability that a model will produce at least one correct answer after k attempts, without actually generating multiple responses. Second, inference resource allocation, where computational resources are dynamically distributed based on predicted task difficulty. Harder problems receive more attempts, allowing more tasks to be solved within the same compute budget.

Building a Decision Foundation for Trustworthy AI Agents
Capability calibration enables AI agents to establish a stable and quantifiable confidence signal before taking action. This allows agents to determine whether they can solve a task independently, when to call external tools, and when to seek human assistance—helping AI systems operate more reliably in uncertain environments.

Advancing Capability Calibration to Power Agentic AI Applications
Looking ahead, Appier’s AI research team will continue advancing capability calibration by improving model evaluation methods and expanding the framework to applications such as model routing, human–AI collaboration, and trustworthy AI systems. Leveraging Appier’s deep expertise in AI and marketing technology, these research advances will be translated into product capabilities, accelerating the deployment of Agentic AI in advertising and marketing decision-making and helping enterprises operate more efficiently in an increasingly complex digital landscape.

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Adam Cunningham Named Global CEO of Allied Global Marketing

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Adam Cunningham Named Global CEO of Allied Global Marketing

Kelly Estrella Promoted to Chief Operating Officer as Clint Kendall Transitions to Allied’s Board of Directors

Allied Global Marketing (Allied) announced that Adam Cunningham, previously Chief Strategy Officer, has been appointed Global Chief Executive Officer. Kelly Estrella, previously Chief of Marketing Operations, has been promoted to Chief Operating Officer. The appointments position Allied for its next phase of growth as an integrated marketing partner to brands across entertainment, gaming, sports, hospitality, tourism and location-based experiences, combining deep category expertise with proprietary tools, data and applied AI. Cunningham succeeds Clint Kendall, who will become a member of Allied’s Board of Directors.

“Adam has helped shape Allied’s strategy at a pivotal moment for our industry,” said Kendall. “As marketing becomes more integrated, more data-led and more operationally complex, he brings the strategic clarity, commercial focus and modern operating discipline needed to lead Allied forward.”

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As CEO, Cunningham will oversee Allied’s global business and lead the agency’s focus on integrated growth, operational discipline and the continued development of proprietary tools, data and applied AI that help teams work with greater speed, precision and insight. He will work across strategy, creative, paid, earned, owned and analytics to strengthen cross-market collaboration, deepen client partnerships and advance workflow capabilities that improve delivery while keeping human judgement at the centre.

“Clients need partners who can connect creative ambition with operational rigour, audience insight and faster, more measurable execution,” said Cunningham. “Allied is uniquely built for that moment. We have deep category expertise, a strong global team and the opportunity to turn our integrated model, proprietary tools, data and applied AI into an even stronger advantage for the brands and experiences we help grow.”

As Chief Operating Officer, Estrella will lead global operations, with responsibility for aligning teams, strengthening delivery discipline and scaling Allied’s capabilities across markets and clients to support the agency’s continued growth.

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“Kelly is one of the most trusted and effective leaders in our business,” Cunningham added. “She brings the operational discipline, cross-market credibility and clarity of execution this next chapter requires. Her leadership will be critical as we scale the business with greater consistency, speed and accountability.”

Kendall joined Allied Global Marketing in 2001 and has served as CEO since 2009, leading the company through more than two decades of growth and evolution. In his new role on Allied’s Board, he will support continuity during the leadership transition and work closely with Allied’s ownership group, Belmont Capital.

Together, these appointments strengthen Allied’s leadership and position the agency to expand its integrated offer, deepen strategic partnerships and deliver more measurable growth for clients in the moments that shape culture.

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Proven ROI Launches Proven Cite to Help Businesses Win in the Era of AI Search

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MTS Staff Writer
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Proven ROI Launches Proven Cite to Help Businesses Win in the Era of AI Search

Proven Cite, AI Visibility Platform

Proven ROI launches Proven Cite to help businesses get cited in AI search results.

Proven Cite, a groundbreaking platform from Proven ROI, has officially launched, introducing a new category of software designed to help businesses understand, measure, and improve how artificial intelligence systems evaluate and cite their content.

Search has changed. If AI does not cite your content, you do not exist in the answer economy. Proven Cite shows you exactly how to fix that.”

— John Cronin, Founder of Proven ROI

As search behavior rapidly shifts from traditional keyword queries to conversational AI interactions, businesses face a new challenge: visibility is no longer determined solely by rankings, but by whether AI systems choose to reference and cite their content.

Proven Cite is built to solve exactly that.

A New Era of Search Requires a New Kind of Tool

Search is undergoing a fundamental transformation. Instead of presenting users with a list of links, platforms like ChatGPT, Gemini, and Perplexity now generate direct answers often citing only a handful of sources.

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This shift has created a visibility gap.

Traditional SEO tools measure rankings, backlinks, and traffic. But they were not designed to analyze how large language models interpret, trust, and extract information from content.

Proven Cite fills that gap.

The platform evaluates websites across 13 AI-readability and citation factors, helping businesses understand why competitors are being cited, and what changes are needed to earn those citations themselves.

From Rankings to Citations: The Next Evolution of Visibility

According to Proven ROI, the future of digital visibility is no longer about being found, it is about being selected.

“Businesses are realizing that ranking on page one is no longer enough,” said a spokesperson for Proven ROI. “If your content is not structured in a way that AI can understand, trust, and extract, you will not be included in the answers users actually see.”

This aligns with a broader industry shift toward what Proven ROI calls Generative Engine Optimization (GEO), the practice of optimizing content for AI driven discovery, not just traditional search engines.

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Proven ROI has been at the forefront of this movement, helping companies build AI ready websites designed to surface in answers, not just search results.

How Proven Cite Works

Proven Cite provides businesses with a clear, actionable framework for improving AI visibility.

Key capabilities include:

AI Readability Scoring
Analyze how effectively AI systems can process and interpret your content.

Citation Gap Analysis
Identify why competitors are being cited instead of your brand.

LLM Evaluation Factors
Score content against the core elements that influence AI trust and extraction.

Optimization Recommendations
Get step-by-step guidance to improve citation likelihood across AI platforms.

The platform is designed to be both technical and accessible, giving marketing teams, founders, and agencies a transparent view into how AI systems “see” their websites.

Built for the Future of Digital Marketing

Proven ROI, headquartered in Austin, Texas, has built its reputation on helping businesses connect marketing directly to revenue through data driven strategies and integrated systems.

With Proven Cite, the company is extending that mission into the rapidly evolving world of AI search.

The launch reflects a larger shift in how digital success is measured:

From traffic → to visibility in answers
From rankings → to citations
From keywords → to structured, trustworthy content

“Most companies are still optimizing for how search worked yesterday,” the company noted. “Proven Cite is built for how discovery works today, and where it is going next.”

Why This Matters Now

The rise of AI generated answers is accelerating across every major platform.

As users increasingly rely on AI to make decisions, the brands that are cited gain disproportionate trust, authority, and influence, often before a user ever visits a website.

This creates both a risk and an opportunity:

Brands that fail to adapt may become invisible
Brands that optimize early can dominate emerging channels

Proven Cite positions itself as the intelligence layer that helps businesses navigate this transition with clarity and confidence.

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Palo Alto Networks Unveils the Industry’s Most Secure Browser Built for Agentic AI

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Palo Alto Networks Unveils the Industry's Most Secure Browser Built for Agentic AI

Prisma SASE enhancements secure AI-driven work across the entire modern enterprise 

Palo Alto Networks, the global cybersecurity leader, unveiled a major evolution of Prisma Browser, introducing the industry’s most secure browser built for the Agentic AI era. As employees shift from merely using AI as a tool to now utilizing autonomous agents that act on their behalf, Prisma Browser converts the web into a secure AI-driven workspace. Users can now unlock new levels of productivity with Agentic AI, without compromising security.

Today, the browser is the primary engine of modern work and where users spend 85% of their workday. However, the browser’s role is rapidly expanding beyond a simple window to the web and is now the central hub for agentic AI interactions. While this shift unlocks unprecedented efficiency, a new class of sophisticated risks unique to autonomous AI has emerged, such as shadow AI agents, prompt injection attacks and agent hijacking. Prisma Browser paves the way for this new era of work by providing agentic capabilities in combination with a secure foundation to protect these autonomous workflows.

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Anand Oswal, Executive Vice President of AI & Network Security, Palo Alto Networks
“Organizations are unleashing a new workforce of agents, however, you cannot give autonomy without security. By embedding AI-powered data protection and securing AI interactions directly in the browser, leaders can now confidently greenlight strategic AI initiatives that were previously stalled. Prisma Browser isn’t just securing an interface, it’s securing a new way of work.”

Prisma Browser introduces key innovations that bring secure agentic AI to end users by:

  • Powering the Agentic Workspace: Enables organizations to leverage the LLM of their choice across all models and platforms. Prisma Browser allows teams to utilize the most effective AI tools for any specific task, maximizing productivity and accelerating autonomous workflows.
  • Securing AI Interactions: Automatically discovers user AI activity and enforces content-aware boundaries to keep agents within their intended scope. Prisma Browser prevents sensitive data from leaking to unmanaged or public AI tools during automated tasks.
  • Preventing Agent Hijacking: Identifies and blocks prompt injection attacks—including malicious instructions hidden within websites designed to hijack AI agents—keeping automated workflows on track and preventing agents from being manipulated into unauthorized actions.
  • Enabling Global Compliance: Provides real-time distinction between human actions and automated AI tasks. By assessing the intentions of both human and non-human identities, Prisma Browser enables total accountability and compliance with evolving global AI regulations.

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Jonathan Jaffe, Chief Information Security Officer, Lemonade
“The browser has evolved to deal with a whole new landscape of threats with AI threats, like prompt injection or the use of AI extensions that are unsafe. The browser will continue to be the single control point as agents end up doing things on behalf of the user, but through the browser. So I see the browser as being the dominant control point for protecting employees against bad actions. As we allow people to experiment with agents that use the browser to run tasks, we feel more comfortable doing that with Prisma Browser.”

The Industry’s Most Comprehensive SASE Solution for the Agentic AI Era
AI-driven productivity starts in the browser but must be secured across the entire enterprise. Prisma Browser’s evolution is just one of the critical innovations made to Prisma SASE, the most comprehensive SASE solution built for the agentic AI era. Powered by Precision AI, Prisma SASE delivers Universal Zero Trust, providing consistent protection and unmatched performance wherever work happens. By converging secure agentic browsing, autonomous operations, and AI-powered data protection into a unified solution built on a resilient architecture, Prisma SASE transforms AI-driven workflows into a secure growth engine that operates at machine speed.

Prisma SASE extends best-in-class capabilities by:

  • Enabling Autonomous Operations: Empowers IT to accelerate productivity by eliminating the manual troubleshooting and “ticket fatigue” that stall operations, allowing teams to focus on strategic AI growth.
  • Securing Data End-to-End: Discovers and protects sensitive data throughout the entire AI lifecycle—within AI tools and agents and across the entire organization—to prevent leakage into shadow AI environments and protect information across endpoints, network, and SaaS.
  • Providing Business Continuity: Delivers cloud-scale security and operational resilience to high-bandwidth campuses, helping ensure seamless performance and uninterrupted operations for critical resources.

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AiPPT.com Enhances Its AI Image Generator with Nano Banana 2 to Support Smarter Slide

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AiPPT.com Enhances Its AI Image Generator with Nano Banana 2 to Support Smarter Slide

AiPPT.com announced an update to its built-in AI image generator with the addition of the advanced model Nano Banana 2. The update gives users more ways to create visuals that fit their slides while keeping the design process inside the presentation editor.

AiPPT.com works as a modern AI presentation maker that combines writing, layout creation, and media generation in one workspace. The new model strengthens that experience by helping users generate images that match slide themes without leaving the editor.

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Expanding Image Generation Options

This presentation creation tool already supports several AI image systems. Users can still access earlier models from the Nano Banana family, including Nano Banana and Nano Banana Pro. AiPPT.com also connects to other popular models such as Flux models, Imagen models, and Seedream 4.0.

Nano Banana 2 expands this collection and improves prompt understanding. The model produces visuals that suit many presentation scenarios. Teachers may create diagrams. Marketers may produce concept illustrations. Creative scenes can also be generated through short written prompts.

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A Broader AI Presentation Environment

Nano Banana 2 joins a larger ecosystem inside AiPPT.com. Users can generate a presentation from prompts, documents, and images. A unique feature even lets them download PPT from links: simply enter a webpage URL to generate a clear, editable outline, turn it into a complete slide deck, and save it.

Users also gain access to a large design library. The free PPT template library features over 200,000 slide templates with diverse themes, supporting business reports, academic presentations, marketing materials, and training slides.

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Elastic Eliminates the SOAR Automation Tax with Native Workflows

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RAVATAR Brings More Natural Real-Time Voice Interaction to AI Avatars with Gemini Native Audio

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Elastic Workflows brings native automation directly into Elastic Security with no separate SOAR tool required

Elastic , the Search AI Company, announced that Elastic Workflows, a native automation capability with direct access to alerts, cases, and investigation data, is now built directly into Elastic Security. By bringing native automation to the agentic security operations platform that already includes unified SIEM and XDR, Elastic is eliminating the “SOAR automation tax” by removing the need for a separate SOAR to turn insights into action.

Traditionally, security teams have relied on a standalone SOAR to automate investigation and response. This adds complexity, requiring extra vendors, integrations, and ongoing maintenance. In a security landscape where adversaries are using AI to execute attacks in minutes, organizations can no longer rely on a response workflow stitched together across several vendors. Elastic Workflows embeds automation directly within Elastic Security, giving teams the ability to act on alerts and security data quickly, all without the need for additional tools or extra add-ons.

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“Using Workflows enabled our SOC to spend so much more time on the things that matter. On a daily basis, we ran through 500 alerts, spending 3 hours creating cases and enriching them manually. Using Workflows, this is all done automatically, saving up to 2.5 hours a day.” – SOC leader, European government agency.

“If you’re not using AI to fight AI, you’re already behind, and if you’re still relying on separate SOAR tools, you’re even further,” said Mike Nichols, general manager, Security at Elastic. “Elastic Workflows brings AI-driven automation directly to where data lives with no extra tools or integration overhead.”

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Elastic Workflows allows analysts to execute scripted playbooks for consistent, repeatable responses alongside AI agents that reason through complex investigations. A single Workflow combines scripted automation with AI reasoning, helping teams respond effectively when an investigation doesn’t match a known pattern.

Built on the proven Elasticsearch Platform

Workflows gets its agentic capabilities through integration with Agent Builder, a native feature of Elasticsearch designed for building custom AI agents. Because Elastic Security is built on the Elasticsearch data and AI platform, agents reason with superior context, delivering more accurate results.

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Zeta Marketing Platform Named a Leader in Analyst Report on Email Marketing Service Providers, Q1 2026

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Zeta Marketing Platform Named a Leader in Analyst Report on Email Marketing Service Providers, Q1 2026

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Received the highest Strategy score among all evaluated vendors and the highest possible scores in 11 criteria, including AI Approach, Vision, and Innovation

Zeta Global , the AI Marketing Cloud, announced that the Zeta Marketing Platform has been recognized as a leader in The Forrester Wave™: Email Marketing Service Providers, Q1 2026. The platform, which unifies identity, intelligence, and activation to deliver better experiences for consumers and better results for brands, received the highest score of any evaluated vendor in the Strategy category and the highest possible score (5.0) in 11 criteria.

As enterprises replace legacy martech stacks with AI-driven platforms, marketers are demanding solutions that simplify execution and improve business performance. Zeta sees this recognition as a reflection of its long-term investment in a platform purpose-built to reduce complexity, sharpen personalization, and accelerate business growth.

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With AI embedded at its core, the Zeta Marketing Platform integrates identity resolution, customer data management, predictive intelligence, and omnichannel activation into a single connected system. Forrester’s evaluation noted that “Zeta’s approach to AI, data management, and data governance stand out.”

“The era of fragmented martech is over,” said David A. Steinberg, Co-Founder, Chairman, and CEO of Zeta Global. “In the AI era, marketers need a single system that knows their customers, predicts what’s next, and proves its impact without requiring an army of specialists to operate it. That’s what we’ve built. We’re proud that Forrester has recognized us among top vendors in the market.”

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The Zeta Marketing Platform achieved the highest possible scores in 11 criteria, including Identity Resolution, Data Management, Data Governance, Skills Improvement, AI Approach and Perspective, Regulatory Compliance, Agency Services, Vision, Innovation, Roadmap, and Partner Ecosystem.

Forrester’s report also noted that Zeta “will work well for marketers of all industries and capability levels, particularly those who want to maximize their customer insights by experimenting with AI” and that customers specifically praise Zeta’s accessibility.

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DFI Retail Partners with SymphonyAI to Drive AI-Driven Merchandising Capabilities

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DFI Retail Partners with SymphonyAI to Drive AI-Driven Merchandising Capabilities

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Leading Asian retailer aims to strengthen its merchandise planning foundation with unified, data-driven retail intelligence

DFI Retail, a leading Asian retailer has launched a pilot with SymphonyAI, a global leader in Vertical AI platforms, to evaluate advanced retail intelligence capabilities designed to enhance enterprise merchandise planning. The initiative reflects DFI’s disciplined, customer-first approach to assessing how next-generation retail insights can support better decisions across promotions, assortment, clustering, and space planning.

“DFI is committed to strengthening our data foundation to enable faster, more consistent merchandising decisions that improve quality and value for customers across Asia.” — Crystal Chan, Group Chief Technology and Information Officer, DFI Retail Group

As competition intensifies and customer expectations evolve, DFI is investing in a proven and scaled AI solution that aims to strengthen retail fundamentals, improve process efficiency, and support more agile merchandising decisions.

Crystal Chan, Group Chief Technology and Information Officer, DFI Retail Group said,“This strategic initiative with SymphonyAI reflects DFI’s commitment to improve our core data foundation and technology solutions for our team members. We aim to make better and faster merchandising decisions to continuously improve quality and value for our customers across Asia, all enabled by AI.”

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Exploring Next-Generation Retail Intelligence

Retailers around the world are embracing technologies that help turn disparate data into unified insight, enhancing planning, responsiveness, and operational clarity. DFI’s initiative embodies this broader industry evolution toward connected retail intelligence — where data, planning, and execution insights coalesce to inform decision pathways and support retailer priorities.

Why DFI Selected SymphonyAI’s Retail Platform for Evaluation

DFI’s decision to work with SymphonyAI reflects the alignment between DFI’s future performance aspirations and the platform’s retail specialization, unified data and architecture, and proven presence in enterprise retail environments.

“Leading retailers are investing in connected, data-centric platforms that help align planning and execution while strengthening decision confidence,” said Manish Choudhary, President, SymphonyAI Retail. “Our retail platform is designed to support customers as they evaluate advanced intelligence capabilities in real operating conditions and build foundations for longer-term transformation.”

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Retail Impact Context

The importance of investments like DFI’s is underscored by findings from SymphonyAI’s Economic Impact of Vertical AI research, which highlights the scale of opportunity when retail planning and execution are informed by domain-specific intelligence. That study estimates up to $54 billion in annual economic impact in the retail and grocery sector alone, driven by optimized promotion planning, assortment & personalization, and inventory management.

In documented customer examples, Vertical AI platforms have helped global grocery and enterprise retail organizations achieve measurable results such as multi-million-dollar profit improvements, significant sales lift, and more efficient cross-functional coordination — showing what’s possible as retailers bring connected insight to core operational decisions.

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March Networks and VIVOTEK Merge Branded Video Security Businesses to Deliver Greater Scale and Expanded Portfolio

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March Networks and VIVOTEK Merge Branded Video Security Businesses to Deliver Greater Scale and Expanded Portfolio

Vision and Intelligence. Aligned.

March Networks, a global leader in intelligent video surveillance and business intelligence, and VIVOTEK, a leading global provider of IP cameras and cloud video solutions, jointly announced the merger of VIVOTEK’s branded business (OBM) with March Networks to deliver greater scale and a stronger, end-to-end video security portfolio spanning cloud, hybrid, and on-premise video surveillance environments.

Together, the two companies combine complementary strengths in enterprise video management, AI-powered analytics, advanced cameras, and cloud services to accelerate innovation and expand their global security ecosystem.

Following the closing, which is expected in mid-April, the combined organization will be led by Peter Strom, President and CEO of March Networks.

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“This integration is about driving greater scale and accelerating long-term growth,” said Strom. “By bringing together two market leaders with highly complementary strengths, we are expanding our capabilities and creating new opportunities to deliver more value to our customers and partners. March Networks’ leadership in enterprise video management, analytics, and business intelligence combines with VIVOTEK’s camera innovation, AI capabilities, and direct-to-cloud video technologies to deliver a more powerful, end-to-end portfolio. Together, we are better positioned to help our partners grow and enable their customers to operate more securely and efficiently.”

For customers and partners, the merger expands the available solution portfolio while maintaining the same trusted brands, support teams, and technology platforms they rely on today.

VIVOTEK’s manufacturing (ODM) business will continue to operate independently, while its branded business (OBM) combines with March Networks.

Stronger Together

March Networks is known for the most scalable, reliable, and secure enterprise video solutions used by the world’s largest banks, retailers, transit agencies, and other commercial customers. VIVOTEK is recognized for its broad portfolio of NDAA-compliant IP cameras, leading AI analytics, and VORTEX, its direct-to-cloud video solution, designed for simplified deployment and cloud video management.

Together, the combined organization significantly expands its global scale and innovation capacity, including:

  • Operations across six continents and more than 70 countries, with expected annual revenue of over $200 million USD
  • More than 300 engineers in R&D across four Centers of Excellence in Ottawa, Taipei, Poland, and Italy
  • An expansive network of more than 1,100 certified channel partners worldwide

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“This is a seamless transition for our customers and partners. They will continue working with the same teams they know and trust, while benefiting from greater scale, more choice, and broader global coverage,” said Net Payne, Chief Sales and Marketing Officer. “Whether you’re an existing technology partner, part of our channel ecosystem, or an end customer using our products, we remain committed to delivering the value you have come to expect from each company.”

The combination will take effect following Delta Electronics’ purchase of the remaining VIVOTEK shares it does not already own, which is expected to be completed in mid-April.

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BeyondID and Nexera Announce Strategic Partnership to Deliver Secure, Production-Ready AI for the Enterprise

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BeyondID and Nexera Announce Strategic Partnership to Deliver Secure, Production-Ready AI for the Enterprise

Joint offerings combine AI intelligence and identity governance to help organizations deploy AI that is intelligent, secure, compliant, and operationally resilient from day one

BeyondID, a leading AI-powered Managed Identity Solutions Provider (MISP) and KeyData Cyber Family Company, and Nexera, a leading provider of production-grade AI systems and managed operations, announced a strategic partnership to help organizations accelerate AI adoption without sacrificing security, compliance, or control.

As enterprises rapidly deploy AI platforms, such as Anthropic, Microsoft Copilot, Google Gemini, and OpenAI, they often lack the foundational identity governance required to operate AI safely at scale. Non-human identities (NHIs) such as AI agents, automated workflows, and service accounts represent a growing and largely unmanaged attack surface. Without proper governance, organizations face significant compliance, operational, and security risk.

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The BeyondID and Nexera partnership directly addresses this gap. Nexera brings the Intelligence Layer, designing, building, and operating production AI systems from strategy through managed operations. BeyondID secures the Identity and Trust Layer, governing every AI agent, model, and workflow with identity-first architecture, least-privileged access, and continuous monitoring.

“Enterprises are under enormous pressure to deploy AI quickly, but speed without governance is a liability,” said Arun Shrestha, Founder of BeyondID. “Nexera builds intelligent AI systems while BeyondID ensures every AI agent, model, and workflow is securely identified, governed, and monitored. Now, organizations no longer have to choose between moving fast and staying secure.”

The partnership introduces four integrated go-to-market offerings designed to take enterprises from AI strategy to secure, scalable production deployment:

AI Identity Readiness Sprint (30–45 Days): A rapid assessment that covers AI use cases, platform evaluation, identity and access risk, governance blueprint, and a 90-day execution roadmap.

90-Day Secure Agent Launch: Production-grade AI agent deployment with identity architecture embedded at the build stage, including access controls, secrets management, monitoring, and compliance validation with measurable ROI.

Enterprise AI Platform Hardening: Secure rollout for Anthropic, Microsoft Copilot, Google Gemini, and OpenAI deployments, including shadow AI detection, AI privilege tiering, data segmentation, and regulatory alignment.

AI Operations + Identity Monitoring (Managed): Ongoing managed services covering drift and model monitoring, identity anomaly detection, agent access recertification, and continuous governance optimization.

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Unlike large systems integrators that offer AI strategy without deep identity specialization, BeyondID and Nexera deliver an integrated, execution-focused model. Engagements move from strategy to production in 90 days. Identity governance is embedded at the architecture stage, not bolted on afterward. And both companies offer ongoing managed services — meaning clients receive continuous AI and identity operations support, not one-time project delivery.

“AI is only as powerful as the trust placed in it,” said Tom Wisnowski, CEO at Nexera. “With BeyondID, we can now offer our clients the full stack, from intelligent systems to the identity infrastructure that makes those systems safe to operate at enterprise scale.”

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Banzai Reaches Deal to Acquire Assets of ConnectAndSell, a Profitable Company, More Than Doubling Annual Revenue and Expanding AI Platform Capabilities

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Banzai Reaches Deal to Acquire Assets of ConnectAndSell, a Profitable Company, More Than Doubling Annual Revenue and Expanding AI Platform Capabilities

ConnectAndSell is a Leading AI Sales Acceleration Platform Serving B2B Organizations Across Healthcare, Financial Services & Technology Industries

Proposed Acquisition Strengthens Banzai’s Marketing and Sales Software Platform with Established Revenue-Generating Business

Banzai International, a leading AI marketing technology company, announced that it has reached an agreement on terms to acquire assets of ConnectAndSell, Inc. (“ConnectandSell”), an AI-powered sales enablement platform serving B2B organizations across financial services, healthcare, technology, and other industries. The acquisition is expected to increase Banzai’s annual revenue by approximately $15 million. The two companies have executed a non-binding letter of intent, and the final transaction is expected to close in early Q2 2026, subject to execution of a definitive agreement and closing conditions.

ConnectAndSell’s AI-powered platform is designed to improve seller productivity by helping sales teams spend more time in live conversations with qualified decision-makers. The proposed acquisition would add sales acceleration capabilities to Banzai’s platform and expand the Company’s ability to support customers across a broader portion of the revenue generation process.

Banzai believes the addition of ConnectAndSell would strengthen its position as a provider of integrated marketing and sales technology solutions while creating meaningful cross-sell opportunities across both companies’ customer bases. The transaction would also further Banzai’s strategy of building a broader platform of practical, revenue-generating software solutions.

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“ConnectAndSell has a highly complementary sales acceleration capability,” said Joe Davy, Founder and CEO of Banzai. “We believe the proposed acquisition aligns well with our strategy of acquiring proven AI-powered business solutions. This transaction would expand Banzai’s platform across more of the go-to-market process and create additional opportunities for customer expansion across our platform.”

Financial and Strategic Benefits

  • Expands Platform Capabilities: The proposed acquisition would add sales acceleration functionality to Banzai’s platform, broadening its reach across the go-to-market workflow.
  • Enhances Revenue Generation Offering: ConnectAndSell would extend Banzai’s ability to support customers from audience engagement and demand generation through sales execution and conversion.
  • Creates Cross-Sell Opportunities: Banzai sees the potential to introduce ConnectAndSell’s capabilities to its existing customer base while also expanding Banzai’s broader offerings to ConnectAndSell customers.
  • Supports Platform Expansion Strategy: The proposed acquisition would continue Banzai’s strategy of building a more comprehensive software platform through the addition of complementary, business-critical solutions.

Jonti McLaren, President of ConnectAndSell, added, “We believe Banzai is the right platform to build on what ConnectAndSell has developed over the years. This proposed transaction would position our technology within Banzai’s AI-powered family of products and create new opportunities to deliver value to customers at greater scale.”

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Idomoo Introduces Strata: The First AI Foundation Model for Layered Video

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Idomoo Introduces Strata: The First AI Foundation Model for Layered Video

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Strata goes beyond standard diffusion models, generating fully editable, layered video compositions that are always on brand.

Idomoo announced Strata, a generative AI foundation model that redefines how brands create video content. Unlike standard diffusion-based models that output a single, flat video file, Strata generates layered compositions that can easily be edited and personalized at virtually unlimited scale.

Rather than forcing content into rigid templates, Strata designs custom video blueprints that are a perfect fit every time.

Layered video has long been the standard for professional video production tools like Adobe After Effects but has not been tackled by gen AI to date. Strata not only generates separate layers for text, animation, footage and actors — it designs the full composition, defining placement, contrast, movement, timing and pacing across all layers, all while enforcing nuanced brand guidelines. Part of Lucas AI Video Agent, Strata is the first foundation model purpose-built for this challenge.

“Every other AI video model generates pixels: a flat file you can’t meaningfully edit,” said Danny Kalish, Idomoo cofounder and CTO. “Strata generates structure: independent layers with typography, animation, motion paths and synchronized audio, all composed into a production-ready video blueprint. That’s a fundamentally different technical problem, and solving it is what makes AI video genuinely usable and scalable for enterprises for the first time.”

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Blueprints Over Templates

Many template-based “AI wrappers” have emerged to address the layered video challenge. Their solution is to force generated footage into preset HTML templates, which allow for some editing and brand compliance. But templates are a workaround. They’re never a perfect fit for the content. They’re rigid, offer limited personalization and brand compliance, and simply can’t match studio quality.

Strata works differently. Rather than forcing content into rigid templates, it designs custom video blueprints that are a perfect fit every time. No more forcing a square peg into a round hole.

This means that whether you’re creating a sales video for a bank, an employee onboarding video or an ecommerce ad, your video will always be studio-quality and fully editable.

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Customized to Your Brand DNA

A brand is so much more than fonts and colors. Lucas, Idomoo’s AI video agent, analyzes a company’s approved content to learn its brand voice as well as its specific visual styles, such as imagery and motion cues. It then uses this to build a comprehensive Brand DNA (Design, Narrative and Assets), which Strata applies to any video content generated through Idomoo’s platform, ensuring 360-degree brand compliance.

Personalization at Scale

Strata has personalization at its heart. Each video blueprint is fully personalizable: text, images, footage and more. Personalized data can be added to any layer of the video, seamlessly integrated into the scene. This means brands can meaningfully hyper-personalize videos in real time for millions of viewers in any language.

Strata technology is patent pending. An early access version of Strata is being tested by several of Idomoo’s largest customers and is now available through Lucas AI Video Agent, part of Idomoo’s AI video platform.

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Arc XP Partners with TollBit to Help Publishers Monitor, Control, and Monetize AI Bot Traffic

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Arc XP Partners with TollBit to Help Publishers Monitor, Control, and Monetize AI Bot Traffic

New edge integration enables real-time AI bot detection and creates a structured monetization pathway for AI-driven access to publisher content.

Arc XP, the content platform and operating system built for ambitious media companies, announced a new integration with TollBit, the leading platform that helps publishers and creators monitor, manage, and monetize AI usage of their content. The integration gives Arc XP publishers a turnkey path to understand and generate revenue from AI bots and agents that access their content, powered by TollBit.

As generative AI bots increasingly scrape publisher content to access up-to-date information and generate answers, media organizations face growing infrastructure strain, content commoditization, and limited visibility into how their intellectual property is being accessed. While some publishers have entered into licensing agreements with major AI companies, many lack the infrastructure to systematically detect and manage automated AI traffic.

The Arc XP–TollBit integration addresses that gap.

“AI companies are extracting value from publisher content at scale,” said Sharad Vivek, Global Head of Partnerships and Alliances at Arc XP. “Publishers need control and transparency, not guesswork. This partnership gives media organizations the ability to manage AI access on their terms and participate in emerging AI licensing models.”

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From Detection to Commercial Participation.

Most bot-management tools focus solely on blocking traffic. The Arc XP–TollBit integration connects real-time detection with a structured commercial pathway.

Through native integration within Arc XP’s delivery infrastructure and TollBit’s marketplace, publishers can enable TollBit directly from the Arc XP dashboard. Once activated, publishers can then:

  • Monitor AI bot traffic with TollBit Analytics to better understand AI scraping patterns
  • Identify and classify AI bots in real time
  • Block access entirely, if desired
  • Set up an agent-optimized website
  • Redirect AI bots to the TollBit Bot Paywall on your agent site to enforce access rules and pricing

This will allow media organizations powered by Arc XP to automatically monitor AI bot traffic, set licensing terms, and collect payments from AI agents and LLM developers seeking to use their content for real-time retrieval. Participation in monetization programs is optional and configurable. Publishers gain more control over how automated agents interact with their content.

“The current friction between AI development and content creation isn’t just a technical hurdle; it is a fundamental challenge to how the internet operates,” said Toshit Panigrahi, CEO and co-founder of TollBit. “At TollBit, our goal has always been to create a structured, fair exchange for this new AI era. By joining forces with Arc XP, we’re making it effortless for publishers to set their own terms and monetize their content with ease.”

Arc XP provides the native edge-integration and policy-control layer, while TollBit manages the agent authentication, programmatic licensing, and monetization.

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Infrastructure for the AI Era.

AI licensing revenue models are still evolving. However, publishers cannot afford to remain passive participants in an ecosystem where automated agents access content at scale. This integration provides the technical foundation required to enforce access rules, gain visibility into AI activity, and monetize real-time AI retrieval of publisher content.

As AI reshapes how information is discovered and consumed, publishers need infrastructure that supports both protection and participation. The Arc XP–TollBit integration strengthens Arc XP’s broader AI-readiness strategy, reinforcing its differentiation across content protection, monetization, and audience ownership.

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Dataminr Redefines Cyber Defense with AI-Powered Client-Tailored Intelligence and Autonomous Threat and Exposure Management

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Dataminr Redefines Cyber Defense with AI-Powered Client-Tailored Intelligence and Autonomous Threat and Exposure Management

Dataminr for Cyber Defense, the first unified solution from the acquisition of ThreatConnect, fuses real-time intelligence with detailed internal posture to contextualize, prioritize, and automate the entire threat management lifecycle

Dataminr, the leader in AI-powered real-time event, threat & risk intelligence, launched Dataminr for Cyber Defense, a suite of preemptive threat and exposure solutions that assembles and operationalizes real-time, client-tailored intelligence from first signal to risk-prioritized action. Built with agentic and predictive AI at its core, these new solutions securely fuse Dataminr’s external foresight with an organization’s internal telemetry to contextualize threats with precise relevance and business impact. Realizing the strategic vision of the company’s acquisition of ThreatConnect, these unified, adaptive defense solutions drive decisive, automated responses prioritized by continuously quantified business and financial risk.

“No business—and no critical infrastructure—is immune from cyber threats. Real resilience means moving past reactive alerting to proactive, secure-by-design defense: understand the threat, prepare for it, and respond fast. But with defenders increasingly unable to match machine-speed attacks, we need agentic AI to close the gap. Using Dataminr to fuse external foresight with internal telemetry, organizations can finally cut through the noise and neutralize threats before they cause material impact,” said Jen Easterly, Chair of Dataminr’s Corporate Advisory Board.

Purpose-Built Solutions for Every Level of Security Maturity
Dataminr for Cyber Defense is delivered through three core solutions that seamlessly integrate into existing security tools—so customers can start where they are and expand as maturity increases.

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Available immediately:

  • Dataminr Client-Tailored Threat Intelligence: An AI-powered threat intelligence solution that automatically and in real-time filters noise and highlights the threats that truly matter to the organization by fusing external threat signals with internal telemetry. Dataminr bridges the gap between instant detection and actionable foresight, equipping users not only with real-time visibility but with the predictive intelligence necessary to navigate what may come next. It empowers security teams to accelerate operations without requiring manual research cycles, additional tools, or complex workflows.
  • Dataminr Agentic TI Ops: A unified system that redefines the threat intelligence platform by combining Dataminr Client-Tailored Threat Intelligence together with other  sources of commercial and internally generated intelligence. Dataminr ensures customers retain full choice and control over the intelligence fueling their defenses. The agentic platform rapidly orchestrates investigation, enrichment, prioritization, and distribution workflows without added analyst burden or process complexity.
  • Dataminr Predictive Threat Exposure Management: A Continuous Threat Exposure Management (CTEM) solution that combines cyber risk quantification with security control assessment and vulnerability prioritization, enabling security leaders to prioritize and report actions based on measurable business impact rather than alert volume or CVSS scores alone. It provides immediate, clear context on what to do next based on priorities and real-time security posture. When combined with Dataminr Client-Tailored Threat Intelligence or Agentic TI Ops solutions, Dataminr Predictive Threat Exposure Management empowers analysts to leverage the same insights in real-time to support investigations and drive operational decisions.

Learn more about Dataminr for Cyber Defense and these solutions on Dataminr.com.

“We acquired ThreatConnect with a clear vision: to unite our unrivaled breadth and depth of external threat signals with internal telemetry and provide organizations with clarity on what threats are impacting their business so they can act with speed and precision,” said Ted Bailey, CEO and Founder of Dataminr. “The old model of static feeds is obsolete. If you aren’t linking the real-time threat directly to your specific posture and real-time financial impact, you are operating blindly. Dataminr for Cyber Defense empowers teams to stop reacting to noise and take the immediate defensive action necessary to drive superior security outcomes.”

Dataminr for Cyber Defense is built to operationalize the modern cyber defense requirements identified in Gartner® research across two critical categories: Unified Cyber Risk Intelligence (UCRI) by fusing real-time external threats, internal exposure, and business risk into a shared decision model; and Continuous Threat Exposure Management (CTEM), by continuously identifying, validating, and prioritizing exposure based on live telemetry and evolving threats. Dataminr for Cyber Defense is the first suite of solutions to operationalize UCRI and CTEM, modernizing legacy SOC models from alerts and incidents to continuous, preemptive, and prioritized risk control.

“Looking ahead, the future of threat intelligence is Unified Cyber Risk Intelligence (UCRI) and will be defined by the convergence of multisignal collection and advanced analytical capabilities. This multisignal approach, combined with the evolution of AI techniques such as machine learning and natural language processing, will enable faster, more accurate detection of emerging threats and subtle attack patterns.” (Gartner, The Evolution of Threat Intelligence is Unified Cyber Risk Intelligence, 15 September 2025.)

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Agentic and Predictive AI at the Core of Dataminr for Cyber Defense
Unlike security products that have bolted-on AI and merely summarize alert data after the fact, Dataminr stands apart as an AI pioneer. With 55+ proprietary LLMs and a 12+ year event archive, Dataminr’s end-to-end AI architecture leverages Multi-Modal Fusion AI for discovery, ReGenAI for Live Event Briefs and real-time updates, and agentic AI-powered Intel Agents for ongoing context. By continuously ingesting from more than one million public data sources, this system delivers the speed and scale to detect and respond to events, threats, and risks as they unfold. Predictive intelligence and client-tailored guidance combine historical progression of similar threats with internal and external exposure to provide likely developments, enabling users to move rapidly from signal to action with the highest level of confidence.

In customer deployments, the impact of Dataminr’s agentic AI is immediate and measurable. Dataminr’s automation maximizes the value of the entire security stack, with 97% of customers reporting improved effectiveness in operational tools like SIEMs, SOARs, and EDRs. Furthermore, by reducing investigation cycles from hours to minutes, 67% of users report cutting their Mean Time to Respond (MTTR) by more than half, enabling teams to neutralize threats before they cause financial or operational impact. With the total expected financial loss increasing by $2,209,1001 for every 10 days a data breach goes undetected, this speed is critical for enabling teams to neutralize threats before they cause severe operational or business impact.

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Algolia Unlocks Smarter Search and Faster Growth for Shopify Merchants

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Algolia Unlocks Smarter Search and Faster Growth for Shopify Merchants

Algolia Logo

Algolia, the AI Search and Retrieval platform orchestrating more than 1.75 trillion queries each year, trusted by over 18,000 businesses and used by millions of developers worldwide, announced significant enhancements to its Shopify integration. The updates further strengthen Algolia’s position within the Shopify ecosystem and deliver faster performance, deeper merchandising control, and stronger scalability for growing brands.

The release introduces Commerce Pipeline, a new indexing foundation that dramatically improves speed and reliability, as well as enhanced analytics, campaign-driven merchandising, structured category support, and richer content discovery. Native Horizon theme and Native Virtual Replica Support will follow this summer.

Nate Barad, Vice President of Product and Technical Marketing, Algolia, said: “Together, these innovations give Shopify merchants a faster, smarter search experience that directly supports revenue growth. We are aligning tightly with Shopify’s evolution while giving merchandisers more control, better data, and enterprise-grade performance.”

Commerce Pipeline: Built for Scale
At the core of the expansion is Commerce Pipeline, a next-generation indexing architecture replacing Algolia’s previous system, and a foundational upgrade for Shopify and its merchants. Search now keeps pace with merchandising, international expansion, and peak demand without costly workarounds.

For large catalogs, full reindex times have dropped by upwards of 80 percent, from over 45 minutes to under 10 minutes. Throughput has increased by more than 50 percent, and for Shopify Markets merchants, product updates now reflect in an average of two minutes. Metafield-heavy stores can now complete full reindexes reliably, and the previous 10-market limit has been removed.

One-Click Pixel Activation: Smarter Data, Better Relevancy
Algolia’s new Click-to-Activate Pixel Analytics captures shopper behavior, including clicks, add-to-carts, and purchases, in a single step.

For merchandisers, this means clearer insight into product performance and stronger data to guide ranking, promotions, and campaign decisions. Behavioral signals automatically improve relevancy, making advanced features available immediately without additional tracking projects.

Barad added, “When shopper data flows seamlessly into search, results improve from day one, Merchandisers can optimize faster and drive stronger performance.”

Enhanced Autocomplete, InstantSearch, & Analytics for Shopify App Blocks
Algolia expanded customization within Shopify App Blocks, giving merchants greater control over how search behaves without requiring a storefront rebuild. Merchants can now pass advanced parameters, including analytics tags, directly into search configurations, enabling more precise tracking and smarter optimization.

This gives merchandisers clearer direction over what search prioritizes and measures. They can align search with campaign goals, track what matters most, and launch faster without complex technical projects. It’s less operational overhead and more measurable impact on what shoppers see and buy.

Dynamic Contexts for Collection Page Merchandising
Algolia enables merchants to apply dynamic rule contexts directly to collection pages, unlocking true page-level merchandising control. Rule contexts act as smart triggers that activate specific merchandising rules, such as pinning products, boosting categories, hiding items, applying filters, or displaying banners, based on the situation.

Barad added: “This means the same collection page can deliver different experiences depending on how a shopper arrives or what campaign is running. For example, a Women’s Shoes collection can prioritize clearance items for email traffic, boost new arrivals for homepage visitors, or highlight a featured brand during a seasonal promotion, all without changing the underlying collection. Merchants gain campaign-specific control over product ordering and presentation, supporting paid media, organic traffic, and promotional pushes with precision.”

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This enhancement gives merchants a stable, supported way to tailor collection pages dynamically while keeping their merchandising strategy agile and aligned to business goals.

Metaobject Support for Richer Content in Search
Algolia now indexes Shopify Metaobjects, allowing buying guides, fit details, ingredients, brand stories, and promotional content to appear directly within search and category experiences.

Barad noted: “Content no longer sits on the sidelines, instead it becomes part of the merchandising engine, helping shoppers discover not just products, but the context that drives confidence and conversion.”

Hierarchical Category Support for Merchandising Studio and Query Categorization
Algolia’s Shopify connector now indexes Shopify’s Standard Product Taxonomy, bringing full parent-child category hierarchies directly into search and merchandising workflows. Instead of relying on flat collection data, merchants can now leverage structured category paths such as Apparel & Accessories > Clothing > Activewear > Tops, enabling deeper and more precise merchandising control.

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This enhancement allows Merchandising Studio and Query Categorization to operate with full category depth, unlocking multilevel facets and AI-driven optimizations that depend on hierarchical structure. Because it uses the category data merchants already maintain within Shopify, no additional data entry or complex mappings are required. The result is more intuitive category-based merchandising, cleaner navigation, and smarter query understanding without added operational overhead.

As Shopify evolves, Algolia continues to align closely with its platform roadmap. Native support for Horizon themes, which power new storefronts, will roll out this summer, ensuring seamless compatibility with Shopify’s newest storefront framework.

Also coming this summer, Algolia will support Virtual Replicas natively within Shopify admin, eliminating index duplication and removing a major scaling blocker for enterprise brands. Merchants will be able to configure sorting without engineering workarounds or storage concerns.

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

CreatorIQ Appoints Senthil Kumaran as Chief Technology Officer to Accelerate AI-Driven Innovation in Creator Marketing

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CreatorIQ Appoints Senthil Kumaran as Chief Technology Officer to Accelerate AI-Driven Innovation in Creator Marketing

Veteran technology leader to scale CreatorIQ’s global engineering organization and expand the AI and data infrastructure behind the enterprise creator marketing operating system

CreatorIQ, the operating system for creator-led growth, announced the appointment of Senthil Kumaran as Chief Technology Officer. Kumaran brings more than two decades experience scaling global engineering organizations, integrating complex platforms, and building predictive machine learning systems on first-party data. He will lead CreatorIQ’s global technology organization as the company accelerates its AI-driven roadmap and deepens its data advantage for brands and agencies worldwide.

Kumaran joins CreatorIQ from his role as CTO of Digital Turbine (NASDAQ: APPS), where he led large-scale engineering teams and advanced cloud-native, data-driven platforms. He previously held engineering leadership roles at Meta Reality Labs, Verifone, Yahoo!, and Xperi Inc. Over the course of his career, he has overseen global teams of more than 1,000 engineers, built predictive machine learning systems leveraging first-party data, led development of major AWS environments at scale, and integrated technology stacks, enterprise systems and products across multiple companies post-acquisition.

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His appointment comes at a pivotal moment for the creator economy. As AI-native applications reshape business and marketing, brands are demanding greater speed, deeper insights, and measurable impact from creator investments. CreatorIQ is positioned to meet this shift by further operationalizing its proprietary Creator Graph™ intelligence infrastructure and expanding AI-assisted capabilities across the platform.

“AI is transforming marketing from campaign management into intelligent systems that orchestrate entire ecosystems in real time,” said Chris Harrington, CEO of CreatorIQ. “Nowhere is that shift more visible than in the creator economy, where brands are managing thousands of creator relationships across global markets. CreatorIQ is building the AI-native platform to power that future—turning creator partnerships into always-on growth engines for the world’s leading brands. Senthil brings the technical vision and leadership to accelerate this transformation and help define the next generation of creator marketing.”

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Under Kumaran’s leadership, CreatorIQ will focus on advancing AI-powered execution layers, accelerating product velocity, strengthening data infrastructure, and expanding integrations that reduce time to value for customers. By reducing operational complexity through intelligent systems, CreatorIQ aims to give marketers time back to invest in the inherently human aspects of creator marketing that give it the edge over traditional media.

“CreatorIQ has built an extraordinary foundation — industry-leading data, the powerful Creator Graph, and a global ecosystem of customers and partners,” said Senthil Kumaran, Chief Technology Officer of CreatorIQ. “As marketing shifts toward data- and AI-driven execution, the opportunity is to transform that foundation into intelligent systems that help brands and creators operate faster and more effectively. I’m excited to build on CreatorIQ’s data advantage to unlock new capabilities, deepen integrations across the marketing ecosystem, and accelerate how brands launch, optimize, and monetize creator programs.”

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

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