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Bloomreach Deepens Partnership With Databricks, Extending AI Personalization Across Email, Web, and More Through New CustomerLake Integration

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Bloomreach Deepens Partnership With Databricks, Extending AI Personalization Across Email, Web, and More Through New CustomerLake Integration

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Bloomreach, the AI company for personalization, announced it is a launch partner for Databricks CustomerLake, a new agentic Customer Data Platform (CDP). The announcement reflects Bloomreach’s broader investment in the Databricks platform, which extends to new insight capabilities being built into its Loomi marketing agent. Together, the companies are making scaled 1:1 personalization possible for every marketer, offering a direct path from unified customer data to real-time, personalized execution across the channels that matter most.

“From web to email to AI conversations, marketers need the ability to personalize customer engagement where the stakes are highest,” said Anirban Bardalaye.

“From web to email to AI conversations, marketers need the ability to personalize customer engagement where the stakes are highest,” said Anirban Bardalaye, Chief Product Officer, Bloomreach. “CustomerLake gives our agentic platform, Loomi, the governed enterprise data foundation it needs to personalize every channel, without any tradeoffs between data quality and speed. Add the real-time behavioral signals Loomi builds into every interaction, and personalization compounds — each engagement more relevant than the last.”

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

Most enterprise marketing teams sit downstream from their own data. Customer profiles live in one system, campaign execution happens in another, and the gap between them costs time and accuracy. CustomerLake closes that gap by bringing CDP capabilities directly into Databricks, where customer context, AI models, and governance already live — without duplicating sensitive data or creating new silos. Loomi extends it to execution, so a unified customer record built in CustomerLake can immediately power a personalized campaign activated by Loomi across email, web, SMS, and more.

Marketing Technology News: Idle data is as good as no data

Campaigns are further optimized by Loomi’s commerce-specific artificial intelligence, trained on more than 12 years of interaction data from the world’s largest ecommerce brands. The integration with CustomerLake connects this commerce expertise directly to the governed data and AI foundation where enterprises already manage their customer intelligence.

“Our customers are asking for simple and scalable ways to combine and activate otherwise siloed customer data into personalized, intelligent experiences alongside the myriad of tools they already use,” said Stephen Orban, SVP Product Partnerships and Ecosystem at Databricks. “Databricks has always been built on openness and customer choice, and partners have a significant opportunity to integrate directly with CustomerLake to meet customers where their data and agents already live and deliver the next generation of marketing solutions on a unified foundation.”

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Siemens partners with Databricks and FFT to turn production data into scalable AI-driven insights

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Siemens partners with Databricks and FFT to turn production data into scalable AI-driven insights

Corporate information | Siemens

  • Siemens Industrial Edge and FFT DataBridge connect shopfloor and plant data directly to the Databricks Platform – no IoT middleware required

  • New edge to cloud connectivity offers scalable advanced analytics and a unified, AI‑ready production data foundation

  • Industrial customers can optimize their operations, reduce costs and increase productivity

Siemens announced a new edge-to-cloud integration with Databricks, the Data and AI company, and long‑time automation partner FFT Produktionssysteme GmbH (FFT). Together, the partners will connect production data directly to enterprise AI – without complex IoT middleware. This will help industrial customers transform their production data into actionable insights and scale industrial AI across global operations.

With the new integration, customers are able to stream contextualized shopfloor and plant data from Siemens Industrial Edge via the FFT DataBridge directly to the Databricks Platform, where it can be analyzed and used to train AI models centrally for implementation across global production networks. These models can then be deployed back to the edge for execution at the point of production. This approach helps industrial companies optimize their operations, reduce costs and increase productivity with low‑latency, data‑driven decision‑making. It lays the foundation for physical AI and future autonomous operations.

Siemens Industrial Edge enables customers to deploy and manage edge devices and apps on the production site. The app ecosystem allows seamless connectivity to industrial assets, IT systems and the cloud.

“Industrial AI only delivers value when data, context and execution come together,” said Rainer Brehm, COO Automation and CTO at Siemens Digital Industries. “With Databricks and FFT, we enable our customers to scale industrial AI across factories and plants and make AI-powered production real.”

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Operationalizing Industrial AI with seamless IT/OT integration

With Siemens Industrial Edge and Industrial Information Hub (integration layer for industrial data), customers benefit from a secure, scalable and low-maintenance edge platform designed to unlock siloed industrial data and execute intelligent applications close to the production process. This includes advanced local analytics, physical AI and closed loop AI workflows that require low latency, high availability and strict security compliance.

Databricks complements this with advanced analytics, machine learning and agentic AI for industrial data in a cloud agnostic, governed environment with minimal infrastructure overhead. This supports a wide range of advanced use cases, including predictive maintenance, quality optimization, energy management, supply chain optimization and agentic AI applications.

“By uniting Siemens’ industrial automation and edge expertise with the Databricks Platform, we help industrial companies close the gap between industrial data and scalable business impact across their industrial network,” said Shiv Trisal, Global Industrials GTM Leader at Databricks. “This partnership is a foundational step in making human-agent collaboration a reality for industrial operations.”

Siemens Industrial Edge enables customers to deploy and manage edge devices and apps on the production site. The app ecosystem allows seamless connectivity to industrial assets, IT systems and the cloud.

Marketing Technology News: Is the Traditional CDP Already Out of Date?

FFT DataBridge: Industrialgrade data pipelines for adaptive production

FFT Produktionssysteme GmbH plays a key role in operationalizing the joint Siemens–Databricks architecture. As a long-standing Siemens partner with deep shopfloor expertise, FFT provides the DataBridge application that securely and efficiently connects Siemens Industrial Edge with the Databricks platform. FFT DataBridge streams contextualized, AI-ready production data from the edge to the cloud, where it can be combined with additional IT and OT data sources.

“Together with our partners Databricks and Siemens, FFT DataBridge provides a simple, powerful gateway to the cloud for more than 30,000 potential customers,” said Volker Stark, COO at FFT Produktionssysteme. It is ready to use and does not require expensive and time-intensive transformation of data. By natively bridging the gap between IT and OT, we eliminate the need for complex IoT layers and significantly simplify industrial connectivity for customers of Databricks.”

With the combined offering from Siemens, Databricks, and FFT, industrial producers can unlock AI‑ready production data, scale Industrial AI, and optimize operations across global production sites

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Framer Launches AI Agents

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Ecer.com Reshaping the New Mobile Cross-Border B2B Ecosystem

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Create, update, and maintain production websites with AI, directly inside Framer.

Adeptia Strengthens Leadership Team to Meet Growing Demand for AI-Ready Data and Intelligent ETL

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Adeptia Strengthens Leadership Team to Meet Growing Demand for AI-Ready Data and Intelligent ETL

About Us - Data Integration Company | Adeptia Inc.

New executive leaders join as enterprises accelerate investments in AI-ready data infrastructure

Adeptia, the intelligent ETL platform for enterprise data automation, announced the appointment of three senior executives to support the company’s next phase of growth and innovation: Tim Bond, Chief Product Officer; Jill Ransome, Vice President of Marketing; and John Moore, Vice President of Revenue Operations. The leadership additions reflect Adeptia’s continued investment in helping enterprises modernize how they integrate, govern, and operationalize data in an AI-driven world.

Organizations in highly regulated industries are seeking modern alternatives to traditional integration and ETL approaches to support automation, AI, and digital transformation. The company’s Intelligent ETL platform creates a trusted foundation for AI initiatives by connecting data across systems, automating workflows, and improving visibility into business operations.

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Adeptia Automate enables organizations to transform complex, raw data into operational intelligence. Unlike traditional ETL, which was designed for predictable data flowing between known systems, Adeptia Intelligent ETL helps organizations manage today’s increasingly complex business data. The platform uses AI to design and optimize pipelines while applying industry-specific business rules to deliver trusted, consistent outcomes.

“As enterprises race to deploy AI, they’re discovering that success relies heavily on having trusted, accessible, and actionable data,” said Charles Nardi, CEO of Adeptia. “Our leadership will be instrumental as we continue helping organizations transform fragmented data into trusted, AI-ready information that powers automation, operational intelligence, and business growth.”

Ransome will lead global marketing strategy and execution, expanding Adeptia’s market presence and driving awareness of the company’s Intelligent ETL approach to enterprise data automation; Bond will oversee product strategy and innovation, advancing the company’s AI-native platform as the foundation organizations rely on to build, orchestrate and scale their data workflows; and Moore will lead revenue operations initiatives focused on scaling go-to-market performance, improving operational efficiency, and supporting customer growth.

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Prior to joining Adeptia, Ransome held senior marketing leadership roles across enterprise software and technology organizations, driving brand growth, demand generation, and market expansion at SaaS companies, including Jitterbit, Tangoe, and Unite Us. Bond was a senior product advisor at various software companies, including Nymbl, Jitterbit, and Zudy, bringing more than a decade of experience leading product strategy and development across data, integration, and enterprise software. Moore has extensive expertise in building scalable revenue operations functions that align sales, marketing, and customer success teams across various industries, at Intapp, Meltwater, and Nolan Transportation Group.

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Planview Closes the Gap Between Strategic Intent and Business Outcomes in the Age of AI

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Planview Closes the Gap Between Strategic Intent and Business Outcomes in the Age of AI

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Company unveils three fundamental shifts that define strategic portfolio management in the agentic era

Planview®, the leading platform that equips organizations to act decisively and close the gap between strategic intent and outcomes, introduces new capabilities for the future of AI-powered SPM. This includes the debut of the Outcome Intelligence Graph, a model of the enterprise portfolio in which every decision connects to the resources behind it and the results it produces. The Outcome Intelligence Graph addresses three imperatives that Planview sees as non-negotiable for the agentic era: every decision must drive outcomes; actions must keep pace with change; and governance must be built for speed — human and agent alike. The company has published a full vision statement on the shifts required for agentic-era strategic portfolio management from CEO Matt Zilli on its blog.

“AI does not close the gap between intent and outcome. It widens it. A misaligned decision now compounds at machine speed, at scale, before anyone sees a signal,” said Matt Zilli, Planview CEO. “This is also the moment AI can finally do what was impossible at human speed: connect strategy to execution in real time, reconcile investments to outcomes continuously, and give every leader, team, and agent the same view.”

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Introducing the Outcome Intelligence Graph

With the Outcome Intelligence Graph, leaders and AI agents reason from the same picture. The relationships inside the graph carry three decades of practitioner knowledge about how portfolios behave, finally making the hardest question answerable: did the initiative we funded deliver what we expected?

“General-purpose AI models are remarkable, but they don’t know what a $40 million program delay costs your company. Tracking workflows at the team level isn’t enough — leaders need to be able to understand the whole picture. Anvi®, powered by the Outcome Intelligence Graph, is built on 30 years of how enterprise portfolios actually behave — that’s not something you can replicate with a connector or a prompt,” said Louise K. Allen, Planview Chief Product Officer. “It’s the difference between AI that can answer questions and AI that understands the full strategic context around the work.”

Marketing Technology News: Idle data is as good as no data

New Anvi-Powered Capabilities

Planview is also announcing new capabilities that put the Outcome Intelligence Graph to work across planning, collaboration, and the broader AI ecosystem:

  • Anvi-powered Scenario Planning addresses the need for enterprise-wide intelligence, turning days of manual spreadsheet modeling into minutes. Describe your objectives and automatically get back ranked scenarios with full tradeoff analysis across capacity, financials, and strategic fit, so leaders can understand decision tradeoffs and see what the organization can actually achieve.
  • Anvi MCP server puts the Outcome Intelligence Graph wherever your team gets work done, allowing Copilot, Claude, ChatGPT, or any enterprise agent to call Anvi directly — bringing the context of your business and Planview’s decades of practitioner knowledge into whichever AI environment your teams already use.
  • Originally launched at Planview Connect 2026, Agent Resource Management is the real-time governance plane for the agentic era, placing people and AI agents in one system to plan, govern, and optimize together — with full cost visibility on every capacity decision, automatic guardrails on agent activity, and continuous proof of which outcomes your AI investments deliver.

Together with the new Anvi Home experience — where teams build, test, and deploy agents with a curated prompt library and admin controls for distributing them across the organization — these capabilities turn the Outcome Intelligence Graph from a model into action.

“The enterprises asking, ‘how do we adopt AI faster?’ are asking the right question in the wrong order. The first question is: ‘how do we know whether our AI investments are producing the outcomes we funded them to produce?’” said Zilli. “For most organizations, no one can answer it — this is the gap strategic portfolio management was built to close.”

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Sigma Named 2026 Databricks ISV Business Intelligence Partner of the Year and Joins as Launch Partner for Lakehouse//RT, Databricks’ New Real-Time Lakehouse

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Sigma Named 2026 Databricks ISV Business Intelligence Partner of the Year and Joins as Launch Partner for Lakehouse//RT, Databricks' New Real-Time Lakehouse

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For the second consecutive year, Sigma is recognized for deepening its partnership and platform on Databricks — now spanning Lakehouse//RT, Genie Agents, Agent Bricks, and Lakebase

Databricks Data + AI Summit — Sigma, the layer to build and scale analytics, apps and agents, announced that it has been named the 2026 Databricks ISV Business Intelligence Partner of the Year at the annual Data + AI Summit, and joined as a launch partner for Lakehouse//RT, Databricks’ new real-time lakehouse. The partner award, presented for the second consecutive year, recognizes Sigma’s contributions to helping enterprise teams build and deploy AI Apps, agents, and analytics on governed enterprise data with Unity Catalog-grade security, governance, and scale—from inherited permissions to immutable audit—all on the Databricks platform.

“The hardest part of enterprise AI isn’t building the model. It’s making agents work on real business data, under real permissions, at scale. That’s exactly what Sigma and Databricks solve together.” – Mike Palmer, CEO of Sigma

The recognition comes on the heels of Sigma’s recently closed $80 million Series E, which included a strategic investment from Databricks Ventures and doubled the company’s valuation to $3 billion. Together, Sigma and Databricks have deepened their warehouse-native architecture to give business and technical teams a single governed workspace for AI Apps, analytics and automated workflows, without extracting data or duplicating governance.

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“We’re honored to receive this recognition from Databricks for the second year in a row,” said Mike Palmer, CEO of Sigma. “Sigma now connects directly to Lakehouse//RT, Agent Bricks, Genie Agents and Lakebase, so joint customers can get sub-second query performance at scale, explore billions of rows through a familiar spreadsheet interface, build agents that act on that data and manage the full agent workflow — memory, state and all — without ever leaving the governed environment they already trust. The hardest part of enterprise AI isn’t building the model. It’s making agents work on real business data, under real permissions, at scale. That’s exactly what Sigma and Databricks solve together.”

“As the race to productionize AI accelerates, customers consistently ask us how they can better manage their data in order to build AI apps and agents that make a real impact on their business,” said Stephen Orban, SVP, Product Ecosystem & Partnerships at Databricks. “As a key Databricks partner, Sigma helps our joint customers do exactly that. We’re proud to recognize them as the 2026 Databricks ISV Business Intelligence Partner of the Year.”

Marketing Technology News: Idle data is as good as no data

New Capabilities for Joint Sigma and Databricks Customers:

Alongside the award, Sigma announced an expansion of its strategic partnership spanning the full Databricks platform. New capabilities include:

  • Sigma joins as a launch partner for Lakehouse//RT, Databricks’ new real-time lakehouseLakehouse//RT delivers millisecond query latency at massive concurrency on existing Delta tables, with no data movement and full Unity Catalog governance, unlocking a new class of real-time use cases for joint customers. Where high-concurrency, low-latency workloads previously required standing up external serving layers and duplicating data, Lakehouse//RT handles user-facing analytics, operational dashboards, product analytics, and AI agent-serving natively on Databricks.
  • Deeper integration with Databricks Genie and Agent Bricks. Sigma acts as the AI runtime layer that turns Databricks intelligence into governed AI Apps for every user. With Genie, business teams ask questions in natural language and build no-code agents that feed directly into Sigma AI Apps where insights become workflows without a handoff to engineering. With Agent Bricks, teams build and deploy custom AI agents grounded in enterprise data and surface them inside Sigma. From there, any user can interact with the agents, trigger automated actions and drive outcomes in a fully governed workspace. Data teams define the logic and access controls once, and everyone else operates within them with full lineage and auditability throughout.
  • First-party connectivity to Databricks Lakebase, Databricks’ serverless Postgres database built for AI agents. Customers can now query transactional data alongside their analytical datasets in Databricks and build dashboards that reflect live operational activity, including order status updates, inventory shifts, system health, and more, without moving data between systems or maintaining a separate pipeline for operational reporting. Sigma’s spreadsheet-native interface handles both in one governed workspace.
  • Support for Unity Catalog Semantics, Databricks’ semantic layer for defining and governing reusable business metrics across the platform. Metric definitions managed in Unity Catalog now surface natively inside Sigma workbooks, so data teams can define business logic and provide consistent enterprise context for analytics, AI applications and agents once – every report, dashboard, and AI Apps output draws from the same source. This is designed to eliminate the metric drift that happens when governance lives in the warehouse, but BI adds its own semantic layer on top.

Sigma is an Icon Partner for the Databricks Data + AI Summit 2026, June 15–18 in San Francisco, and will be exhibiting at Booth #106 for daily theater sessions featuring live product demos and hands-on training. Sigma will also host several featured sessions at the event, including customers such as the Hospital for Special Surgery, Unilever, Dotmatics, and DraftKings.

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Graviti Power Accelerates Texas Market Entry with VertexOne’s Cloud-Based CIS & EDI Solutions

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Graviti Power Accelerates Texas Market Entry with VertexOne's Cloud-Based CIS & EDI Solutions

VertexOne, a leading provider of cloud software designed to revolutionize the customer experience within the energy and utility industry, announced that newly formed Texas-based energy services company, Graviti Power, LLC., has chosen VertexOne’s leading billing and customer information system (CIS), VXretail, and electronic data interchange (EDI) solution, VXexchange, to better serve their large-scale commercial customers in the ERCOT market.

“VertexOne gives us the operational backbone to scale quickly, automate complex processes, and deliver a high-quality customer experience from day one.” Vidya Sagar, CEO of Graviti Power

The Option2 Retail Energy Provider, which sells electricity to a slate of large, non-residential customers, including hotels, gas stations, retail malls, and industrial warehouses, says they chose VertexOne specifically for their extensive industry expertise and proven track record of success operating in the highly competitive Texas retail energy market.

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“Operating in the Texas market requires precision, speed, and adaptable technology that’s purpose-built for competitive retail energy,” said Vidya Sagar, CEO of Graviti Power. “VertexOne gives us the operational backbone to scale quickly, automate complex processes, and deliver a high-quality customer experience from day one. Their experience in ERCOT and commitment to customer success made them the clear partner for our market entry.”

VertexOne’s unified platform connects enrollment, usage, ratings, billing, invoicing, and market transactions in a single operating environment, enabling REPs like Graviti Power to hit the ground running with Texas-specific billing logic already built in.

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“Our industry-leading technology stack is purpose-built to support competitive energy suppliers with automation, scalability, and compliance at its core,” Ananda Goswami, VertexOne Senior Vice President of Sales Strategy, said. “By providing a unified operational environment and superior implementation support, we’re proud to enable new entrants like Graviti Power to operate efficiently while maintaining the flexibility to evolve with market demands.”

By entering into the ERCOT retail energy market, Sagar said Graviti Power is positioned to connect their customers through a cohesive energy ecosystem while supporting the growing demand for electrification and commercial energy innovation.

“As we expand our broader energy ecosystem, having an integrated billing and market operations platform is essential,” Sagar said. “And VertexOne enables us to connect technology, infrastructure, and customer experience in a way that supports both innovation and reliability.”

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DQLabs Named a Representative Vendor in the 2026 Gartner® Market Guide for Data Observability Tools

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DQLabs Named a Representative Vendor in the 2026 Gartner® Market Guide for Data Observability Tools

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DQLabs has been recognized in the Gartner Market Guide as one of 20 vendors. We are listed in all the 5 use cases mentioned in the report.

DQLabs the provider of PRIZM, which is an Enterprise Platform for Data Observability, Data Quality and Context, announced it has been named a Representative Vendor in the Gartner Market Guide for Data Observability Tools (February 2026). We believe the recognition is based on the capabilities of the PRIZM platform by DQLabs.

In the Market Guide, Gartner states that data observability capabilities have gone from being a nice-to-have feature into a tactical necessity. According to Gartner’s 2025 State of AI-ready Data Survey, 53% of D&A or AI leaders said their organizations have already implemented data observability tools. In addition, 31% of respondents claimed they consider implementing the tools within 6-12 months, and 12% within 12-18 months, underscoring near-term momentum. Also, based on Gartner market share analysis, the overall revenue growth in the data observability market is 20.8% in 2024 and comes to $346.4 million. From these data points, Gartner sees strong growth for data observability adoption in the next few years due to the demand for AI-ready data. Gartner identifies the defining market trend as a move toward unified platforms. In the report, Gartner notes: “The market trend is moving toward unified platforms that combine various observabilities, data governance, and security into a single pane of glass. This integration will simplify operations, reduce costs associated with tool sprawl, and improve overall system reliability.”

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“We believe this recognition reflects our vision: that data teams should not have to stitch observability, data quality, and context together from separate point tools,” said Raj Joseph, CEO at DQLabs. “PRIZM was built to unify them on one AI-native control plane, so teams can move from detecting an issue to understanding its root cause and resolving it without switching tools with full context and complete automation. We believe being recognized by Gartner and being mentioned in all five observation categories, including cost allocation, validates that direction for us.”

Marketing Technology News: Idle data is as good as no data

How we believe PRIZM by DQLabs goes beyond basic data observability:

  • PRIZM by DQLabs mentioned in the all five observation categories Gartner defines: data content, data pipelines, data infrastructure, data lineage and cost allocation.
  • PRIZM by DQLabs clusters the alerts instead of creating noise. PRIZM groups thousands of related alerts into a handful of root causes using context, so teams fix few high priority problems to solve thousands of alerts.
  • PRIZM by DQLabs observes what matters most. PRIZM scores each asset, attributes, alerts by criticality and puts the deepest monitoring there, rather than treating every table the same and flooding teams with low-value alerts.
  • PRIZM by DQLabs observes cost and usage, not just data health. PRIZM tracks query and resource consumption and ties data issues to spend.

Several customers deploying PRIZM by DQLabs report consolidating three or more separate tools into a single platform, recognizing value within the first three months, and completing root cause analysis in minutes rather than days. Because PRIZM clusters alerts to their root cause and automates checks that teams used to build by hand, customers report substantial savings, with fewer people tied up triaging alerts and data engineers freed to build pipelines and data products instead of firefighting.

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Elastic Named a Strong Performer in Extended Detection And Response Platforms, Q2 2026

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Elastic Named a Strong Performer in Extended Detection And Response Platforms, Q2 2026

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Report recognizes Elastic’s strong SIEM-replacement features, open data architecture, AI innovation, and endpoint protection

Elastic, the Search AI Company, announced that it has been named a Strong Performer in The Forrester Wave™: Extended Detection And Response Platforms, Q2 2026. The report recognized Elastic Security’s SIEM-replacement capabilities, open data architecture, AI innovation, and endpoint protection. Access the complimentary report here.

Elastic Security is an agentic security operations platform that unifies SIEM, XDR, and native automation. Elastic’s native endpoint protection offers tangible efficacy against real-world attack scenarios. Elastic Security is the only vendor to achieve 14 consecutive months of 100% rates in AV-Comparatives’ Malware and Real-World Protection Tests. The Forrester Wave assessment notes that Elastic’s strategy envisions an open, agentic SOC that will automate operations.

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Elastic’s vendor profile in the report states the following:

  • Elastic’s SIEM-replacement features are strong, as it ingests a wide range of telemetry at scale, including from its endpoint agent, enabling security teams to correlate across cloud, endpoint, identity, application, and network data without siloed tools. Its open data formats and core engines, strong training content, and flexible data management make it heavily customizable.
  • Flexibility is a differentiator: Elastic is a good fit for organizations looking for– and that have the resources to support– a tool built for maximum flexibility across data ingestion, analytics, and AI. Security teams can ingest telemetry from virtually any source, tailor detections to their unique environment and risk profile, and build workflows aligned with existing processes rather than adapting to rigid platform constraints. Detection engineers can move faster, reduce vendor lock-in, and create security operations experiences that fit their organization.
  • Open, agentic SOC automates operations: Elastic demonstrates a strong commitment to innovation, with a focus on AI features, such as Attack Discovery and Automatic Migration. Attack Discovery correlates related alerts into higher-confidence attack narratives so analysts focus on real incidents rather than undifferentiated alert queues, while Automatic Migration moves dashboards and detection rules from legacy SIEMs into Elastic without rewriting rules.

Marketing Technology News: Idle data is as good as no data

“We believe every security team deserves access to proven endpoint capability, regardless of budget or team size,” said Mike Nichols, general manager, Security, Elastic. “This Forrester recognition validates what our customers already know: the endpoint detection included in our agentic security platform works. No separate license. No add-on. Enterprise-grade protection, accessible to everyone.”

Elastic Security runs on the same Elasticsearch platform as observability and search workloads, so security teams can correlate across operational and security telemetry without moving data across tools. The Elastic Security MCP App enables alert triaging, threat hunting, and case management directly within the tools analysts already use, including Claude Desktop, Claude.ai, VS Code Copilot, and Cursor.

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Netomi Brings Agentic AI to Azure and Dynamics 365

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Netomi Brings Agentic AI to Azure and Dynamics 365

Netomi

Enterprise Agentic AI built for scene-based reasoning, governed execution, and operational autonomy at scale.

Netomi announced expanded availability of its governed Agentic AI platform, built on Microsoft Azure Kubernetes Service, providing a deeper integration with Microsoft Dynamics 365, and available through the Microsoft Marketplace.

This architecture allows enterprises to run customer operations proactively, where AI continuously evaluates system conditions and intervenes before issues materialize.

As AI becomes the operational layer of customer experience, enterprises face a new challenge: ensuring autonomous systems act with context, discipline, and policy alignment rather than simply executing tasks faster. Netomi’s Agentic AI for CX operates in production across Fortune 500 enterprises in travel, hospitality, insurance, banking, retail, media, and telecommunications. Its architecture allows AI agents to reason over dynamic customer scenes rather than follow predefined scripts, evaluating policies, enterprise systems, and real-time context before taking action.

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For Microsoft customers, Netomi operates as an Azure-native agentic runtime, allowing agentic AI to execute decisions directly within existing enterprise systems while maintaining hardened policy enforcement and operational control. Customer experience unfolds through changing operational scenes where policies, systems, and real-world conditions interact simultaneously. Netomi enables AI agents to understand each scene before acting.

Deploying Agentic AI at Microsoft Azure scale

Netomi on Azure provides a governed agentic runtime designed for high-stakes enterprise operations. By operating inside the enterprise security perimeter, Netomi allows organizations to introduce autonomous reasoning into customer operations while maintaining the sovereignty, data residency, and reliability required in highly regulated environments.

This architecture allows enterprises to run customer operations proactively, where AI continuously evaluates system conditions and intervenes before issues materialize.

Together, these capabilities allow enterprises to operate autonomous systems with full visibility, control, and policy enforcement at runtime.

Marketing Technology News: Idle data is as good as no data

  • Situational awareness at runtime – AI agents reason across enterprise systems, policies, customer signals, and operational context before executing actions, allowing organizations to anticipate intent and deliver autonomous resolution.
  • Embedded runtime governance – Every tool call, policy evaluation, and system action is validated at the moment of decision. Governance is enforced to prevent non-compliant actions, ensuring autonomous operations remain aligned with enterprise policies and regulatory constraints without the “black box” risk of unmonitored LLM execution.
  • Continuous telemetry and observability – Enterprises gain full visibility into how models interpret context, coordinate actions across systems, and apply policy logic, making autonomous operations inspectable, measurable, and continuously improvable.
  • Parallel orchestration of complex workflows – Multi-system operations execute concurrently rather than sequentially, allowing enterprises to coordinate high-complexity customer scenarios across multiple systems without introducing latency or operational risk.
  • Regional deployment and compliance alignment – Integration with Azure identity, security, and regional compliance frameworks ensures autonomous systems operate strictly within the client’s existing cloud standards.

Bringing Scene-Based Autonomy into Dynamics 365

Netomi integrates with Dynamics 365 to embed scene-aware reasoning across end-to-end customer journeys, spanning service, marketing engagement, and commerce transactions. By leveraging rich customer, operational, and transactional data within Dynamics 365, Netomi enables enterprises to make real-time, policy-aligned decisions within each interaction. In service, this means resolving complex issues proactively before escalation. In marketing, it enables timely, context-aware offers based on live customer state. In commerce, it supports dynamic actions such as upgrades, rebooking, or concessions based on inventory, pricing, and customer value. By building on Dynamics 365’s secure, enterprise-grade data foundation, Netomi enables organizations to deliver more precise, consistent, and controlled customer experiences across every touchpoint. Key capabilities include:

  • Scene-Based Customer Interactions – AI agents reason over live Dynamics 365 data and enterprise rules, allowing strategies to adapt dynamically as customer situations evolve.
  • Pre-emptive Agent Assist inside Dynamics 365 – Human agents receive anticipatory guidance rather than scripted suggestions. Netomi identifies emerging issues, surfaces next-best actions, and recommends policy-aligned interventions before escalation occurs.
  • Continuous Knowledge Alignment via SharePoint – Policy and knowledge updates flow directly into agent reasoning models, ensuring decisions remain aligned with current enterprise standards. Telemetry provides CX, compliance, and operations leaders visibility into how AI interprets policy and protects the brand in real time.

Together, these capabilities allow enterprises to deploy AI that understands the operational scene within which it is acting, surfaces its reasoning through telemetry, and adjusts decisions before minor issues escalate into customer harm.

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Acxiom Real ID Powers Identity for Databricks CustomerLake and AI-Ready Marketing

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Acxiom Real ID Powers Identity for Databricks CustomerLake and AI-Ready Marketing

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New native application and integration with Databricks enable identity resolution and enrichment without data movement for clients

Acxiom®, the connected data and technology foundation for the world’s leading brands, announced that Acxiom Real ID is now a native Built-On application in Databricks, the Data and AI company, and is available in the Databricks Marketplace. This integration transforms how enterprise marketers leverage their customer data, providing a foundational infrastructure for enterprise AI, powering omnichannel personalization, and maximizing value across unified martech and adtech ecosystems.

Powered by Acxiom’s global identity graph of more than 260 million addressable individuals in the U.S., the solution enables brands to unify, enrich, and activate customer data without the complexities and risks of moving or duplicating directly identifiable personal information (PII).

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With Acxiom Real ID as the resolved identity foundation for every analytics, audience, and activation workflow in Databricks, marketers can achieve a single, unified, and actionable view of customers to deliver better customer experiences while maintaining full control over data, access, and compliance.

Acxiom is also a launch partner for Databricks CustomerLake, the new Agentic CDP built natively on Databricks. Together, Acxiom Real ID and CustomerLake help enterprises build trusted Customer 360 profiles, resolve identity, enrich customer data, and activate audiences from the same governed environment where their customer data already lives.

Marketing Technology News: Idle data is as good as no data

With Acxiom’s Real ID available natively on Databricks, enterprise marketers can:

  • Acquire ideal customers with unmatched precision: Connect known and unknown signals for a clear view of high-quality audience segments, driving better leads and smarter, more efficient acquisition efforts.
  • Maximize customer lifetime value: Enrich first-party data with insights into preferences, behaviors, and household dynamics to deliver experiences that resonate, keeping customers engaged, preventing churn, and growing lifetime value.
  • Build an agentic marketing operation: CustomerLake, now integrated with Acxiom’s industry leading identity and customer data, enables marketers to design and integrate agentic workflows into their marketing operations and activation platforms.
  • Confidently measure and optimize every marketing dollar: Understand the true impact of marketing investments and precisely which campaigns are driving real business growth to optimize spend, collaborate more effectively with partners, and prove ROI with confidence.
  • Launch impactful campaigns with speed and confidence: Move from insight to activation faster with robust identity resolution, data governance, and privacy controls seamlessly integrated.

“Acxiom Real ID on Databricks powers the connected customer intelligence and data foundation that enterprises need to operationalize AI within and across their marketing systems,” said Keith Camoosa, Chief Product & Technology Innovation Officer at Acxiom. “To drive growth, modern marketers must navigate increasing data fragmentation and reduce unnecessary complexity across the martech and adtech ecosystems. By bringing Acxiom Real ID natively into Databricks, clients can unify customer intelligence, accelerate AI-driven insights, and activate more effectively across channels while maintaining governance, transparency, and control over their data assets and marketing investments.”

“Acxiom’s deep expertise in identity and data enrichment is a powerful addition to the Databricks platform,” said Tasso Argyros, VP, Engineering at Databricks. “This partnership empowers our joint customers to transform their data into a unified, intelligent asset. With Acxiom Real ID, brands can accelerate their journey to AI-driven marketing, ensuring their personalization efforts are both impactful and privacy-compliant, all within a single, governed environment.”

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eTrigue Insights Launches With 1:1 Context-Relevant Messaging Enabling Higher Conversion Rates for Partner Marketing

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Revefi Extends Its AI DBA to Autonomously Optimize Databricks Ecosystem

eTrigue

Company leapfrogs traditional personalization techniques by delivering contextually relevant 1:1 messages across hundreds of partners and thousands of prospects simultaneously. eTrigue Insights enables automated co-branded content delivery for digital marketing campaigns, generating higher conversion rates.

eTriguethe company behind the popular digital partner marketing platform of the same name, announced the launch of its new platform, eTrigue Insights.

“Meeting customers where they are on their buying journey with relevance is key.” – William Herr, Sr. Global Partner Marketing Manager at AWS.

The powerful eTrigue Insights Platform and Services offering is designed to enable enterprise companies and their channel partners to execute contextually relevant 1:1 content to prospects at scale. With seamless pass-through at the partner level, eTrigue Insights Messaging solves the co-branding and prospect engagement challenges that resource-constrained partners face, delivering the right message to each individual at precisely the right time. The program scales to tens of thousands of recipients across hundreds of partner campaigns simultaneously without performance degradation. The result heightens prospect engagement levels, leading to swifter connections with customers and enhanced pipeline activity.

eTrigue Insights Messaging leverages the intelligence of eTrigue Lead & Company Insights to identify and summarize a prospect’s background, experience level, industry, social media, news, and company websites, creating highly customized, context-specific content for each recipient. In line with all eTrigue Insights Lead Accelerator Partner Marketing Programs, partner branding and co-content are configured automatically to ensure each partner’s message reaches the contact on time and on message. The eTrigue Insights Lead Accelerator Partner Marketing Program, with Lead & Company Insights, Insights Messaging, and Sales Team Insights leverages both Amazon Nova Pro2 and Anthropic Claude Sonnet in parallel.

Marketing Technology News: MarTech Interview with Theresa Pham, Head of Product @ Wayvia

“Meeting customers where they are on their buying journey with relevance is key. This means contextual personalization beyond simply inserting a name or data field, rather creating a branded partner message informed by the recipient’s job, skill set, interests, focus area, and more,” says William Herr, Sr. Global Partner Marketing Manager for Amazon Web Services (AWS). “The more relevant and personalized your message, the more likely it is to help a customer find the right solution for their needs at precisely the right time.”

Partner marketing disconnects at the junction of two distinct categories: campaign strategy/execution and sales execution. While sponsors create content and marketing campaigns, partners traditionally lack the resources to launch campaigns efficiently, struggle to create tailored messaging, and follow up effectively. The results are a resource allocation that ends in poor accountability and missed opportunities for everyone involved.

Marketing Technology News: Idle data is as good as no data

“Despite significant channel opportunities, execution remains a persistent barrier. Research shows that 36% of channel marketers cite inadequate partner enablement and co-selling training as their top challenge, while 34% struggle to access partner-side counterparts to co-execute campaigns,” says Jay McBain, Chief Analyst, Omida (formerly with Canalys). “The result is a gap between what partner ecosystems could generate and what they deliver. When vendors leave partners to market on their own, campaigns often stall, leads go untouched, and revenue is uncaptured. Frustrating both the vendor and the partner.”

“Companies can now close the gap between campaign strategy and execution efficiently and with accurate measurability to activate pipelines for the greatest chance of success,” Jeff Holmes, CEO at eTrigue. “By leveraging eTrigue Insights Messaging, Lead & Company Insights and Sales Team Insights enterprise vendors can be in control of every step of the through-channel marketing and sales process. From launching campaigns to engaging with marketing qualified leads with more relevance, empowering sales teams for more effective follow up to tracking opportunities and sales team responsiveness, eTrigue Insights brings accountability to partner marketing. With seamless execution, eTrigue Insights Messaging enables a swifter time-to-engagement delivering higher quality leads thus increasing sales pipeline activity at a faster pace.”

eTrigue Insights platform and Lead Accelerator services offering are trusted by companies including AWS, Red Hat, NVIDIA, SAP, Shopify, Palo Alto Networks, and Watchguard, among others. Lead & Company Insights and Insights Messaging are available now with the eTrigue Insights platform and services offering. eTrigue Insights is based on the success of the eTrigue DemandCenter platform, widely used to create and run co-marketing campaigns for partners, simply, quickly, and at scale. The company’s white-label, turnkey service provides content, campaign buildout, eTrigue Insights platform, and all program management, ensuring partners can focus on lead follow-up and sales.

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Ataccama joins Databricks Marketplace to extend data trust from source systems to AI

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Ataccama joins Databricks Marketplace to extend data trust from source systems to AI

Ataccama brings AI to data lineage to help business users

Ataccama’s MCP Server, available now in the Databricks Marketplace, extends trusted data context from source systems through the Databricks platform to AI models and agents

Ataccama, the data trust company, announced a native integration with Databricks, the Data and AI company, to bring data quality, lineage, and governance signals from enterprise source systems, including SAP, Oracle, and mainframe environments, into the Databricks platform, helping customers build AI applications and agents on trusted data. Available now in the Databricks Marketplace, the integration connects Ataccama’s governed quality signals and metadata context directly to Databricks pipelines, workflows, and AI tools through the Ataccama MCP Trust Layer.

Enterprise AI has exposed a critical requirement for trusted data. As organizations consolidate data and AI workloads on platforms like Databricks, they need confidence not only in where data resides, but also in its quality, governance, and lineage. Without that context, AI outputs become difficult to explain and even harder to trust. A risk committee may reject a recommendation, a regulator may ask for documentation that cannot be produced, or a business leader may find themselves acting on results no one can confidently validate.

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The MCP integration is now available on the Databricks Marketplace. Databricks Marketplace is an open marketplace for data, analytics and AI, powered by OpenSharing. Together, Ataccama and Databricks address the full infrastructure that production AI requires. Ataccama operates as the trust layer, validating that data is accurate, complete, and certified before it reaches Databricks, so the business definitions, metrics, and relationships that Unity Catalog Semantics governs are built on data that can actually be relied on. A semantic layer defines meaning precisely, but it cannot guarantee that the underlying data reflects reality. Ataccama closes that gap, so every agent, model, and analyst working inside Databricks reasons from definitions that are both well-governed and verifiably correct, from the source systems that supply the data through to the AI outputs that depend on it.

“The next phase of enterprise AI will be defined by trust,” said Jay Limburn, Chief Product Officer at Ataccama. “The organizations that succeed with AI will be the ones that can understand, govern, and stand behind the data informing every decision. By bringing trusted data context directly into Databricks via Databricks Marketplace, we’re helping customers build the confidence needed to scale AI from promising pilots to business-critical outcomes.”

“Customers consistently ask us for easier, more secure ways to discover, access, and share data and AI assets across their organizations and ecosystems,” said Stephen Orban, SVP, Product Ecosystem & Partnerships at Databricks. “By bringing Ataccama ONE to the Databricks Marketplace, we’re helping our joint customers accelerate innovation and unlock more value from their data on an open, governed platform.”

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Key capabilities include:

  • Data trust signals are accessible to AI agents. Ataccama’s MCP Trust Layer exposes a combined semantic and quality layer to AI agents operating in Databricks, surfacing business glossary terms, catalog metadata, and quality scores so agents understand what a data asset means and where it came from, alongside live quality scores, monitoring results, and anomaly signals so they can assess whether it can be trusted before they act on it.
  • Quality checks that run natively on Databricks compute. Ataccama translates enterprise data quality rules into SQL and executes them through Spark pushdown directly on Databricks clusters, without moving data into a separate processing environment. This enables non-technical users to create data quality rules and validate billions of records at the scale required for enterprise AI and analytics workloads.
  • Pipeline gates that stop bad data before it reaches AI. Ataccama’s Data Quality Gates integrate directly with Databricks Lakeflow and DLT pipelines, evaluating data at defined checkpoints before it advances to the next layer. Quality rules and thresholds are defined once in Ataccama ONE and enforced automatically at each gate. Changes propagate across pipelines without requiring code updates. Records that fail a threshold are flagged, quarantined, or rerouted for remediation, ensuring downstream systems receive only trusted data.
  • An audit trail from source systems to AI outputs. Ataccama automatically scans source systems and captures lineage from Oracle, SAP, mainframes, and other enterprise environments through the Databricks platform to BI reports and regulatory outputs. Quality scores are recorded at each step, and full cross-system lineage – including systems outside Databricks that Unity Catalog cannot reach – is visible in a single interface.
  • Governance that follows the data, not the platform. Organizations can extend governance policies, stewardship processes, and metadata management across Databricks and upstream enterprise source systems across more than 200 connectors spanning mainframe and legacy environments, as well as platforms such as dbt and AWS Glue. Organizations define standards once, and Ataccama enforces them wherever data lives, moves, or is used.

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Nexxen Launches MCP & Agent-to-Agent AI Integrations to Platform

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Nexxen Launches MCP & Agent-to-Agent AI Integrations to Platform

One of the first platforms to support both in-platform AI usage and external agent integrations

nexAI embeds AI agents across planning, activation, optimization and monetization, within a platform that unifies demand, data and supply

Nexxen, the advertising technology platform powered by unique data and media, announced the next evolution of nexAI, with interoperability capabilities that allow external AI agents to connect to its platform via open protocols such as Model Context Protocol (“MCP”) and Agent-to-Agent (“A2A”), enabling customers to remotely access Nexxen’s advanced agentic capabilities through any MCP-compatible assistant. The launch will also include new agent-powered workflows across reporting, troubleshooting, campaign QA and audience research, building on nexAI’s existing agentic capabilities.

With the launch, Nexxen moves beyond in-platform AI features to an open AI operating system spanning a DSP, SSP and DMP, that delivers transparent, controllable and interoperable agentic AI across the full campaign lifecycle. In practice, this means Nexxen customers can integrate Nexxen’s data, planning and activation capabilities into their own tools and AI workflows, no longer operating solely inside the platform’s interface but building on top of it.

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Leveraging this endpoint, teams can stand up a reporting agent that compiles cross-campaign performance overnight and flags anomalies before the morning standup, run automated pre-launch campaign QA that checks setups against their own rules, and surface incremental spend recommendations directly inside their own planning tools, all while asking plain-language campaign management questions like “Which audience segments are performing best?” through whichever AI assistant their team prefers.

“Technologically advanced clients increasingly want AI systems that can connect across platforms and tools, rather than a walled garden approach. This new interoperability enables their teams to work more efficiently, while also auditing, understanding and governing their strategy’s execution end to end,” said Karim Rayes, Chief Product Officer, Nexxen. “This latest phase of nexAI reflects a major industry shift from AI experimentation to an open, agentic full-funnel AI layer that has only partially been addressed so far by platforms.”

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Collectively, nexAI delivers a distinct set of capabilities that remain largely nascent across the ad tech ecosystem:

True agentic workflows across the full funnel: Rather than isolating AI features, nexAI embeds AI agents across planning, activation, optimization and monetization within a platform that unifies demand, data and supply.

Dual-path architecture: Nexxen is one of the first to support both native AI usage inside the platform and external agent integration via open protocols like MCP and A2A.

Open, protocol-based interoperability: By embracing MCP and A2A connectivity, Nexxen is a “connectable” platform rather than a closed system.

Transparent, human-governed AI: nexAI emphasizes auditable decisions, human-defined guardrails and observable actions.

“Agentic buying is the next step in the evolution of how we transact media,” said Jeremy Cobb, Vice President of Digital Platforms, H/L. “While the rise of digital gave us the agility we lacked in the traditional TV era, agentic capabilities are the ultimate accelerator. By integrating these tools, we supercharge our speed-to-market and empower our teams to bypass manual data processing, executing optimizations at the precise moment they deliver the greatest impact. Nexxen’s latest advancements are a tremendous addition to this evolution, accelerating our ability to win in a fast-paced market.”

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BlueZoo Announces In-Store Video Advertising Agent Built on Google’s AI Technology

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BlueZoo Announces In-Store Video Advertising Agent Built on Google’s AI Technology

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Building on collaboration at NRF 2026, BlueZoo demonstrates how Google’s latest AI technologies can improve the sales performance of in-store video advertising.

In collaboration with Google Cloud, and leveraging Google’s Gemini Enterprise technology, BlueZoo is making available an AI agent to optimize in-store video advertising. This solution is available on GitHub today and will be demonstrated at InfoComm 2026 in Las Vegas, June 17-19 at the BlueZoo booth #C9713.

One of the most exciting aspects of this collaboration is the use of accurate and timely audience measurement to guide AI generation of video.”

— Lavi Nigam, Machine Learning Engineer at Google

The announcement builds on the prototype unveiled at NRF 2026, where BlueZoo and Google showcased how real-time audience measurement and AI-generated video content could be combined to maximize revenue performance of in-store video advertising. The AI agent, layered on Google’s latest technology, allows retail media network operators to progressively make their advertising more effective while protecting consumer privacy.

“Not all in-store advertising delivers the same point-of-sale revenue. By calculating revenue-per-impression, BlueZoo’s audience measurement reveals which advertisements perform best,” said Bill Evans, CEO of BlueZoo. “Because Google’s video synthesis has dramatically lowered the cost of video generation, creative directors can iteratively create and test many alternatives to find the most effective creative, increasing in-store conversion across the store chain. BlueZoo is replacing assumptions about creative quality with data.”

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BlueZoo’s platform provides fully anonymized audience measurement and analytics without collecting personally identifiable information. When combined with Google’s AI capabilities for low-cost video synthesis, retailers gain the ability to accelerate content creation, permitting iterative improvement of campaign creatives.

“One of the most exciting aspects of this collaboration is the use of accurate and timely audience measurement to guide AI generation of video,” said Lavi Nigam, Machine Learning Engineer at Google. “AI systems perform best when driven by fine-grain data that report real-world events. BlueZoo’s anonymized audience measurement, combined with retailer point-of-sales data, provide the inputs that the retail AI campaign agent uses to optimize the creative process.”

AI agent technology, designed to deliver intelligence and automate complex workflows to orchestrate multi-step tasks across connected systems. Google recently introduced Gemini Omni, its next-generation video generation technology. Accessing BlueZoo’s analytics in Google Cloud’s BigQuery data warehouse, employing Omni for video generation, and exposing the AI agent to retailer campaign managers via the Gemini Enterprise App, the agent employs a robust AI infrastructure.

Marketing Technology News: Idle data is as good as no data

The combined solution enables continual optimization in which AI-generated creatives are informed by real time audience data and adjusted based on point-of-sale revenue performance. This feedback loop improves advertising campaign effectiveness while preserving consumer privacy. As retail media networks evolve, this powerful combination of BlueZoo’s privacy-first analytics and Google’s AI infrastructure is essential for brands looking to maximize the ROI of every in-store screen. To experience this next-generation advertising agent firsthand, visit BlueZoo at InfoComm booth #C9713 or explore the open-source solution on GitHub today.

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VidAU Launches AI Marketing Agents Built on a Proprietary Marketing Execution Harness

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VidAU Launches AI Marketing Agents Built on a Proprietary Marketing Execution Harness

About Us -

VidAU launches AI Marketing Agents that unify content, ads, SEO, GEO, social media, and analytics into a self-learning marketing platform.

New platform transforms years of real-world marketing execution expertise into a reusable, learning-driven AI system that coordinates creative production, advertising, social media, creator marketing, SEO, GEO, and performance analytics.

The next generation of marketing won’t be defined by who has the biggest team or the largest software stack. Joanna, Co-Founder and CEO of VidAU”

— Joanna Chan, Vidau’s CEO.

VidAU today announced the launch of VidAU AI Marketing Agents, a new agentic marketing platform built on the company’s proprietary Marketing Execution Harness.
The launch marks VidAU’s evolution from an AI creative technology company into an AI-native growth infrastructure company. Instead of simply generating content or automating isolated marketing tasks, VidAU AI Marketing Agents convert proven marketing workflows, campaign playbooks, brand rules, channel knowledge, and performance feedback into a coordinated execution system that can plan, execute, measure, learn, and improve over time.

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VidAU’s core belief is simple: the next generation of marketing will not be won by companies with the largest teams or the most software tools. It will be won by companies that can turn marketing expertise into compounding AI execution. “The next generation of marketing won’t be defined by who has the biggest team or the largest software stack.,” said Joanna, Co-Founder and CEO of VidAU. “It will be defined by who can turn marketing expertise into a system that executes, learns, and improves every day. VidAU is building that execution layer.”

From Marketing Tools to AI-Native Growth Infrastructure
Modern marketers often manage dozens of disconnected platforms, creating operational silos that slow execution and make optimization difficult. Creative teams, paid media specialists, SEO experts, influencer managers, and analysts frequently operate independently despite sharing the same growth objectives.
VidAU AI Marketing Agents eliminate those barriers by coordinating multiple specialized AI systems under one intelligent orchestration layer.
The platform includes dedicated agents responsible for:
Creative Generation: Producing videos, advertising assets, landing pages, and multilingual marketing content tailored for different audiences and platforms.
Advertising Management: Optimizing campaigns across Google, Meta, TikTok, and additional advertising ecosystems with continuous budget allocation and bid adjustments.
Social Media Operations: Planning, publishing, monitoring trends, and engaging communities across multiple social platforms.
Creator Marketing: Discovering relevant influencers, automating outreach, supporting collaboration workflows, and measuring campaign performance.
SEO & Generative Engine Optimization (GEO): Building content strategies that improve visibility across search engines as well as AI assistants and answer engines including ChatGPT, Perplexity, and other emerging discovery platforms.
Insights & Analytics: Connecting performance data across channels to identify opportunities, detect risks, and converting every campaign outcome into reusable knowledge for future execution.
Unlike standalone AI tools, every agent shares context and collaborates toward the same business goals instead of optimizing in isolation, allowing the system to coordinate decisions across channels and improve with every campaign cycle.

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A Coordination Layer Built for Results
At the center of the platform is the VidAU Marketing Execution Harness, a proprietary control layer built from real-world marketing workflows, campaign playbooks, channel rules, brand governance patterns, and performance feedback loops accumulated through VidAU’s years of experience in creative production, localization, advertising, and global marketing operations.
The harness continuously translates high-level growth objectives into structured workflows, decomposes campaigns into agent-executable tasks, assigns work across specialized agents, applies brand and compliance guardrails, validates outputs before execution。
Instead of marketers coordinating software manually, they define objectives while the platform manages execution.

Learning From Every Campaign
One of the biggest limitations of traditional marketing automation is that each campaign often starts with little accumulated intelligence.
VidAU addresses this through a continuous learning framework that captures market signals, evaluates campaign performance, updates strategic models, and improves future decisions automatically.
Every execution cycle strengthens the platform’s understanding of audience behavior, creative performance, bidding strategies, and channel effectiveness—allowing optimization to compound over time rather than reset. Over time, this creates a marketing execution flywheel.
Built for the Era of AI Search
Consumer discovery is rapidly shifting beyond traditional search engines into conversational AI and generative answer platforms.
To help brands remain visible in this evolving landscape, VidAU integrates both Search Engine Optimization (SEO) and Generative Engine Optimization (GEO) into its autonomous workflow. The platform continuously identifies high-intent opportunities, develops content strategies, and adapts to changing search behaviors across both conventional and AI-powered ecosystems.
By treating GEO as a core marketing function instead of an afterthought, businesses can position themselves for long-term discoverability as AI increasingly influences purchasing decisions.

Enterprise-Ready by Design
VidAU AI Marketing Agents are designed for organizations that require scalability, governance, and seamless integration with existing infrastructure.
The platform supports direct connections with major advertising networks, CRM systems, customer data platforms, analytics environments, and enterprise workflows while maintaining brand consistency through built-in governance and compliance controls.
Multilingual capabilities and support for global markets enable organizations to deploy campaigns across regions without sacrificing localization or quality.

A New Category of Marketing Execution
For years, marketing software has helped professionals work faster.
VidAU believes the next evolution is software that works independently.
Rather than simply assisting marketers with isolated tasks, AI Marketing Agents assume responsibility for planning, coordinating, executing, learning, and optimizing toward measurable business objectives.
As organizations increasingly seek efficiency without sacrificing growth, autonomous marketing systems may become as fundamental as CRM and advertising platforms are today.

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Truescope Launches Truescope AI, Transforming Media Monitoring Into AI-Powered Intelligence

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Nowspeed Launches SEO AI Agent to Transform Search Optimization to Deliver a Breakthrough in Speed and Quality

Truescope's Competitors, Revenue, Number of Employees, Funding,  Acquisitions & News - Owler Company Profile

New AI platform introduces two intelligent teammates — Truescope Assistant and Truescope Analyst — giving communications pros instant, deep media intelligence

Truescope, the media intelligence platform built for modern communications professionals, today announced the launch of Truescope AI, giving communications teams two intelligent teammates to autonomously analyse, summarise and deliver insights across their media landscape. The launch marks a pivotal step in Truescope’s transformation to a fully AI-powered intelligence platform.

“The new age of media monitoring and analysis is AI-first,” said John Croll, Truescope Co-founder and CEO. “Truescope AI puts two intelligent team members to work the moment you log in, so communications professionals spend less time on research and more time on strategic work that actually moves the needle.”

For communications professionals who need to understand the real-world impact of media and social coverage, Truescope AI delivers what legacy monitoring tools cannot: the ability to construct and execute complex queries across aggregate data in real time, surfacing actionable intelligence in minutes rather than hours. Truescope AI works across the entire media landscape simultaneously to deliver sentiment breakdowns, executive briefings, competitive analysis and crisis-ready reports on demand.

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Truescope AI introduces two purpose-built AI teammates designed to capture every development and turn coverage into intelligence you can act on:

Truescope Assistant

Truescope Assistant is the always-on AI summariser teammate that ensures no piece of relevant coverage goes unnoticed. The moment a user is on the platform, Assistant has already processed and summarised the day’s media across every monitored source — surfacing what matters most and making media awareness effortless for every member of a communications team and their executives.

– Instant coverage summaries. Assistant summarises coverage across broadcast, online, print and social channels in Truescope in real time, collapsing hours of manual reading into a single structured brief. Daily and weekly digests run across saved searches automatically.
– Spike alert explainers. When coverage volume spikes, Assistant explains the topic, the driver, the lead outlets and the sentiment shift so the team can respond before the inbox fills.
– AI report sections and natural-language search. Drop an AI-written summary into any Truescope report in one click. Ask a question in plain language across your inbox and saved searches and Assistant returns the answer in seconds with the underlying articles cited.

Marketing Technology News: Idle data is as good as no data

Truescope Analyst

Truescope Analyst is the multi-agent AI media analyst purpose-built for communications. Ask one question and Analyst breaks it into parallel research threads (sentiment, share of voice, journalist profile, narrative risk, social conversation), runs each across Truescope’s enriched media pipeline, and returns one structured, source-cited report in minutes. What used to take a dedicated analyst days, or a third-party retainer weeks, now happens on demand. It delivers structured, evidence-backed intelligence that typically takes analysts hours to produce manually.

– Plain-language query engine. Users ask questions the way they naturally think and Analyst returns clear, sourced answers within minutes. Every insight is backed by transparent, traceable citations and source references so PR and comms professionals can walk into any meeting or crisis fully prepared.
– Sentiment, journalist and competitive intelligence. Analyst reports include granular sentiment breakdowns by source, topic and time period, alongside detailed journalist profiles that identify who is covering a story, how they frame it, and what their history reveals about their likely angle. Competitive analysis surfaces how your brand’s media presence stacks up against rivals across any defined period, giving teams the context to act decisively.
– Pre-built comms templates and comment-level social intelligence. Pick a template (share of voice, executive scorecard, crisis brief, journalist profile, competitor comparison, narrative analysis and more) and Analyst runs it across the entire monitored media set in minutes. On social, it covers comments and reactions across platforms for the full reaction beneath each post.

“AI should function as a true teammate for communications professionals, not just another tool,” said Michael Bade, Co-founder & Chief Technology Officer. “Truescope AI combines advanced reasoning with real-time media analysis to turn complex coverage into the strategic insights teams need to act faster and with greater confidence.”

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Equinix Collaborates with Cisco and NVIDIA to Deploy Secure AI Factories Across Global Data Center Footprint

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Equinix Collaborates with Cisco and NVIDIA to Deploy Secure AI Factories Across Global Data Center Footprint

Presidio deploys Cisco Secure AI Factory with NVIDIA at Equinix data center in complementary, partner-led lab environment

Endorsed architectures and live testing lab deliver faster path for enterprises from pilot to production AI

Equinix, Inc., the world’s digital infrastructure company®, unveiled an expanded collaboration with Cisco and NVIDIA to accelerate enterprise AI. Working with its partners, the company will enable customers to deploy the Cisco Secure AI Factory with NVIDIA across its global network of high-performance data centers, providing customers with standardized AI factory blueprints and automation that simplify deployments.

Equinix is also partnering with Presidio to deploy their Programmable AI Technology Hub (P.A.T.H.) Lab. The lab will give customers a real-world environment inside Equinix data centers to test, validate and refine AI infrastructure before enterprise-wide rollout.

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“The success of enterprise AI starts with its physical foundation,” said Gordon Mackintosh, Senior Vice President, Global Partner Sales and Ecosystems at Equinix. “Our collaboration with Cisco, NVIDIA and Presidio delivers the infrastructure AI workloads demand while giving customers a place to prove it out before they scale. This is how AI shifts from pilot to production with the speed, simplicity and certainty businesses need.”

By bringing the Cisco Secure AI Factory with NVIDIA into its global data centers, Equinix is making it easier for customers to access the interconnection density, specialized power and advanced cooling customers and partners need to deploy the latest AI hardware and software at scale. These deployments are based on NVIDIA reference architectures that are purpose-built to reflect how enterprises buy and deploy technology: through trusted partners and on infrastructure platforms they already rely on.

“As agentic AI reshapes the industry, long-term success belongs to partner ecosystems that can adapt and innovate as rapidly as the technology itself. Our collaboration with Equinix, Presidio and NVIDIA to deliver the Cisco Secure AI Factory with NVIDIA illustrates how a trusted agile partner ecosystem can deliver secure, flexible AI infrastructure quickly to meet customers’ needs,” said Cassie Roach, Global Vice President of Cloud and AI Infrastructure Partner Sales at Cisco.

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Bringing these architectures to life in a real-world environment, Presidio, a leading global technology services and solutions provider, has partnered with Equinix to develop the Programmable AI Technology Hub (P.A.T.H.) Lab. Built on Cisco’s Secure AI Factory with NVIDIA, the lab is a fully integrated, production-grade AI environment purpose-built for enterprises to test, validate, and refine their AI strategies before committing to full-scale deployment. Through the combined expertise of Presidio, Cisco, NVIDIA and Equinix, enterprises gain access to turnkey AI infrastructure proven to work across hybrid workloads, spanning public cloud, neocloud, on-premises, and colocation environments.

“One of the most important shifts we’ve seen in the last 18 months is that AI success is no longer about finding the most powerful model,” said Tim McHugh, VP Partnerships & Alliances at Presidio. “It’s about building the infrastructure that can run AI everywhere it matters, without sacrificing data sovereignty or control. Equinix Distributed AI™ is the foundation that makes that possible at global scale, and P.A.T.H. is how Presidio brings that capability directly to our clients. We’re not asking them to take our word for it — we’re putting them inside a production-grade environment and showing them what distributed AI infrastructure actually looks like in practice.”

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Thanis Introduces Executive Review Framework for Leadership Communication

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Thanis

Thanis Executive Review Framework preserves leadership voice while sharpening communication behind every critical decision.

Thanis today announced Executive, a new review framework designed to help leaders evaluate assumptions, strengthen reasoning, and preserve ownership of their communication.

Executive was developed around a simple premise: important decisions often begin as written recommendations. While many communication tools focus on grammar, readability, and content generation, Executive evaluates communication through the lens of reasoning quality, accountability, recommendation strength, and decision readiness.

As AI-assisted writing becomes increasingly common in the workplace, organizations face a new challenge: ensuring leadership communication still reflects the judgment, reasoning, and voice of the people responsible for making decisions.

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Board recommendations, acquisition assessments, transformation initiatives, investor updates, executive announcements, policy changes, and security incident communications increasingly shape organizational outcomes through written communication long before discussions occur in a meeting room.

“Many of the most important decisions inside organizations are influenced by documents before they are influenced by meetings. We became interested in helping leaders examine the assumptions, logic, and accountability structures inside those documents before they influence outcomes. As AI becomes a larger part of professional communication, preserving the leader’s voice becomes even more important. Organizations need to hear what their leaders actually think, not simply what an AI system generates on their behalf,” said, Stephen Woodard, Founder, Thanis.

The release comes as organizations continue evaluating the role of artificial intelligence within professional communication. While many tools focus on helping people create content faster, Executive was designed to address a different challenge: helping leaders critically evaluate the strength of the communication they have already written.

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The framework reviews documents across several dimensions, including:
-Clarity of recommendation and intent
-Strength and progression of supporting arguments
-Communication force and executive credibility
-Voice ownership and consistency
-Accountability and recommendation ownership
-Assumptions influencing proposed outcomes

A central capability within the framework is Critical Assumption Analysis, which identifies the single belief most responsible for carrying a recommendation and explains how that assumption may influence the proposed outcome.

According to Thanis, the capability emerged from observing a recurring pattern across leadership communications. Recommendations often appeared persuasive on the surface while depending on assumptions that remained unstated within the argument itself.

During development, Executive was evaluated against a broad range of publicly available and real-world leadership communication scenarios, including board recommendations, acquisition assessments, organizational restructuring proposals, strategic transformation initiatives, security incident communications, vendor renewal decisions, and executive thought leadership content.

The objective was not simply to improve writing style. The objective was to strengthen decision communication.

Thanis believes the distinction is becoming increasingly important as organizations rely more heavily on written communication to coordinate decisions across distributed teams, business units, partners, investors, regulators, and stakeholders.

As AI-generated content becomes easier to produce, the company believes leaders may place greater value on systems that help evaluate reasoning, challenge assumptions, and preserve accountability rather than simply accelerate content creation.

Executive is designed to function as a review layer rather than a generation layer, allowing leaders to maintain ownership of both their message and their decisions while receiving structured feedback on the strength of the communication itself.

“We weren’t trying to build another tool that helps people write faster. We wanted to help leaders think more carefully about the decisions their communication is carrying. Executive was designed to strengthen decision communication while preserving ownership of both the message and the reasoning behind it,” added Stephen Woodard, Founder, Thanis.

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MoEngage Launches Customer Engagement Magazine: Human or AI? For B2C Marketers

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MoEngage Launches Customer Engagement Magazine: Human or AI? For B2C Marketers

Inaugural Issue, Available Now, Features Insights from Chiefmartec’s Scott Brinker, Executives from Amazon Music and Calm

MoEngage, the Agentic customer engagement platform trusted by 1,350+ global consumer brands, launched The Customer Engagement Magazine: Human or AI?, a new quarterly print magazine for B2C marketers. The Customer Engagement Magazine offers practical insights from some of the marketing industry’s most respected practitioners on navigating the tension between automated efficiency and human judgment.

MoEngage is marking the launch with a physical debut at Movable Ink’s ThinkSummit, taking place June 16th–17th in New York City. Attendees can visit MoEngage at Booth #7 to pick up a complimentary copy of Issue 1 and subscribe to receive Issues 2 and 3 upon release.

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The publication’s overarching theme, “Human or AI?,” is explored across three core marketing disciplines:

  • Data: Why AI fails on bad foundations.
  • Personalization: Where the human touch is non-negotiable.
  • Risk: Navigating the ethics of automation.

Each issue, delivered quarterly, goes beyond short-form content to offer a nuanced, in-depth exploration of the complex relationship between human expertise and AI efficiency in customer engagement.

“Marketing leaders are tired of AI hype; they want to know how to actually lead in this new era,” said Raviteja Dodda, Co-founder and CEO of MoEngage. “We created this magazine because, while MoEngage is an Agentic platform, the ‘human’ element has never been more critical. After the response to our previous book, it was clear that marketers want more than digital content: they want a physical, practitioner-led guide to help them decide where AI should take the wheel and where the human hand must stay on the pulse.”

The inaugural issue, Data, takes a deep dive into the core concept that data does not automatically produce better decisions. Each contributor explores the question: “What happens when teams give AI the authority to make decisions on a foundation that is not ready?”

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Issue 1 features compelling editorials from Chiefmartec’s Scott Brinker, Gary Kamikawa, Head of Marketing Technology at Amazon Music, Jeffrey Lee, Lifecycle Marketing Technical Lead at Calm, and other industry leaders. In addition to the print version, subscribers can opt for a digital edition.

In an era where bland, AI-generated content is abundant, the magazine takes a more human approach, leaning heavily into valuable storytelling, Q&As, and lived experience to create a durable, premium print asset. Beautifully designed and thoughtfully edited, each edition is a collectible that marketers will want to save, discuss, and share with colleagues.

The Customer Engagement Magazine: Human or AI? was created for modern B2C brand marketers, industry decision-makers such as CEOs, CMOs, and VPs of Marketing from leading organizations, and the broader MoEngage community.

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