Informatica update aims to provide trust foundation for AI
Agents that continuously perform master data management tasks and a headless architecture for data management improve access to data that can be trusted to inform outputs.
With many enterprises struggling to build AI tools that can be trusted in production, Informatica's latest product development initiatives aim to provide users with a foundation for building reliable agents.
Unveiled on Wednesday during Informatica World, the vendor's user conference in Las Vegas, new features in the Informatica Intelligent Data Management Cloud (IDMC) are highlighted by Agentic Multidomain MDM, which is a set of AI agents that continuously perform master data management tasks such as cleansing, enriching and stewarding data to maintain its quality, consistency and relevance.
In addition, Informatica launched headless data management capabilities -- including native support for Model Context Protocol (MCP) to connect agents with data sources -- that enable users to oversee their data from a central repository while leaving the data where it lives. New integrations, including some with Salesforce, which acquired Informatica in 2025, round out Informatica's IDMC additions.
Given that the new features accelerate master data management to ensure that data can be trusted to inform AI tools, and that they provide a new architecture for both human and agentic workflows, they are valuable additions for Informatica users according to William McKnight, founder and president of McKnight Consulting.
"This is an evolution of Informatica's IDMC from human-directed middleware into more of an autonomous data workforce that continuously cleans and governs data," he said. "It introduces headless data management … to provide front-end tools with real-time, context-rich data. By minimizing the traditional data trust bottleneck, this could enable AI to safely execute workflows independently."
Plenty of other providers are also adding agentic features, McKnight continued. However, Informatica's focus on trust and native integrations with key Salesforce capabilities help distinguish the vendor.
"Informatica differentiates through a focus on trusted data to drive live, real-time business transactions and automated actions," McKnight said. "Natively pairing with Salesforce allows it to stream trusted master data directly into front-end workflows. This headless framework could enable Informatica to embed complex data management into everyday business applications more fluidly than competitors."
Based in Redwood City, Calif., Informatica enables customers to integrate, prepare and govern data to ready it for analytics and AI. Peers range from fellow specialists such as Collibra and Fivetran to hyperscale cloud providers that offer master data management capabilities, including AWS, Google Cloud and Microsoft.
A trust foundation
As enterprises have increasingly invested in AI development over the past few years, but struggled to build tools trustworthy enough to move into production, data management and analytics providers have recently made enabling users to discover and operationalize contextually appropriate data a priority.
This is an evolution of Informatica's IDMC from human-directed middleware into more of an autonomous data workforce that continuously cleans and governs data. … By minimizing the traditional data trust bottleneck, this could enable AI to safely execute workflows independently.
William McKnightPresident, McKnight Consulting
Without contextually relevant data -- such as supply chain data for a supply chain optimization agent -- AI tools will fail to deliver trustworthy outputs and projects will fail. Vendors, however, have taken different approaches to improving data discovery and retrieval.
For example, Databricks introduced Instructed Retriever in January as an alternative to traditional retrieval-augmented generation, which has proven limited. MongoDB and Teradata have added capabilities that refine vector indexing and search to make contextually relevant data easier to discover. And GoodData and Tableau have built context layers that similarly aim to make it easier to feed agents contextually relevant data.
Like GoodData and Tableau that built on existing capabilities to aid AI development -- in their case semantic layers -- Informatica is building on existing master data management capabilities to provide users with a trusted data foundation for AI.
Agentic Multidomain MDM includes a Data Steward Agent to automate the time-consuming work of resolving quality issues and matching records to ensure accuracy. Informatica Agentic Integration automatically joins structured and unstructured data and feeds it into appropriate AI pipelines, and Data Quality and Metadata Enrichment Agents automate governance.
Meanwhile, headless data management, automated by Informatica's Claire AI engine, provides the architecture for organizations to automate their AI workflows.
Driven by a desire to improve efficiency through AI, demand for high-quality data is increasing exponentially, according to Gaurav Pathak, senior vice president of product management for Informatica. Developing Agentic Multidomain MDM and headless data management was a response to the increasing demand for trusted data to fuel applications that improve business efficiency, he continued.
"We have always focused on increasing data management productivity, and both of these [increase productivity]," Pathak said. "With headless data management, we are making that productivity available across every surface. That's the main driver."
Customer feedback showed that many AI initiatives are held back by systems that aren't ready for AI, he added, noting that the new features aim to help users overcome systemic barriers.
"The idea is to work with data quality tools to make sure that bad data does not reach agents, that context is available, make sure that no private, sensitive data is available to agents," Pathak said.
The user perspective
One of the customers using Informatica as part of its AI pipeline is Yum! Brands, a multinational fast food corporation based in Louisville, Ky., that operates such brands as KFC, Pizza Hut and Taco Bell.
Yum! has been an Informatica user for about a decade, and over that time its use of Informatica has evolved from extract, transform and load workloads to get data in and out of systems to master data management and governance.
Now, the company is using Informatica as the context layer for AI, according to Kartik Pillai, Yum!'s director of data strategy, master data management, AI and data governance.
"For us, Informatica plays a role in providing that golden record," he said. "It's about a golden record with context for agents -- the governance, the policies, the lineage, the quality that provides the holistic 360-degree record for an agent to act on. That becomes a feeder for some of our more custom agents."
One such agent is for forecasting labor needs at individual restaurants, a process that requires highly specific data, Pillai continued. Another is for financial reporting such as same-store sales growth.
As Yum! has experimented with AI, Pillai noted one of the barriers to moving pilots into production has been the ideal nature of proof-of-concept projects versus the messy reality of production environments. Governance, therefore, has become critical to ensure consistency so agents can be trusted.
Agentic Multidomain MDM and headless data management, which Yum! has experimented with in recent weeks, could further enable the company to build production-ready agents, according to Pillai.
"We have been conceptualizing with them, and I think definitely they will [help]," he said. "As far as getting things into production, it takes a bit of momentum to get it there."
Additional capabilities and next steps
Beyond Agentic Multidomain MDM and headless data management for AI, Informatica unveiled the following new capabilities:
Data 360 Connector and Scanner, an integration with Salesforce Data 360 that enables the real-time, bi-directional flow of data between Salesforce Data 360 and any enterprise system.
MDM Aware Data 360 to deliver trusted records to Salesforce Data 360 where users can activate data for real-time applications.
Claire in Slack, providing agents for data quality, data discovery and governance -- among others -- in Slack conversations so users don't have to switch between environments to complete their work.
Integrations with data platform and hyperscale cloud vendors simplify AI development, including availability of Informatica MCP servers in development environments such as Amazon Bedrock, Databricks Agent Bricks, Microsoft Foundry and Snowflake Cortex AI.
The integrations with Salesforce provide evidence that Informatica and Salesforce are a complementary fit, according to McKnight. However, accelerating master data management with Agentic Multidomain MDM is the most valuable new feature, he continued.
"As a long-time proponent of master data management, I would have to say that the accelerating of master data management with agents stands out for its efficiency gains in this important area," McKnight said.
Looking ahead, Informatica's product development plans focus on making both agents and humans more productive and accurate, according to Pathak.
Toward that end, initiatives include using metadata to make relevant data available to agents, providing users reusable data products that can aid AI development, and expanding AI-assisted data management and stewardship.
"Our vision for AI to be governed 90% by AI and humans providing 10% by supervising and [implementing] governance and guardrails," Pathak said.
McKnight, meanwhile, suggested that as more organizations put AI tools into production, Informatica could address emerging issues such as data sovereignty and multi-system governance.
"As they are about infrastructure and not a database or cloud company, they could do things like expanding on their recent framework for Microsoft Fabric Open Mirroring by building zero-copy governance bridges that span multiple competing cloud ecosystems simultaneously," he said. "They could launch local data sovereignty agents explicitly designed for localized infrastructure."
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than three decades of experience. He covers analytics and data management.
