Informatica tightens bond with AWS's AI development tools

Improved integration

Although AWS provides some of the same data integration, preparation and governance capabilities as Informatica, many enterprises are wary of vendor lock-in and piece together data management systems rather than use tools from a single provider. As a result, many AWS customers are also Informatica customers.

These product announcements, taken together, tell a different story for Informatica users. Rather than data management as a preparatory practice -- something you do before the real AI work begins -- this positions the platform as operational infrastructure for autonomous agents.

To serve the needs of joint users, integrations between seemingly competitive vendors are common.

AWS and Informatica first partnered about a decade ago, and Informatica now provides versions of its capabilities optimized for use with AWS's analytics, data management and AI development platforms.

The new features introduced during re:Invent are similarly optimized for use with AWS's capabilities. The focus on agentic AI development, meanwhile, is based on feedback from partners and customers as well as Informatica's observations of market trends, according to Rik Tamm-Daniels, the vendor's global vice president of ecosystem alliances and technology.

"We gather insights from customers, our support and sales teams, and broader market trends showing the rapid adoption of agentic AI," he said. "Our goal is to give enterprises a clear and flexible path to build intelligent, compliant agents that can access and act on high-quality data in real time."

Meanwhile, AWS users are an ideal audience for Informatica, according to Kevin Petrie, an analyst at BARC U.S. He noted that many are investing heavily in AI projects, and data readiness is one of the main reasons some pilots fail.

"Compared to the overall market, more [AWS-based enterprises] have formal AI programs, and more of them have AI projects and advanced AI tool sets in production," Petrie said. "They are also highly focused on customer satisfaction as the top measure of AI success. And they depend heavily on rigorous data governance, viewing data quality as the no. 1 obstacle to AI."

In particular, Informatica's tools can help AWS users prepare data stored across cloud, on-premises and hybrid environments, he continued.

"As with all the hyperscalers, AWS users have a lot of data spread across diverse hybrid environments," he said. "Informatica can help them integrate, prepare, and govern these data inputs for AI projects."

Model Context Protocol (MCP), developed by AI provider Anthropic and launched in November 2024, became an integral part of agentic AI development pipelines throughout 2025.

Building agents is complex. It requires developers to discover relevant data, integrate and prepare potentially disparate data types, connect data to appropriate foundation models, feed data to applications and observe pipelines for proper performance.

Doing that each time an agent is built can be prohibitive. MCP helps simplify development by providing prebuilt code for securely integrating models with external data sources.

Informatica's MCP servers connect the vendor's Intelligent Data Management Cloud (IDMC) with AWS's Bedrock AgentCore -- a managed service for building agents using foundation models from various providers -- effectively linking external data sources with appropriate models so joint users can build agents that act on governed data.

While MCP servers optimized for Bedrock AgentCore integrate Informatica's IDMC with foundation models, Informatica's Enterprise Agent Blueprint provides an entire framework -- including MCP servers -- for building and deploying agentic systems on Bedrock AgentCore.

In addition to MCP servers, the framework includes prebuilt connectors and an API layer to simplify data management tasks that are part of agentic AI development.

Informatica's Cloud Data Integration (CDI) connector for Amazon SageMaker is also built to aid AI and machine learning development.

Now generally available, the connector enables data scientists and engineers using the SageMaker development platform to ingest prepared and governed data from Informatica to feed pipelines for machine learning, generative AI and analytics.

By positioning Informatica's IDMC as part of an operational infrastructure for agentic AI, the MCP servers, blueprint for development and connector for SageMaker provide users with the necessary tools to deploy agents successfully, according to Farmer.

"For users, [they] address a practical problem," he said. "Agentic systems don't simply consume data in batch processes. They query, interpret, and act on data dynamically. So, without proper governance woven into that runtime layer, agents will hallucinate, make decisions on outdated information, or violate compliance requirements in ways that only surface after the damage is done."

Meanwhile, the MCP servers stand out as potentially most valuable for joint AWS and Informatica customers, given that about one-third of AWS users already have an MCP server in production and more than half of those not yet using MCP servers are evaluating them, according to Petrie.

"The MCP server offering addresses a proven market demand," he said.

Unlike the agentic AI infrastructure capabilities, using Anthropic's Claude models in the Claire AI Engine through Amazon Bedrock isn't aimed at helping joint Informatica and AWS customers build AI tools. Instead, it is designed to improve the performance of Informatica's own agents.

Informatica provides Claire Agents that execute tasks such as data integration and ensuring data quality. The integration with Claude models through Amazon Bedrock is intended to make Claire Agents more effective as they perform tasks such as schema grounding, SQL optimization and semantic query generation.

Next steps

As Informatica looks ahead to 2026, its objective is to enable users to prepare data that can be trusted to inform AI applications, according to Tamm-Daniels.

"Our commitment is to help customers leverage their data to build AI solutions that deliver accurate, complete and actionable insights," he said.

One opportunity for Informatica to expand its current offering is to provide capabilities that not only prepare data for informing agents but help govern what agents do with data, according to Farmer.

"I'd like to see Informatica move beyond providing data to agents and begin instrumenting what agents do with that data," he said. "Informatica has the metadata infrastructure and the customer relationships to lead here if they can move quickly enough."

Petrie, meanwhile, noted that AWS and Google Cloud introduced new capabilities that enable their joint customers to connect and share data across clouds, which could present Informatica with an opportunity.

"I'll be interested to see how Informatica addresses this, because Informatica can provide a rich data management layer on top of both cloud platforms," he said.

Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.