Informatica Adds AI-Driven Data Management and Governance Features to IDMC for Enterprise AI Readiness

Informatica Adds AI Enhancements to Intelligent Data Management Cloud

Informatica has upgraded its Intelligent Data Management Cloud (IDMC) platform with new AI-driven features aimed at improving how enterprises handle data for generative AI and agentic applications. Sitting atop existing databases, IDMC collects and catalogs data from multiple sources while enforcing governance policies. It offers tools for ETL, data quality monitoring, and master data management.

The recent updates focus on master data management, governance, and data integration to help businesses maintain high-quality data and trace its lineage effectively. With reliable data cleaning and unification across silos, enterprises can better support AI workloads that depend on accurate and trustworthy information.

Automating Records Matching for Compliance and Audits

One key addition is Claire Match Analysis and Explainability, which provides clear field-level insights into why records are matched or kept separate. This transparency supports audit trails and helps teams confirm that AI models reference verified “golden” records, reducing risks related to inaccurate data or compliance problems.

The feature also includes self-service tuning, allowing business users to adjust matching thresholds and retrain models without relying on IT teams. This accelerates feedback loops and improves AI-driven operations.

Informatica has further introduced an Enrichment and Validation Orchestrator to automate record validation and enrichment. Unlike some competitors that require extensive scripting, this orchestrator works seamlessly across Informatica services and third-party sources—including real-time input from large language models.

Additionally, the Data Catalog Scanner for MDM automates compliance tracking by harvesting metadata, mapping lineage, and integrating with Informatica’s Cloud Data Governance and Catalog. This helps enterprises prepare for regulatory audits and supports AI feature engineering efforts.

Enhanced Governance for Greater Visibility and Control

To give enterprises more control over AI data usage, Informatica added an AI governance catalog, a new API, and AI-powered data lineage discovery. The governance catalog monitors various AI models—including proprietary, customer-built, and third-party large language models—to ensure responsible deployment and centralized oversight.

Features such as automated risk scoring aligned with EU AI Act and NIST guidelines, model-card generation, and policy-driven approval gates simplify lifecycle management. The new API supports real-time data quality checks at the point of data entry, ensuring only compliant data is used downstream. This approach reduces cleanup efforts and builds greater trust in analytics and AI outputs.

Model Context Protocol Support and Other Platform Updates

Informatica now supports Model Context Protocol (MCP) on IDMC, enabling customers to connect MCP servers to any asset managed within the cloud platform. MCP is becoming essential for exposing trusted data assets to AI agents, allowing real-time interaction with authoritative business context and improving AI reliability.

Notably, many traditional master data management providers have yet to adopt MCP support, highlighting Informatica’s leadership in this area.

Other recent platform enhancements include new generative AI connectors for application integration and the general availability of Claire Copilot for data integration tasks.

For those managing AI initiatives, these innovations by Informatica provide practical tools to improve data quality, governance, and compliance—critical factors for successful AI deployment.