What challenges did Informatica face before AI implementation?

Disconnected, fragmented, and ungoverned enterprise data causing inefficiency and mistrust in AI-driven automation. Need for real-time, high-quality, governed data to power AI systems with trustworthy insights. Ensuring data privacy, compliance, and governance in AI data consumption.

Source

MicrosoftProductionEvidence: Low40/100

Informatica and Azure AI Foundry: Enterprise AI Agents for Trusted Data-Driven Decisions in Insurance

Use case typeFraud detectionUpdated Jun 13, 2026

Informatica's Intelligent Data Management Cloud (IDMC) integrates with Azure AI Foundry to provide context-aware AI agents that enable trusted, compliant, and explainable enterprise AI decisions. The integration focuses on handling fragmented, ungoverned enterprise data with high-quality, governed data accessible in real-time by AI agents, using MCP servers as a bridge between data and AI. The system supports data discovery, integration, privacy, access control, governance, lineage tracking, and master data management, ensuring AI decisions are based on reliable and verified data. A real-world insurance fraud detection agent uses Azure AI Foundry and Informatica MCP to analyze claims data, identify anomalies, and reduce fraudulent claims while accelerating valid claims processing.

Organization: Informatica
Industry: Insurance
Location: United States
Published: November 2025

Reported outcomes

Strategic outcomes

Risk & complianceTrusted, compliant AI decisionsCustomer experience & trustImproved claims processing and trustRisk & complianceFull data traceability and auditabilityNew product / capabilityContext-aware enterprise AI agents

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: Informatica
Provider: Microsoft
Maturity: Production
Linked source: Informatica Blog

Improved operational efficiency by accelerating the processing of legitimate claims

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Fraud Detection
2AI Agents
3Data Governance

Disconnected, fragmented, and ungoverned enterprise data causing inefficiency and mistrust in AI-driven automation.
Need for real-time, high-quality, governed data to power AI systems with trustworthy insights.
Ensuring data privacy, compliance, and governance in AI data consumption.

Integration of Informatica's IDMC MCP servers with Azure AI Foundry to expose curated and trusted data with metadata, lineage, and governance policies.
Use of Model Context Protocol (MCP) for contextual bridging between AI agents and enterprise data, enabling intelligent data discovery, access control, quality assurance, and master data management.
Deployment of AI agents in Azure AI Foundry using GPT-based retrieval-augmented generation to detect insurance fraud and generate explainable audit reports.

Technologies

Azure AI Foundry Azure OpenAI Informatica IDMC MCP Servers

Reduction in insurance fraud losses through early and accurate detection of fraudulent claims.
Improved operational efficiency by accelerating the processing of legitimate claims.
Full traceability and compliance with data provenance and audit trails for AI-driven decisions.

Architecture

The architecture involves an App Layer for secure user interaction, an Azure AI Foundry layer for cognitive agent orchestration, Informatica IDMC MCP servers for AI data management and governance, and an enterprise data layer integrating diverse data sources, providing trusted, high-quality data to AI agents.

Sources & evidence1

Evidence: Low40/100Evidence strength