Informatica will work with the Customer to establish a foundational understanding of headless data quality services using Informatica Cloud Data Quality (CDQ) capabilities, with an initial focus on the Cloud Address Verification Model Context Protocol (MCP).
Key activities include:
(i) Discovery and use case assessment. Up to two (2) one-hour sessions to:
• Review Customer requirements and identify candidate use cases for Artificial Intelligence (AI)-driven data quality services.
• Assess use cases involving real-time address validation, standardization, enrichment, and integration with AI-driven workflows.
• Evaluate and confirm the complexity and scope of up to three (3) agreed-upon use cases.
(ii) MCP client setup for one (1) client limited to the following:
• Set up and configure one (1) supported MCP client using out-of-the-box capabilities.
• Establish connectivity to Informatica's Cloud Address Verification MCP server, subject to Customer-provided access and permissions.
(iii) CDQ MCP working sessions. Up to three (3) one-hour sessions to:
• Review supported Cloud Address Verification MCP capabilities
• Demonstrate how Artificial Intelligence (AI) agents and MCP-enabled applications can invoke approved address validation, standardization, and enrichment functions without navigating the Intelligent Data Management Cloud (IDMC) user interface.
• Review opportunities to incorporate real-time data quality validation into agent-driven workflows and complement existing batch or integration-based data quality processes.
(iv) Architecture and solution guidance, limited to the following:
• Provide guidance on enabling AI agents and applications to invoke approved data quality functions through supported MCP capabilities.
• Review considerations for maintaining consistent validation rules, security controls, response handling, and auditability.
• Identify applicable integration patterns for incorporating real-time address verification into AI-driven workflows.
Notes:
(i) Discovery activities are limited to a maximum of two (2) sessions, and MCP working sessions are limited to a maximum of three (3) sessions.
(ii) MCP client setup is limited to one (1) supported MCP client. Custom MCP client development is excluded.
(iii) Informatica will evaluate and confirm the complexity of Customer use cases and determine how many (up to three (3)) will be addressed within the working sessions.
(iv) Informatica will not develop or implement multi-agent orchestration.
(v) Custom MCP server development, extensions, or builds are excluded.
(vi) Demonstrations and assessments will leverage only currently supported, generally available or preview Informatica CDQ MCP capabilities, with the initial focus on Cloud Address Verification. Development of new MCP surfaces is excluded.
(vii) Demonstrations will be limited to supported address validation, standardization, and enrichment capabilities. Development or modification of custom data quality rules, mappings, or processes is excluded.
• Active IDMC organization with applicable CDQ capabilities
• Cloud Address Verification entitlement and configuration available (if applicable)
• Informatica Headless/Cloud Address Verification MCP access enabled
• Representative address data and expected validation outcomes available
• MCP-capable AI agent or client identified
• Existing Customer data quality standards or rules available for review
• Customer to provide a list of relevant stakeholders (e.g. data quality and security representatives) and ensure their availability for workshops, setup activities, knowledge transfer sessions and reviews
• Customer to provide the required MCP client environment, access credentials, permissions, connectivity, and representative address data for demonstrations
• Cloud Address Verification MCP capabilities reviewed and mapped to Customer use cases
• Up to three (3) candidate AI agent-driven data quality use cases assessed
• Point-of-entry address validation workflow outlined
• Interaction between real-time MCP validation and existing batch and/or integration quality processes identified
• Input, output, exception, and validation-response requirements documented
• Security, usage, and audit requirements identified
• Headless Cloud Data Quality MCP product documentation
• Data Quality MCP Use Case Summary
• Data Quality Agent Interaction Flow
PSU Catalog
8
Cloud Data Quality
Professional Services Units
Design
Plan
PSU-HDL-004
1-25 units
November 2026
A la carte
Additional Information
Professional Services Units can be converted into Training Units upon written request submitted to the Customer’s assigned Informatica Delivery Manager. The conversion ratio is one (1) Professional Services Unit to ten (10) Training Units. The converted Training Units can be used for any training currently offered in the Informatica University catalog other than training subscriptions. View available learning paths or log in to browse the full Informatica University catalog at https://now.informatica.com/All-Training-Paths.html. Educational Services are governed by the description and terms at https://now.informatica.com/Informatica-University-Terms.html.