Manual map authoring has been the default approach to B2B data integration for decades. Many organizations maintain libraries of thousands of hand-built maps, and every new partner or customer adds another one. The specialists who build them are scarce and expensive, so the integration team becomes the bottleneck, and new customer onboarding and revenue wait with it.
From AI that assists a mapper to AI that builds the mapping
The first wave of AI mapping tools offered field-by-field suggestions, each with a confidence level and rationale, but a person still had to work through every mapping. Adeptia's AI Mapping agent does the work itself. Describe what you need in plain language, upload a sample file for context, and the agent scans the source and target schemas, builds the complete mapping, and asks clarifying questions when it needs more information. It reports its confidence in each field and brings decisions that need human judgment back to you for review.
The agent starts with 25 years of Adeptia mapping experience across insurance, financial services, healthcare and other data-intensive industries, and it learns automatically from every mapping your team builds, in an environment isolated to your organization.
Before anything goes live, you can run real or sample data through the mapping, end to end or down to a single field. Published mappings run as compiled, native code, so there is no AI at runtime: no added latency and no model cost tied to how often a mapping runs. You choose the AI provider (Anthropic, OpenAI, Azure OpenAI or AWS Bedrock) using your own account and API key, and your own AI agents can create and manage mappings through Adeptia's native MCP server.
The result: business users can onboard new trading partners themselves, and mapping work that took a specialist weeks now takes minutes.
Download the whitepaper to see how agentic AI data mapping works and what to look for in an AI mapping solution.