Your AI agents can't reach the systems that run your business
The knowledge your agents need already lives in your core systems.
Your teams built those systems decades before AI existed, so agents have no safe, usable way to read their data or call their business logic.
Business knowledge sits out of reach
Legacy interfaces don't work for AI
Open access puts system of record at risk
A governed path from legacy to AI agents
OpenLegacy finds the high-value programs and data in your mainframe and IBM i estate, exposes approved operations as documented APIs, and publishes them as tools that AI agents can discover and call.
Agents work against live systems of record, so they retrieve current information and run proven business logic. Your teams decide which agent can use which tool, and your core systems keep running unchanged.
Discover legacy assets
Find the programs, transactions, datasets, files, and tables that hold high-value business knowledge.
Expose them as governed APIs
Turn selected operations and data into documented APIs with defined inputs, outputs, and publishing controls.
Publish agent-ready tools
Make approved APIs available to AI agents and MCP-compatible clients as tools they can discover and invoke.What changes when AI reaches your core systems
Every pillar comes from the same method: connect one business process at a time, prove its value, then expand.
Faster time-to-market
Generate production-ready APIs and agent tools in days instead of months.
Cost reduction
Reuse the business logic you already run instead of rewriting it, and cut legacy integration and mainframe costs by up to 60%.
Context reduction
Agents receive only the fields they need, summaries first and full schemas on demand, so they stay accurate and cost less to run.
Big-bang risk
Prove value on one business process at a time. Legacy and modern systems run side by side, and every step is reversible.