RELAI

RELAI is a verifiable continual learning platform for AI agents that turns failures and feedback into replayable learning environments to continuously improve agent reliability. The platform captures failed agent runs and reconstructs their full context including inputs, session state, tool calls, and memory snapshots, creating replayable scenarios for optimization. RELAI's lifelong agent optimizer continuously optimizes prompts, tools, memory, models, workflows, and agent logic as one unified system, tracing failures to the right layer and proposing validated improvements as reviewable pull requests. The platform serves as a learning system of record, tracking every failure, scenario, diagnosis, candidate fix, evaluation, and shipped improvement. RELAI integrates with major agent SDKs including LangGraph, LangChain, OpenAI Agents SDK, and Google Agent Development Kit, plus observability tools like Arize, Braintrust, and LangSmith. The platform has demonstrated 15-40% task success rate improvements and up to 80% reduction in token consumption. Founded in 2024 and headquartered in Washington, DC, RELAI has raised approximately $8.4 million in seed funding from investors including the National Science Foundation, .406 Ventures, Non Sibi Ventures, and TEDCO.

AI Infrastructure > Enabling Technologies > Software > Testing & Optimization > Generative AI

College Wise > Massachusetts Institute of Technology