Building a Multi-Agent AI Pipeline with Mastra and TypeScript
Building an AI feature is easy. Building a reliable multi-agent pipeline that coordinates four specialized AI agents, persists intermediate state, skips already-completed work on retries, and keeps the API responsive while the models think — that is the hard part. This post walks through the architecture behind Clause AI , a platform that analyzes rental and lease agreements. It extracts key…
This article discusses the development of Clause AI, a platform that analyzes rental and lease agreements using a multi-agent AI pipeline powered by specialized AI agents. The article highlights the challenges of building a reliable pipeline, such as handling worker crashes, avoiding redundant processing, and managing rate-limited model endpoints.
To address these issues, Clause AI employs four purpose-built agents with distinct responsibilities and tuned model parameters. The Parser Agent extracts entities and clause-level structures with low reasoning and temperature settings, while the Summary Agent generates plain-English summaries. The Risk Agent flags risky clauses with severity scoring, and the Query Agent answers user questions using Retrieval-Augmented Generation. All agents produce structured output using Zod schemas, ensuring precise and deterministic results.
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