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Celnet · 2026

Bid intelligence agent

Multi-step LangGraph orchestration with human approval gates placed at every irreversible decision.

  • LangGraph
  • GPT-4o
  • Gemini 2.5 Pro
  • FastAPI
  • React
  • TypeScript
Problem

Enterprise bidding is high-stakes and slow: teams have to pull signals from procurement platforms, CRM history, and internal documents, then make a judgment call on whether and how to bid — all under deadline pressure where a wrong automated move, an early submission, a bad number, can't be undone.

The interaction decision

Let the agent do the research and drafting work continuously, but stop and surface a review screen at every step that can't be reversed, before a bid figure is finalized, before anything goes out. The system explains why it's recommending a decision, not just what the decision is, so review takes seconds instead of requiring the reviewer to redo the research themselves.

Architecture

LangGraph orchestration over GPT-4o and Gemini 2.5 Pro, with structured tool calling and retrieval against HigherGov and internal knowledge repositories, business-rule validation nodes, and stateful checkpoints where the graph pauses for human input. FastAPI services connect the graph to HubSpot and internal CRM data; a React and TypeScript frontend renders each pending decision as a reviewable card rather than a raw log.

What shipped

An end-to-end enterprise agent that moves a bid from raw opportunity data to a reviewed, submission-ready package, with humans in the loop at the decision points that matter and out of the loop everywhere else.