We want to use AI to generate complex technical quotes for our customers, but we cannot risk sending an inaccurate bid. How do we structure a human-in-the-loop review process to verify AI outputs before they reach the client?

Question

Tyler Smith · Accepted Answer

Using AI to draft technical quotes is an excellent way to reclaim capacity for your estimator or sales engineers, but you must never let an AI send a bid directly to a client without human verification. A single hallucinated number can ruin your margins or lose the deal entirely. To solve this, build a strict human-in-the-loop workflow. First, have your AI system ingest the client request, past pricing data, and your standard service rates to draft the initial bid. The AI should generate not just the final number, but a detailed breakdown of how it calculated the cost, including any assumptions it made. Next, deliver this draft directly to your estimator via their CRM dashboard or a dedicated internal review queue. The estimator's job is not to build the quote from scratch anymore; their job is to audit, refine, and sign off on the AI's draft. To make this process bulletproof, establish clear thresholds. For example, any quote under a certain dollar amount that meets specific standard criteria can be approved quickly after a brief check. Any complex, custom bid over that threshold must go through a second human sign-off. This workflow keeps your technical experts in their sweet spot. They stop spending hours manually typing data and copy-pasting numbers, and instead focus their expertise on high-level validation and risk management. This drastically speeds up your response times while maintaining complete control over your pricing and margins.