<\/span>Which proposal sections should remain under human review?<\/span><\/h3>\nHumans should approve material commercial, legal, security, privacy, and delivery commitments. Review should also cover unsupported claims, unusual terms, strategic positioning, and exceptions outside established policy.<\/p>\n
<\/span>How can AI avoid inventing product or pricing claims?<\/span><\/h3>\nRestrict generation to approved sources, require traceability for material claims, and stop when evidence is missing. Prices and calculations should come from authoritative systems and deterministic rules.<\/p>\n
<\/span>What systems should connect to the workflow?<\/span><\/h3>\nCommon connections include CRM, product knowledge, pricing or CPQ, contract management, security content, document generation, approval messaging, and storage. Your exact architecture should follow the authoritative source for each decision.<\/p>\n
<\/span>Can this approach automate RFP responses?<\/span><\/h3>\nYes, especially for classifying questions, retrieving approved answers, drafting responses, and routing exceptions. However, complex security, legal, and capability answers still need accountable review before submission.<\/p>\n
<\/span>Which metrics should a pilot track?<\/span><\/h3>\nTrack turnaround time, reviewer effort, factual correction rate, source coverage, exception frequency, adoption, and post-delivery rework. Together, these show whether the workflow improves both efficiency and quality.<\/p>\n
<\/span>Should we buy software or build a custom agent?<\/span><\/h3>\nBuy when standard templates, content libraries, and supported integrations meet your needs. Consider a custom agent when you require specialized retrieval, permissions, pricing logic, or cross-system exception handling.<\/p>\n