AI Proposal Assistant

The AI Proposal Assistant was built to help teams quickly extract and summarize critical information from complex RFPs. Designed for commercial and technical users, the tool scans proposal documents, identifies relevant sections, and generates structured outputs to accelerate response time and reduce errors. I led product strategy and worked closely with internal stakeholders to ensure the tool aligned with how teams actually manage pre-sales work. 

My goal was simple; reduce the time and friction it takes to respond to detailed RFPs. I collaborated with engineering to develop a natural language processing pipeline and integrate custom logic tailored to battery storage and microgrid proposals. The assistant provides fast, structured intake across multiple file types and highlights missing information, helping teams act faster with fewer gaps. This laid the groundwork for broader automation across commercial workflows. 

The first version of the tool reduced intake time by over 50 percent and improved response accuracy across multiple proposals. It also helped unify how the team tracked requirements, coordinated across departments, and submitted consistent deliverables. By building a functional MVP and testing with live RFPs, we proved the value of applied AI not just as a buzzword, but as a practical, time-saving product with measurable business impact.