We receive dozens of requests for proposals every week that arrive in completely different formats, and our estimating team spends hours manually rekeying this data into our internal systems. How do we build an automated AI workflow to parse these messy incoming RFQs?

Question

Tyler Smith · Accepted Answer

Handling incoming requests for proposals in various, messy formats is a common operational bottleneck that keeps your estimating team in low-value data entry seats. You can solve this problem by building an automated AI workflow to parse these documents and make your estimating process system-dependent.

Start by documenting the exact data points your estimating team needs, such as quantities, project timelines, materials, and delivery addresses. Next, build an automated workflow that sends all incoming proposal requests to an AI agent configured using low-code tools. This agent is programmed to read the unstructured document, extract the required fields, and format them into a clean, standardized data structure.

This parsed data can then be automatically loaded into your internal systems or CRM. Your estimating team no longer has to spend hours copying and pasting details from PDFs or messy emails. They simply review the standardized data and generate the pricing. This workflow dramatically reduces manual entry errors, cuts down on turnaround time, and allows your team to handle a much higher volume of opportunities. By turning a chaotic manual process into a system-dependent operation, you improve your operational efficiency and make your business far more scalable.