We Built a Quote Generator That Turns Call Notes Into Proposals in 2 Minutes

One of our clients — a small consultancy with 8 staff — had a quote turnaround problem. After every discovery call, someone had to take their rough notes, work out the scope, pull together pricing, format it into a presentable proposal, and send it to the prospect. On average, this took about two days.

Two days is a long time when a prospect is comparing three providers and the first one to reply with a clear proposal often wins.

The Problem

The bottleneck wasn't the call itself — they were good at discovery calls. The bottleneck was everything that happened after. Specifically:

• Translating rough notes ("needs help with lead gen, 3 staff, currently using spreadsheets, budget around £X") into a structured scope of work.
• Mapping requirements to the right service packages and pricing.
• Formatting everything into a branded PDF that looked professional.
• Actually sending it while the conversation was still warm.

Each step took time, involved context-switching, and usually got delayed by other client work. By the time the proposal went out, the prospect had often gone cold or chosen someone faster.

What We Built

We built a single workflow that takes discovery call notes in and produces a formatted proposal out. The whole process takes about 2 minutes from paste to send.

Here's how it works:

• Input: The consultant pastes their call notes into a simple form — bullet points, rough notes, whatever format they used during the call. No special structure required.
• Extraction: AI parses the notes and pulls out key information — client name, requirements, team size, timeline, budget indicators, specific pain points mentioned.
• Mapping: The extracted requirements are matched against the consultancy's service catalogue and pricing matrix. The right packages are selected, quantities calculated, and pricing applied.
• Generation: A professionally formatted proposal is generated — branded with the consultancy's logo and colours, structured with scope, deliverables, timeline, and pricing. Written in their tone of voice, not generic AI-speak.
• Output: The finished proposal is delivered as a PDF link, ready to review and send. If it looks good, one click sends it to the prospect.

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What Changed

That's not an exaggeration — the 2 minutes of generation plus a quick review. That's not an exaggeration — the 2 minutes of generation plus a quick review. The consultant finishes the call, pastes their notes, reviews the output, and sends. All while the conversation is still fresh.

The quality didn't suffer. Because the system uses their actual service catalogue and pricing, the proposals are accurate. Because it writes in their established tone, the output is consistent with their brand. The consultant still reviews everything before sending — the automation handles the grunt work, not the judgement.

Over the following month, their proposal-to-close rate improved noticeably. Not because the proposals were better, but because they arrived faster — while the prospect was still thinking about the conversation.

This is one example of the kind of build our AI solutions team works on — see more case studies for similar projects, or read about automating CRM follow-up if lead management is your bigger bottleneck.