Development of an AI system for generating personalized commercial proposals
A standard commercial offer doesn't work: the client sees a template and feels unheard. A personalized commercial offer, created in two minutes instead of two hours, addresses the specifics of the client's needs, their industry, and their pain points—and converts better.
System architecture
Data Layer:
- CRM data about the client (history, industry, size, needs from CRM notes)
- Call results (transcription → key requirements extraction via LLM)
- Product/Service Knowledge Base (descriptions, cases, prices, conditions)
Generation Pipeline:
- Extract needs from CRM + call transcript
- Match with relevant services/products from the Knowledge Base
- Select relevant case studies (vector similarity search)
- LLM generation of personalized text with specific client details
- Template rendering to PDF/DOCX/presentation
LLM Prompt Engineering: Structured output: JSON with sections of the proposal. Each section is generated separately for quality control. Validation: ensures that all client requirements are met.
Output formats
PDF (via WeasyPrint / Puppeteer), DOCX (python-docx), Google Slides (Slides API), branded template with corporate design.
Terms: 4-5 weeks
LLM pipeline + template system + CRM integration + PDF rendering.