A little bit of Extra Write up on The Tech Side:
Built with n8n + Gemini 3 API + XGBoost
Tech Stack:
- n8n – Multi-agent workflow orchestration
- Gemini 3 API – Research agent and proposal draft writing agent with tool-calling capabilities as well as parsing complicated structured output consistently and accurately
- Fireflies.ai – Call transcription logs
- XGBoost – ML pricing prediction (3-fold CV)
- FastAPI – Real-time ML inference endpoint
System Architecture
Multi-Agent Pipeline
Fireflies Call → Gemini 3 Research and Transcript Analysis Agent (Tool Calls) → Gemini 3 Proposal Draft Agent with
XGBoost Pricing (as a FastAPI) → Proposal Generation
1. Intelligent Research + Analysis Agent (Gemini 3)
- Analyzes discovery call transcripts in detail
- Uses tool calls to research prospects (company intel, tech stack, competitors)
- Extracts requirements and complexity factors (e.g annual client revenue, integration complexity, tech stack, pain points of clients)
- Gathers context for personalized proposals
- Parse a complex JSON as output for proposal writing
2. Proposal Drafting Agent (Gemini 3 + ML Pricing Engine (XGBoost + FastAPI))
- Predicts project quotes based on:
- Integration complexity
- Project scope
- Technical requirements
- Trained on 40 real deals + 30 LLM-synthetic examples
- Deployed as FastAPI endpoint for tool-call integration
- Then draft various sections of the proposals and parse different sections of proposals as a JSON field.
3. Machine Learning as a Tool (MLAT)
- Novel framework treating ML models as agent tools
- Real-time predictions within agentic workflows
- Rarely explored in modern AI literature
4. Real Time Discovery Agent (Gemini 3 Flash)
- Another mode of PitchCraft where the client themselves can talk to the discovery agent, and based on that transcript, it will do the above analysis
What Makes This Unique
ML with Limited Data: Successfully deployed XGBoost with only 70 total examples (40 real + 30 synthetic) through aggressive feature engineering (to 6) and CV tuning.
Gemini 3 Tool Integration: Research agent dynamically calls ML pricing API as a tool, combining LLM reasoning with statistical prediction.
Real Business Impact: We actually use it daily in our agency sales process:
Speed-to-Lead: Proposals delivered within 2-4 hours of discovery call vs. 2-3 days previously
Time Savings: Reduced proposal creation from 3+ hours to under 10 minutes of hands-on work
Consistency: Eliminated pricing variance—every quote now uses the same ML-driven methodology
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