A multi-agent AI pipeline that analyzes prospects, predicts hiring intent, generates personalized outreach sequences, and produces CRM-ready lead scores — all with confidence tracking and automated quality checks.
Multi-Agent BD Pipeline · PIE v2.0
LinkedIn Profile → Analysis → Strategy → Proposal → Quality Check
18-item output bundle with confidence scoring
Multi-Agent Proposal Intelligence Pipeline
## PROSPECT INPUT
Name: Chandan Kumar
Title: Head of Talent Acquisition
Company: smallcase
Industry Context: FinTech
## PROSPECT PROFILE DATA
Name: Chandan Kumar
Title: Head of Talent Acquisition at smallcase
Location: Bangalore, India
Experience:
- Head of TA at smallcase (2021 - Present)
- Lead Technical Recruiter at Digit88 (2018 - 2021)
Recent Post:
"We are expanding our core backend and platform engineering teams in Bangalore and Remote! Looking for strong Go and Java developers who want to build high-scale wealth-tech transaction systems. DM me if interested!"
## COMPANY DATA
Company: smallcase
Industry: Fintech / Wealth-tech
Growth Stage: Series C (Backed by Sequoia & Amazon)
Tech Stack: Go, Java, React, Node.js, PostgreSQL, AWS
Open Openings:
- Senior Backend Engineer (Go)
- DevOps Platform Engineer (Kubernetes)
- Principal Architect
Hiring Trends:
Rapid expansion of transactional backend ledgers to support rising volume in model portfolio investments.
## ADDITIONAL CONTEXT
(none provided)
---
Generate a complete BD proposal bundle as a single JSON object with this exact structure:
{
"executiveSummary": "string — 3-4 sentence high-level business case summary",
"prospectIntelligence": {
"name": "string",
"designation": "string",
"company": "string",
"location": "string",
"industry": "string",
"experience": "string",
"leadershipLevel": "string — one of: Founder, CEO, CTO, VP HR, CHRO, TA Head, Engineering Director, Recruiter, Manager, Partner, Investor",
"decisionAuthority": "string — High/Medium/Low",
"previousCompanies": ["string"],
"awards": ["string"],
"hiringOwnership": true/false,
"skills": ["string"],
"certifications": ["string"]
},
"companyIntelligence": {
"industry": "string",
"stage": "string — Startup/Scaleup/Enterprise/Public Company",
"funding": "string",
"ipo": "string",
"employees": "string",
"countries": ["string"],
"products": ["string"],
... [truncated]Run on any AI platform (copies prompt)
The Proposal Intelligence Engine (PIE) is Finlytic Pro's most advanced business development tool. Unlike a simple prompt generator, PIE operates as a team of 13 specialized AI agents working together to produce a comprehensive BD output bundle including intelligence analysis, psychology profiling, multi-channel outreach, and CRM-ready lead scoring.
PIE replaces generic outreach with intelligence-driven proposals that demonstrate genuine understanding of the prospect's business, hiring challenges, and communication style.
Enter Prospect Intelligence
Select Industry Playbook
Run the Pipeline
Review and Export
Enter Prospect Intelligence
Fill in prospect name, designation, company. Paste LinkedIn profile and company overview.
Select Industry Playbook
Choose the target industry to activate specialized hiring patterns and messaging.
Run the Pipeline
Execute the 13-agent pipeline to generate the complete BD output bundle.
Review and Export
Browse tabbed output sections and export the full markdown dossier.
PIE is a multi-agent AI system that simulates 13 specialized roles working together to produce a comprehensive BD proposal bundle.
PIE uses structured multi-agent architecture, industry playbooks, confidence scoring, and automated quality checking.
No. All inputs are processed client-side. API calls go directly to Google Gemini or OpenAI.
A multi-agent AI pipeline that analyzes prospects, predicts hiring intent, generates personalized outreach sequences, and produces CRM-ready lead scores — all with confidence tracking and automated quality checks.
Multi-Agent BD Pipeline · PIE v2.0
LinkedIn Profile → Analysis → Strategy → Proposal → Quality Check
18-item output bundle with confidence scoring
Multi-Agent Proposal Intelligence Pipeline
## PROSPECT INPUT
Name: Chandan Kumar
Title: Head of Talent Acquisition
Company: smallcase
Industry Context: FinTech
## PROSPECT PROFILE DATA
Name: Chandan Kumar
Title: Head of Talent Acquisition at smallcase
Location: Bangalore, India
Experience:
- Head of TA at smallcase (2021 - Present)
- Lead Technical Recruiter at Digit88 (2018 - 2021)
Recent Post:
"We are expanding our core backend and platform engineering teams in Bangalore and Remote! Looking for strong Go and Java developers who want to build high-scale wealth-tech transaction systems. DM me if interested!"
## COMPANY DATA
Company: smallcase
Industry: Fintech / Wealth-tech
Growth Stage: Series C (Backed by Sequoia & Amazon)
Tech Stack: Go, Java, React, Node.js, PostgreSQL, AWS
Open Openings:
- Senior Backend Engineer (Go)
- DevOps Platform Engineer (Kubernetes)
- Principal Architect
Hiring Trends:
Rapid expansion of transactional backend ledgers to support rising volume in model portfolio investments.
## ADDITIONAL CONTEXT
(none provided)
---
Generate a complete BD proposal bundle as a single JSON object with this exact structure:
{
"executiveSummary": "string — 3-4 sentence high-level business case summary",
"prospectIntelligence": {
"name": "string",
"designation": "string",
"company": "string",
"location": "string",
"industry": "string",
"experience": "string",
"leadershipLevel": "string — one of: Founder, CEO, CTO, VP HR, CHRO, TA Head, Engineering Director, Recruiter, Manager, Partner, Investor",
"decisionAuthority": "string — High/Medium/Low",
"previousCompanies": ["string"],
"awards": ["string"],
"hiringOwnership": true/false,
"skills": ["string"],
"certifications": ["string"]
},
"companyIntelligence": {
"industry": "string",
"stage": "string — Startup/Scaleup/Enterprise/Public Company",
"funding": "string",
"ipo": "string",
"employees": "string",
"countries": ["string"],
"products": ["string"],
... [truncated]Run on any AI platform (copies prompt)
The Proposal Intelligence Engine (PIE) is Finlytic Pro's most advanced business development tool. Unlike a simple prompt generator, PIE operates as a team of 13 specialized AI agents working together to produce a comprehensive BD output bundle including intelligence analysis, psychology profiling, multi-channel outreach, and CRM-ready lead scoring.
PIE replaces generic outreach with intelligence-driven proposals that demonstrate genuine understanding of the prospect's business, hiring challenges, and communication style.
Enter Prospect Intelligence
Select Industry Playbook
Run the Pipeline
Review and Export
Enter Prospect Intelligence
Fill in prospect name, designation, company. Paste LinkedIn profile and company overview.
Select Industry Playbook
Choose the target industry to activate specialized hiring patterns and messaging.
Run the Pipeline
Execute the 13-agent pipeline to generate the complete BD output bundle.
Review and Export
Browse tabbed output sections and export the full markdown dossier.
PIE is a multi-agent AI system that simulates 13 specialized roles working together to produce a comprehensive BD proposal bundle.
PIE uses structured multi-agent architecture, industry playbooks, confidence scoring, and automated quality checking.
No. All inputs are processed client-side. API calls go directly to Google Gemini or OpenAI.