AI Warm Introduction Agent

Cold outreach fails. Our AI Agent finds best path to decision-makers via trusted connections, scores it, and generates intro messages-helping B2B teams build trust and close deals faster.

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Inspiration

Cold outreach in B2B sales is inefficient—low response rates, lack of trust, and difficulty reaching decision-makers. We were inspired by how real-world deals happen through warm introductions instead of random emails.

This led us to a key idea:
What if AI + modern developer tools like Lovable could automate trusted introductions?

What We Built

We built AI Warm Introduction Agent using Lovable to rapidly design and deploy a full-stack AI-powered application.

The platform helps users:

  • Discover the best introduction path
  • Evaluate trust using scoring
  • Generate personalized AI messages

Instead of cold outreach, users get a smart, relationship-driven approach to sales.

How It Works

We model the network as a graph and use BFS to find paths.

We score each path using:

$$ Score = 0.4 \times Relationship + 0.3 \times Industry + 0.3 \times Seniority $$

Then AI generates:

  • Message to connector
  • Final introduction message

How We Built It

We leveraged Lovable as our primary development platform to:

  • Rapidly scaffold the full-stack app
  • Build UI components efficiently
  • Integrate backend logic with minimal setup
  • Connect to AI services via Lovable Cloud

Tech used:

  • Lovable (core platform)
  • React + TypeScript
  • Tailwind CSS
  • Supabase Edge Functions
  • Google Gemini API
  • BFS-based graph logic

Lovable significantly reduced development time and allowed us to focus on core logic and user experience instead of boilerplate code.

Challenges We Faced

  • Designing a meaningful scoring algorithm
  • Making AI outputs feel human and contextual
  • Structuring network data realistically
  • Balancing speed (hackathon) vs quality

What We Learned

  • Tools like Lovable can drastically accelerate full-stack AI development
  • Combining AI + algorithms creates real value
  • Trust-based systems outperform cold strategies
  • Execution matters more than idea in hackathons

What’s Next

  • Real LinkedIn integration
  • Live network syncing
  • ML-based success prediction

Built With

  • Lovable
  • React
  • TypeScript
  • Tailwind CSS
  • Supabase
  • Google Gemini API
  • BFS Graph Algorithm

Built With

  • bfs-algorithm
  • framer-motion
  • google-gemini-api
  • lovable
  • react
  • shadcn/ui
  • supabase
  • tailwind-css
  • typescript
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