ReviveIQ

AI-Powered Dead Deal Resurrection | Never lose a deal to bad timing again

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📖 About the Project

ReviveIQ was born from a simple question:
“Why do companies lose so much revenue just because the follow-up was mistimed?”

While exploring HubSpot for my own workflow, I noticed a massive problem:
thousands of closed-lost deals just sit there forever, even though many could be recovered with the right timing. Sales teams rely on reminders, spreadsheets, or pure luck — and none of it scales.

🔥 Inspiration

I wanted to build something that:

  • scans closed-lost deals automatically
  • detects real-world trigger events
  • alerts the sales team at the perfect moment
  • and revives revenue that would otherwise be forgotten

That’s how ReviveIQ started — as a small script to detect funding signals — and it evolved into a full-blown AI-powered agent.

🛠️ How I Built It

The project is built using:

  • Node.js 18+ (backend and core logic)
  • HubSpot API v3 (CRM integration)
  • Google Gemini (AI analysis + email generation)
  • Multiple data sources (Crunchbase, News, Apollo)
  • Event-driven architecture with modular signal detectors

I structured it so each “revival signal” works as its own detection module.
Then the AI layer adds:

  • context analysis
  • confidence scoring
  • personalized outreach

Everything finally syncs back to HubSpot with tasks + notes.

🎓 What I Learned

This project taught me:

  • How to design production-ready, fault-tolerant Node.js systems
  • Best practices for HubSpot API integration
  • How to combine multiple external APIs efficiently
  • Prompt-engineering for AI models like Gemini
  • Error handling, rate limiting, retries, exponential backoff
  • Structuring real-world ETL + enrichment pipelines

⚠️ Challenges I Faced

Building ReviveIQ was not easy. Major challenges included:

  • Handling API inconsistencies across different data providers
  • Designing a modular signal engine that can scale
  • Ensuring speed (~2 seconds per deal) even with multiple external calls
  • Making AI output reliable and consistent
  • Preventing task-spam in HubSpot by using confidence thresholds
  • Creating meaningful, actionable revival signals (not noise)

But solving these problems made ReviveIQ robust, fast, and genuinely useful.

🎥 Full Project Demo (Uncut Screen Recording)
👉 Watch the real working demo here

ReviveIQ is more than a tool it’s a way to recover lost revenue using intelligence, automation, and perfect timing.

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