SignalDesk
Automated opportunity pipeline: scrape, classify with Groq, draft replies, ship to WhatsApp.
summary
- Ingests opportunity feeds from Reddit, Hacker News, Product Hunt, and GitHub Issues on a daily schedule.
- Scores each lead against a skill profile with Groq, then stores fit, source, and delivery state in MongoDB.
- Drafts a tailored first reply and cover letter from portfolio context instead of sending a generic template.
- Delivers the shortlisted batch through an authenticated WhatsApp Web session for quick human approval.
problem
- Useful leads expire quickly because public boards reward whoever sees, qualifies, and replies first.
- Manual scanning burns time before fit, budget, timing, and contact context are clear enough to act on.
- Generic outreach weakens trust, so every draft needs to reflect the role, portfolio evidence, and timing.
approach
- Adapters normalize each source into Candidate records with role, budget, timing, and contact context.
- Groq scores fit against a saved skill profile, while MongoDB hashes prevent repeats across every source.
- A drafting pass uses portfolio context to prepare the reply and cover letter before WhatsApp delivery.
outcome
- The pipeline turns daily board scanning into a short approval queue with role-aware outreach ready.
- Delivery state, retry pressure, source failures, and provider usage all stay visible instead of buried in logs.
- The human chooses approve, edit, or skip while the system keeps search and drafting repeatable each morning.