Inspiration
Most opportunity discovery is noisy. Large prize pools, grants, hackathons, marketplaces, and other asymmetric opportunities are scattered across the web, while the real constraint is usually time: a $100,000 prize decided after your deadline may be less useful than a $12,500 prize decided next week.
What it does
Opportunity Operator is a deadline-aware AI decision engine. A user gives it a goal, a maximum cash window, and a minimum payout. The system semantically ranks verified opportunities against that goal, then combines AI similarity with payout size, deadline fit, and eligibility status.
It returns:
- the highest-ranked executable opportunity
- a transparent score
- the decision date and submission deadline
- evidence supporting the opportunity
- an execution pipeline
- the exact owner-only action where automation must stop
How we built it
The live backend runs as a Supabase Edge Function and uses Supabase's hosted gte-small AI model for semantic embeddings. Opportunity descriptions and the user's goal are embedded and normalized, then ranked with a weighted score:
48% semantic fit + 30% deadline fit + 17% payout fit + 5% eligibility/open-status
The frontend is a lightweight web interface that calls the deployed function and presents the ranked result, evidence, and owner-action boundary.
Live validation
A real production test returned HTTP 200 in 537 ms and selected DevNetwork [API + Cloud + AI] Hackathon 2026 as the top opportunity for a 40-day cash constraint, with an 88.7/100 score.
Why this matters
Opportunity search is usually treated as a list problem. Opportunity Operator treats it as a decision problem. It removes options that are too late, too small, closed, or too dependent on human labor, and it explains why the surviving option wins.
AI safety / human boundary
The system explicitly refuses to autonomously perform owner-only actions such as accepting legal terms, submitting identity documents, spending money, or impersonating the user. Those are surfaced as owner gates while the rest of the workflow is automated.
What could be next
The same engine can expand beyond hackathons to grants, RFPs, incentive programs, marketplaces, procurement opportunities, and other time-sensitive commercial workflows. Automated ingestion and live verification would turn it into a continuously running opportunity operating system for founders and teams.
Built With
- css
- html
- javascript
- supabase-ai
- supabase-edge-functions
- typescript