About OpportunityIQ
AI-powered SaaS that helps freelancers score job fit before they apply.
OpportunityIQ is a working production SaaS, live and fully functional today, not a prototype, not a mockup, not a pitch deck. What you're buying is a complete, deployed codebase built around a substantial technical asset: a deterministic scoring engine that does real analytical work, not just a thin wrapper around a chat model. The problem it solves: freelancers who apply to jobs regularly, on Upwork and similar platforms, burn real time deciding which listings are actually worth a proposal. OpportunityIQ answers that question directly: paste a job post, and get back an honest read on fit before you invest in writing a pitch. The workflow is complete, end to end. A user signs up, builds a lightweight profile and an evidence vault of past work, then pastes any job description into the analyzer. The app extracts the job's requirements, checks them against the user's actual, provable evidence, and returns a fit score, a confidence-rated recommendation, and a clear apply/maybe/skip decision. Every analysis is saved to history, and any analysis can become a tracked application, moving through draft, sent, interview, and won/lost. The scoring engine is the core asset. Rather than trusting an LLM's raw judgment, OpportunityIQ discards the AI's volatile opinions and recomputes fit, confidence, and recommendation through a roughly 1,500-line deterministic pipeline, pure, testable logic that a buyer's engineer can read, reason about, and modify with confidence. It's a substantial, auditable technical asset, not a black box: it's covered end to end by an automated test suite, and all 556 of those tests pass, alongside a clean TypeScript build and zero lint errors. The engineering underneath is solid. The stack is Next.js, Supabase (Postgres, Auth, Row Level Security), OpenAI, and Vercel, all standard, well-documented, widely-used tools, with no bespoke infrastructure to reverse-engineer. Security work is already done: Row Level Security is enforced on every table, and the codebase has no code path anywhere that uses a privileged database key to bypass it. The current production deployment has been independently verified as live, healthy, and serving traffic. You can take this in several directions. Run it as-is and start validating demand. Add a billing layer and begin monetizing. Market it directly to the freelancer communities it's built for. Or lift the scoring engine out entirely and repurpose it for a different product, the logic is decoupled enough to reuse. The transfer is documented, not improvised. The sale includes a full buyer documentation set, setup instructions, environment variable reference, Supabase schema and migration guide, deployment steps, and a literal transfer checklist covering exactly what moves directly versus what you'll set up fresh (your own Supabase project, Vercel account, and optional OpenAI key, none of the seller's personal accounts or credentials are included). One thing this listing won't do is oversell where the business actually stands. This is a pre-revenue asset sale: there is no verified external user base and no revenue to point to today. What's for sale is a genuinely working product and a real piece of engineering, priced and positioned as exactly that, so you know precisely what you're acquiring.
Project details
Website: https://opportunityiq-v2-ai-engine.vercel.app
Next step: <p>OpportunityIQ is a working product with a solid technical foundation, and there is meaningful room for a buyer to grow it commercially:</p><p><br></p><ol><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Add billing/subscription infrastructure (e.g. Stripe) to start monetizing the existing feature set.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Market directly to freelancers, virtual assistants, and independent job seekers on platforms like Upwork, Fiverr, and LinkedIn, where fit-scoring and application tracking are real pain points.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Expand the deterministic scoring engine to cover adjacent use cases beyond freelance gigs (e.g. full-time remote job matching, agency project intake).</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>Layer on usage analytics and onboarding flows to convert the existing pre-revenue product into a measurable funnel.</li><li data-list="bullet"><span class="ql-ui" contenteditable="false"></span>License or reuse the underlying scoring/evaluation technology in other job-matching or evaluation products.</li></ol><p>The codebase, test suite, and documentation are structured to make any of these a reasonable next step rather than a rebuild.</p>
For sale
Asking price: $3,900 USD
What's included
Source code, All related design work
Full git commit history, the 7 Supabase migration files (verified to fully recreate the schema on a fresh project), the 556-test automated test suite, and complete buyer documentation: README, buyer setup guide, environment variable reference, Supabase setup guide, deployment guide, known-issues disclosure, and a transfer checklist. The buyer sets up their own Supabase, Vercel, and (optional) OpenAI accounts; no seller accounts or credentials are included.
Reason for selling
I am busy with other things and no longer have time to maintain this project.