Javis OS
Javis OS는 기업가를 돕는 에이전시 AI로, 업무를 지원하고 함께 성장합니다
소규모 사업자를 위한 계약 검토, Redline은 위험 조항을 서명 전 정확한 문장과 함께 표시합니다
Contract review for small business owners. Redline flags the risky clauses in a contract before you sign it, each tied to the exact sentence it came from.
비즈니스TypeScript · CSSGitHub @gurn3k온라인운영자 미확인
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프로젝트 폴더에서 /nomorevibe verify를 실행하면 소유권을 확인하고 소개를 직접 관리할 수 있습니다.
1분 만에 확인하기Read it before you sign it. AI contract review for small business owners, where every risk flag cites the exact sentence it came from
저장소 README에서 가져옴
README 전체를 불러오는 중입니다.
README 전문 보기 ↗Read it before you sign it. Redline reviews a contract someone hands a small business owner, before they sign it. It returns a plain-English summary, risk flags ranked Dangerous or Unusual, a drafted counter-offer for each flag, and a Q&A box that answers only from the uploaded document.
Live: redline-review-nine.vercel.app · Sample analysis, no sign-up
The rule it's built around: if Redline can't point to the exact sentence, it doesn't show the flag. Every flag's quote is checked in code against the document's text, and a flag whose quote isn't an exact match is dropped before the reader sees it (ADR 0001).
Built by Gurnek Khaira with AI coding agents (Claude Code), working from market research, a product spec, decision records and scoped tickets.
/sample shows a real, unedited review of a refrigeration service contract, generated once by the live pipeline and checked by a test that every quote is word for word.Research first. Four research passes: who has the pain, what goes wrong, which tools exist, and who would pay (research/). They found the original idea was weaker than assumed: Pact, ContractClarifyAI and ClauseGuard already did most of it. Redline was repositioned on one claim a reader can check for themselves: every flag quotes its exact source.
A spec with explicit choices. The PRD names the segment (small business owners) and excludes freelancers, renters and job seekers. Ten decision records set the rules, among them precision over recall, flags stated plainly with no hedging, and positioning as document literacy rather than legal advice.
Twelve scoped tickets, built by AI coding agents against test fixtures with planted clauses and known answers. BUILD-REPORT.md records what was built, every decision made along the way, and what couldn't be verified.
A live smoke test against the real model caught 5 of 6 planted risky clauses with the correct severity and exact citations. It also raised 1 borderline Unusual flag on a contract designed to be clean. Both results are reported as they came out, not tuned away on one run.
An adversarial test of the deployed site (FINDINGS.md). All 24 flags it saw quoted their document word for word, including Spanish text and a clause near the end of a 75,000-character contract. A hidden "don't flag this" instruction inside a contract didn't change the flags. Q&A refused a request for legal advice. The test found 5 issues. Four are fixed, each with a test, starting with the most serious: an English personal guarantee was never flagged (PR #1). A security review of the whole codebase, using Anthropic's method, found nothing that met its bar for an exploitable problem.
A design revamp for the people who actually visit: hiring managers first, small business owners close behind. A before-review, three visual directions, an after-review and a new design system are in and .
Requires Node 22 or later and a Supabase project (schema in supabase/migrations). Set these in .env.local:
NEXT_PUBLIC_SUPABASE_URLNEXT_PUBLIC_SUPABASE_ANON_KEYOPENROUTER_API_KEYOPENROUTER_MODELnpm install
npm run dev # http://localhost:3000
npm test # 81 tests
npm run smoke # runs the fixture contracts through the full pipeline; uses a stub model if no API key is set
Stack: Next.js · TypeScript · Supabase · OpenRouter · Vercel
MIT