Loading...
AI ENGINEERINGTEAM.
Proof, Not Promises
Real benchmarks from real tests
Every number below comes from automated E2E tests against live AI providers. No cherry-picking, no mock data.
214
Tests Generated
Across 3 scenarios: 32 (todo) + 82 (e-commerce) + 100 (iterate). 4 categories: basic, edge, integration, security.
A
Quality Grade
Simple apps score A (90/100). Complex apps score B-C. Graded on completeness, security, compatibility, code quality, test coverage.
76%
Token Reduction (Cost Savings)
Test Agent output reduced from 11,431 → 2,763 tokens. Review Agent: 4,274 → 1,785. System prompts: -40%. Total: 35-45% savings.
19
Research Papers
From ICLR, NeurIPS, ACL, EMNLP, FSE, NAACL, ICML, ACM TOSEM. Every design decision has a citation. Not a weekend hack.
E2E Pipeline Results8/8 PASSED
ScenarioGradeTestsTimeComplexity
Simple Todo AppA903295s2/5
E-commerce PlatformC7882198s4/5
Iterate: Add ReviewsB87100241s4/5
Why Co-Lab
A better way to build software
Fragmented, slow, painful
Traditional development chains hand-offs across silos. Requirements drift, code reviews stall, and more time is spent coordinating than building.
Sequential hand-offs
Every step waits on the last
Context lost between teams
Docs, Slack, Jira, repeat
Weeks to ship one feature
3–6 week average cycle
Three steps to production
Research-Driven Features
Built on 19 papers from ICLR, NeurIPS, ACL & more
Every architectural decision has a citation. A system designed using peer-reviewed advances in multi-agent AI research.
Parallel Code Generation
Frontend and Backend agents run simultaneously, sharing an API contract for compatible endpoints and response shapes.
API Contract Specification
The Orchestrator writes a formal contract before any code is generated. Both agents implement the same spec.
Quality Grading (A-F)
Every generation is scored across 5 dimensions: completeness, security, compatibility, code quality, and test coverage.
Independent Test Generation
The Test Agent generates tests against the specification, not the code. Tests check what SHOULD work, not what DOES.
Feedback Loop
When quality is low, the system identifies specific issues, classifies which agent should fix them, and runs targeted repairs.
Human-in-the-Loop
You review the plan before code is generated. Two confirmation gates prevent wasted computation.
Multi-Provider Routing
Mix and match: GPT for frontend, Claude for backend, Gemini for review. Each agent can use a different model.
In-Browser Execution
Preview generated apps live via WebContainer — no setup, no install, no leaving the browser.
Stop prompting.
Start shipping.
Describe your app. Review the plan. Get production-ready code with tests, grading, and a live preview — all in one session.