Best AI Metrics and Evaluation Startups & Tools

Measure and benchmark AI quality, speed, and reliability across real-world tasks.

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CanIShip

Indie hackers reinvent QA every Thursday by typing “npm test” and calling it a day, then wonder why no one sticks around after launch. CanIShip extracts that wishful thinking and submits the product to the same nine-point safety regime merchants use when their cargo crosses an international border. You copy your URL, write one sentence about what the app does, and in fifteen minutes get back a thumbs-up or a red stop sign alongside detailed receipts. The service runs its full battery on every pass: functional tests that drive flows with Playwright, axe-core accessibility scans against WCAG 2.1 AA, Lighthouse tight core-web-vitals benchmarks, header audits drawn from OWASP checklists, network link validation, mobile viewport diagnostics at 375 px, plus an extra layer that flags business or regulatory red flags such as illegal products, fake engagement, or platform policy marshes. Nothing to install and no access tokens traded away; the runner just needs the publicly reachable site. Three inspections per month cost exactly zero euros, and after that the published plan shows only paid tiers without surprises. Founders who equate “ship” with “upload” receive instead a short essay explaining why their little rocket is about to explode—or why it is cleared to leave orbit. Ultimately useful only for web front-ends today, yet within that narrow corridor the breadth is unmatched: one submission produces data a full QA team would normally cobble together from five separate tools, spreadsheet gymnastics, and at least one collaborator whose eyes glaze over at pytest. Solo builders shipping AI-generated code will understand exactly what still needs human editing, and they will understand it before the Hacker News headline goes live.

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Hani Mebar