Spur

Spur (YC Summer 2024) is an AI-powered agentic QA platform founded by Yale graduates Sneha Sivakumar and Anushka Nijhawan. Instead of writing test scripts, you describe what to test in plain language — 'add a product to the cart', 'submit a job application' — and autonomous browser agents execute those flows, adapt to UI changes without brittle CSS/XPath selectors, and flag real bugs with video replays and step-by-step analysis. The company raised a $4.5M seed round led by First Round Capital (with Pear VC, Neo, and Conviction participating) and has found early traction with e-commerce brands.

The honest caveat: Spur is still an early-stage startup, so the platform is less battle-tested than incumbents and enterprise compliance stories are thin. Agent-based testing can be slower and more expensive per-run than deterministic scripts, and highly dynamic apps (heavy canvas/WebGL, complex auth flows) may still need hand-written tests. Pricing is not public, which usually means 'talk to sales'.

Sign up at Spur's website and connect your staging or production URL. Write test scenarios in plain English in the dashboard, then schedule runs or hook them into CI.