Spur is building an AI QA engineer that tests websites and web applications the way a real user would. Instead of writing brittle scripts, users issue plain commands such as 'add to cart' or 'apply for a job,' and Spur's AI browser agents click through the page, simulate the workflow, detect bugs, and return instant feedback.
This approach targets the perennial pain of web QA: keeping test coverage current as products change, and catching the kinds of real-world breakages that scripted tests miss. By driving the browser like a human, Spur's agents can validate end-to-end flows and surface regressions without teams maintaining large suites of selector-based tests.
Spur was founded by Yale graduates Sneha Sivakumar (CEO, previously at Figma and Snap) and Anushka Nijhawan (CTO, previously at DeepMind and Meta). The founders' combined background in design-led product and applied AI shapes a tool aimed at making quality checks faster and more accessible for development and e-commerce teams.
In April 2025, Spur raised a $4.5M seed round led by Liz Wessel of First Round Capital, with participation from Pear VC, Neo, Conviction, and angels from Figma, Dropbox, and Rippling. The company is using the capital to expand its AI QA engineer and hire across Applied AI, business operations, and go-to-market.
Spur sits in the fast-growing AI testing category alongside agent-driven QA tools, differentiating with a user-centric, command-driven model that appeals to teams and online retailers who want practical bug detection without deep test-engineering investment.