Faisal and Ahmad launched Intuned, a YC‑S22 startup that turns natural‑language requests into production‑ready browser automation code. The platform targets sites without public APIs, letting users scrape data, generate reports, or submit forms without writing Playwright scripts themselves. By treating each automation as code, Intuned captures execution context, enabling rapid debugging and version control. This eliminates the manual upkeep that typically stalls RPA projects.

Intuned’s infra provides a managed runtime for Playwright‑based TypeScript or Python projects, handling authentication, session reuse, scheduling, concurrency and observability. Users can code directly in the online IDE or hand off the job to the AI agent, which iteratively generates, tests, and patches code as site layouts evolve. Isolation per project improves security. The system records parameters, results, traces and logs for each run.

The tight infra‑agent loop fuels features like “Fix with AI,” where a failed run opens an agent session that proposes a code diff, and self‑healing, which auto‑deploys vetted fixes. Intuned also exposes the stack as a Web Task API, letting developers invoke browser tasks via HTTP. The service offers a free tier with trial credits, aiming to make reliable automations cheap and predictable.