Customers primarily use the Intuned AI agent to automate websites that don't expose APIs. Common use-cases include scraping data, pulling reports, and submitting forms. As the website changes, our agent also helps automatically heal the automation.

On Intuned, browser automations are created by an AI agent and run as code. Our infra captures the context of every run, allowing our agent to debug and maintain the underlying code - to keep the automations working over time. This way, we’re able to offer the predictability, speed, and cost of code, without the painful parts of writing and maintaining it.

Here’s a demo of building a scraper on Intuned: https://youtu.be/ruZP73bK4FU

Here’s a demo of using AI to maintain a project: https://youtu.be/e4R4hLdHBro

Backstory: we were accepted into YC for a completely different idea. During the batch, because of Faisal's background at UiPath, several batchmates asked us whether RPA tools could fill API gaps in their products by automating websites without APIs. When it was time to pivot, we went back to those founders to dig deeper. (RPA in this context is referring to using UI automation to do complete non-testing tasks)

We discovered that the actual hard problem in browser automation is maintenance. Websites change, selectors break, and failures can be painful to reproduce and fix. So in early 2024, we decided to take a crack at this problem with a handful of customers. It needed a fair number of iterations before we landed on our current code-first approach.

How it works: Intuned is infra + agent, deeply integrated.

On the infrastructure side, Intuned is a managed runtime for browser automation code. Projects are usually Playwright-based TypeScript or Python. Users can write them directly in our online IDE, or hand the work off to the agent. Either way, once deployed, the platform runs each project in its own isolated machine and handles auth/session reuse, scheduling, batch execution, concurrency, observability, and the other plumbing around running browser code.

On the agent side, it took us a few iterations to get to the current approach. Our initial attempts were rigid pipelines: collect requirements, inspect the site, generate code, then try to patch whatever broke. It looked reasonable on paper, but real websites are too messy for fixed paths. Late last year, we were planning to ship that version when stronger models landed and harnesses like Claude Code and Codex showed what a more open-ended coding agent could do. We built a prototype on the Claude Agent SDK, it felt much better than what we had, and we scrapped the release and decided to rebuild the agent.

The rebuild came down to three pieces around the SDK: an execution environment for running long agent sessions reliably, a CLI that exposes the platform to the agent so it operates Intuned the way engineers do, and a custom plugin (skills + MCP) built around what we've learned building browser automations.

The infra-agent integration is where the product gets more interesting. The runtime doesn't just run the automation; it captures the context needed to debug it when it fails: params, results, traces, logs. That enables features like Fix with AI, where you can open a failed run and have the agent investigate and prepare a fix.

The same integration powers a feature called self-healing. For configured projects, the platform detects failures, starts an agent session with the relevant context, and either proposes a fix for review or deploys it automatically. Demo: https://youtu.be/IVHIXw0lYMs

We recently also packaged the infra and agent as an API called Web Task API, here is a demo: https://youtu.be/1olRn3l95vw

We strongly believe that browser automations can and should be faster, cheaper and more predictable. Check us out at https://app.intuned.io/, we have a free tier with trial credits for your first few automations. Excited to hear your thoughts, questions, and feedback!