Self-Healing Browser Automation

Automate logins, data collection, and visual checks in real browsers, with AI steps that repair broken selectors and secure code execution when you need it.

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The problem

Browser automations break the moment a page changes: selectors stop matching, logins expire, and scripts fail silently until someone notices the missing data.

How it runs today

Teams maintain brittle scripts by hand, re-record entire flows after every UI change, and keep session cookies in ad hoc places that nobody can audit.

With Heym

Build the flow as Playwright steps or sandboxed Python, let AI steps repair failed selectors mid-run, and restore sessions from saved cookies with a login fallback.

The workflow, end to end

The Playwright Visual AI Monitor template is an importable starting point: it takes a full-page screenshot on a schedule, has an LLM inspect the page for anomalies, and sends a Slack alert when something looks off.

Target sitePlaywright steps or codeAuto heal and auth checksData, screenshots, alerts

Playwright Visual AI Monitor

Sticky Note

Before you run

Adjust the cron schedule before enabling this in production.
Verify the destination channel, chat, queue, or socket before sending live traffic.
Swap the demo URLs and selectors for real endpoints you control.

Sticky Note

Playwright Visual AI Monitor

Take a full-page screenshot on a schedule, analyse it with an LLM for anomalies, and Slack-alert when something looks off.

Main path

Every30min -> CaptureScreen -> AnalyseVisual -> IssueFound -> AlertTeam -> ...

Every30min

CaptureScreen

AnalyseVisual

GLM-4.7

IssueFound

true

false

AlertTeam

AllClear

Sticky Note

Live run checklist

Test both exits around IssueFound before going live.
Tune the schedule, wait, or batch size first so repeated runs stay predictable.
Double-check AlertTeam before sending alerts or messages to a live destination.

Open this template, inspect every node, and import it

See it in Heym

A short walkthrough recorded in the product.

Browser Automation in Heym with Playwright — Building a Playwright automation from an empty canvas: open a page, scroll, screenshot, read page text, and extract live data, with AI steps that save themselves for later runs.

Where control lives

Code mode is disabled by default and always runs sandboxed, auth state is verified before steps execute, and every run keeps screenshots and captured network data for inspection.

Browser automations that survive UI changes and expired sessions instead of failing quietly.

Built with these Heym capabilities

Playwright steps and code mode

AI steps with auto heal

Cookie and storage state auth

Login fallback steps

Screenshots and network capture

Hardened sandbox execution

Cron scheduling

Slack and email alerts

Common applications

Portal data extraction behind loginScheduled visual checks with screenshotsForm filling and submission flowsPrice and availability monitoringLegacy app automation without APIsSession reuse with saved cookies

Deployment and integration

Self-host with Docker or Kubernetes, keeping data on your infrastructure.
Connect your own model providers: OpenAI, Ollama, vLLM, and more.
Integrate over HTTP, webhooks, Slack, email, and MCP tools.
Expose finished workflows as APIs, portals, or MCP servers.

Have a process that fits this pattern?

Show us the workflow, data sources, tools, and human decisions involved. We will help map it to Heym.

Discuss your use case Explore workflow templates