TL;DR: StableBrowse is the browser layer for AI agents. We transform dynamic websites into structured knowledge graphs that capture how sites truly work, giving agents persistent memory to complete tasks reliably without starting from scratch every time.

Ask: If you’re building agents that browse the web, scrape data, fill forms, monitor prices, or work inside authenticated portals, we’d love to talk! Reach us at team@stablebrowse.ai or schedule a demo at stablebrowse.com.

https://youtu.be/ng_ZM1PCkv0?si=x4pVN9tEb5PNhfxv

Problem: AI agents are increasingly being used for real web workflows like tracking competitor pricing, applying for loans, updating CRM records, booking travel, submitting expense reports, and navigating legacy enterprise systems.

Most browser agents still treat every interaction like it’s the first time, repeatedly asking an LLM what to click next. This works in demos, but breaks in production because websites constantly change through:

• Pop-ups and modal interruptions
• Login and authentication flows
• Slow-loading dropdowns and forms
• Layout and UI updates
• Dynamic page behavior

As a result, agents become unreliable, expensive to run, and difficult to scale across real-world workflows.

Solution: StableBrowse gives AI agents persistent memory of how websites actually work by converting websites into structured execution graphs. Instead of rediscovering workflows every run, StableBrowse learns websites once and reuses that knowledge across future executions.

We convert pages into structured states, turn buttons and forms into reliable actions, extract clean structured data instead of raw HTML, and detect when websites change to keep workflows reliable over time.

At runtime, StableBrowse handles:

• Navigating known workflows
• Filling forms and completing submissions
• Extracting clean, structured data
• Handling date pickers and dropdowns
• Detecting when websites change
• Returning usable outputs instead of raw HTML

This allows the LLM to focus on user intent instead of fragile browser interactions. The results are dramatic: 70–80% lower token usage, 3–4× faster workflows, and up to 98% success rate.

Background: We started StableBrowse after running into these same frustrations ourselves while building browser agents. Our team brings experience from Amazon (agentic commerce), AWS EC2 Nitro, applied AI research, and multiple fast-growing startups.