Insights on AI agents, web automation, and building the perception layer for the next generation of AI applications.
Why logs and screenshots are not enough for AI agents — and how trace-based observability enables replay, determinism, and real debugging.
Vision models are good at seeing, but agents fail at acting. This post explains why vision-first web agents break down in practice, and how semantic geometry enables reliable execution.
How we solved the '4,500 elements problem' and saved customers thousands in token costs without sacrificing accuracy.
Building AI agents that can truly see and understand the web requires more than just scraping HTML. Learn how Sentience provides visual grounding for large action models.
Traditional headless browsers are slow and expensive. We built an adaptive hybrid architecture that delivers 10x faster performance at 90% lower cost.
Not all web automation tasks are created equal. Learn when to use our Performance Engine for speed and when to use Precision Engine for accuracy.
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