The missing middleware that reduces AI agent errors by 80% and cuts LLM costs by 95%.
Current AI automation treats interfaces as pixel grids or DOM trees—meaningless noise. Agents hallucinate, click wrong buttons, and fail 60-80% of the time. The problem isn't LLM capability—it's UI legibility.
Paste any HTML. Watch Axillar map it to semantic layers.
This demo runs entirely in your browser. Paste HTML from any website—try right-clicking a web page, selecting "Inspect", then copying an element's HTML. Watch Axillar extract semantic layers in real-time.
Tip: Right-click any web page → Inspect → Copy element HTML
Try AWS Console, Salesforce, or any SaaS dashboard for best results
A protocol, not a product. Infrastructure, not an application.
Axillar sits between the DOM and AI agents, translating hostile UIs into clean semantic responsibility layers. Think of it as the Rosetta Stone for AI browser automation.
Contains: Global nav, breadcrumbs, mode filters
Contains: Main content, data objects, current task
Contains: Action buttons, contextual menus, tools panel
from axillar_parser import Axillar # Parse any HTML engine = Axillar(html_string) engine.auto_map() # Get semantic manifest manifest = engine.to_dict() # Get LLM-ready context context = engine.get_agent_context() # Agent now knows exactly what to do # No hallucination. No wrong clicks. Just works.
Open-source parser. Enterprise services. Exit-ready.
Built by a 20-year platform veteran who architected systems at Lowe's Innovation Labs. This isn't vapor—it's production-ready middleware with proven metrics.