
A production-grade multi-agent framework for autonomous data extraction. Works with small language models through Tree of Thought reasoning.
Build production-grade autonomous web scrapers that actually work.
Multi-path exploration enables smaller models to perform complex reasoning through systematic evaluation and backtracking.
Combines screenshot analysis with DOM understanding for superior page comprehension, not just HTML parsing.
Observes failures and adapts strategies in real-time. 90%+ self-recovery rate on complex tasks.
Automatically generates reusable Playwright extraction patterns from successful explorations.
Builds a persistent knowledge graph of learned approaches for zero-shot generalization.
No hardcoded selectors or site-specific logic. Pure autonomous exploration and discovery.
Six specialized agents working in harmony through a state machine orchestrator.
Vision + DOM Analysis
ToT Strategy
Playwright Actions
Quality Assurance
Data Extraction
Template Generation
Benchmarked with Llama 3.1 8B on complex extraction tasks.
vs 5% hardcoded
Production-grade
Auto-healing
New sites
| Feature | CogNexus | Traditional | LLM-only |
|---|---|---|---|
| Works with SLMs | ✓ ToT amplifies | N/A | ✗ Need GPT-4 |
| Generalizable | ✓ Discovery-driven | ✗ Hardcoded | ⚠ Prompt-dependent |
| Self-correcting | ✓ Observes & adapts | ✗ Fails silently | ⚠ Limited |
| Template generation | ✓ Auto Playwright | N/A | ✗ No |
CogNexus uses Tree of Thought reasoning to generate multiple extraction strategies, evaluate each approach, and pick the best one.
Leave blank to extract everything, or describe what you're searching for to get a personalized extraction.
Generates multiple strategies, evaluates each, picks the best.
Checks SSL, headers, broken links, mixed content, and exposed secrets.
Generates charts from extracted data using Matplotlib.

Start extracting data autonomously in minutes.
pip install cognexus-extractor