Web scraping and web security are changing fast. Traditional scrapers break whenever websites update their layout, and traditional security tools completely miss zero-day threats and hidden prompt injections targeting autonomous AI agents.
To solve this, we built OpticParse & PhishVision — a decentralized, edge-native computer vision scraper and real-time cybersecurity refinery. Running across a distributed network in 8 global continents, the system continuously extracts web data using vision AI, maps global retail trends, and detects emerging phishing sites and adversarial prompts before they appear on public blacklists.
Over the past week alone, the network processed 497,000+ edge requests with a 99.9% uptime, while our open-source developer toolkits have crossed 2,600+ installations across PyPI and NPM.
Whether you're building autonomous browser agents (LangChain, CrewAI, AutoGPT), training LLMs on structured web data, or looking for real-time threat intelligence, you can test our live API, explore our open datasets on Hugging Face, or integrate directly with our Python SDK:
- 🌐 Live Platform & API Docs: opticparse.com
- 🐙 Open-Source GitHub: github.com/parastejpal987-cmyk/opticparse-public
- 🤗 Hugging Face Datasets: huggingface.co/paras9909
- 📦 PyPI:
pip install langchain-opticparse opticparse-py
We'd love to hear your feedback! How is your team currently handling AI web navigation and adversarial prompt defenses?
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