# Precogs AI Documentation
# https://docs.precogs.ai
# Contact: support@precogs.org

## About Precogs AI
Precogs AI is an AI-native security platform for code, binaries, and data.
We provide context-aware vulnerability detection that reduces false positives by 80%.

## Key Concepts

### Security Analysis Types
- SAST: Static Application Security Testing - analyzing source code without execution
- SCA: Software Composition Analysis - scanning dependencies for known CVEs
- DAST: Dynamic Application Security Testing - runtime vulnerability detection
- SBOM: Software Bill of Materials - machine-readable component inventory

### AI & LLM Terms
- MCP: Model Context Protocol - standard for AI agents to interact with external tools
- LLM Guardrails: Security controls preventing AI models from leaking secrets or PII
- Context-aware AI: Security scanning that understands code semantics, not just patterns
- AI-native: Built with AI at the core, not bolted on as an afterthought

## Products

### Developer Tools
- GitHub App: Automated PR security scanning with inline comments
- GitLab App: CI/CD security integration for merge requests
- Python SDK: Programmatic access to Precogs scanning APIs
- CLI: Local command-line scanning tool
- MCP Server: AI agent security interface for autonomous coding assistants

### Portal
- Dashboard: Central hub for viewing findings and trends
- Codebase Scans: Deep static analysis results and remediation guidance

## Use Cases
- Secure AI-assisted development workflows
- Pre-commit security scanning
- CI/CD pipeline integration
- Enterprise code security at scale
- SBOM generation for compliance

## Supported Languages
Python, JavaScript, TypeScript, Go, Java, C, C++, Rust, Ruby, PHP

## Links
- Documentation: https://docs.precogs.ai
- Website: https://www.precogs.ai
- GitHub: https://github.com/precogsai