AI Stack
103+ open-source AI frameworks wired into BrainAi's brain.
Every AI framework that makes BrainAi smart.
Agents, memory, RAG, browser automation, voice, vision, MCP, and local LLMs — hand-picked, categorized, and mapped to the BrainAi surfaces they power.
How BrainAi uses these tools
Tiers 3–5 grounded synthesis, agentic multi-hop.
AI picks the engine, extracts structured JSON from any page.
Persistent user + project context across sessions.
Query everything BrainAi has ever collected.
OSINT crews of specialist agents (recon, correlate, report).
PDFs, invoices, and reports → clean structured data.
Talk to BrainAi; it talks back.
Expose BrainAi to Claude/ChatGPT, and consume other MCP servers.
Run entirely on your machine, no cloud calls.
Chain scrape → extract → enrich → notify.
Recommended smart stack
🤖AI Agent Frameworks
Orchestrate autonomous LLM agents and tool loops.
🧠Memory & Vector DB
Persistent memory and vector stores for agents.
📚RAG (Retrieval-Augmented Generation)
Frameworks for grounding LLMs in your data.
🌐Browser Automation & Web Agents
Agents that click, type, and navigate the web.
🔄Workflow Automation
Visual pipelines, cron, and node-graph orchestration.
💻Coding Agents
AI pair programmers and dev agents.
🗣️Voice AI
Realtime speech, STT and TTS pipelines.
👁️Vision AI
Image gen, detection, segmentation, grounding.
🤝Multi-Agent Systems
Frameworks for cooperating agent societies.
🧩MCP (Model Context Protocol)
The emerging standard for tool interop.
🌍Local AI
Run models on your own hardware.
📄Document & PDF Intelligence
Parse, OCR, and structure documents for RAG.
🔍Search & Research
Web extraction and search APIs for agents.
🧠Reasoning & Inference
Serving runtimes and reasoning frameworks.
🏢Production AI Platforms
Batteries-included platforms to run AI in production.
🚀AI Projects to Learn From
Production-grade AI repos worth studying.