⚡ Codex

Multi-Source RAG System for AI Agents

Real intelligence for your agents. Wikipedia. Reddit. YouTube. Web.
Sourced. Cited. Self-healing. Production-ready.

Buy on Gumroad ($49.99) Learn More

Live Demo

Try a live lookup below. Real Wikipedia, Reddit, YouTube data—no hallucinations.

Key Features

🌐

Multi-Source Retrieval

Real-time data from Wikipedia, Reddit, YouTube, and the open web—all in one query.

📚

Vector Embeddings & RAG

ChromaDB for persistent knowledge. Semantic search that actually understands context.

✓

Citation Trails

Every fact linked back to its source. Full transparency. No BS.

🔧

Self-Correcting

Detects contradictions across sources and flags them automatically.

⚙️

REST API Ready

Simple `/lookup` endpoint. SDK examples for any language.

🚀

Production-Ready

Rate limiting, caching, error handling, health checks—not a demo.

Complete Setup Package

Choose your deployment path. Deploy in 5–10 minutes.

$49.99
  • Full source code (MIT license) — modify, deploy anywhere
  • Docker container — ready to go on any cloud
  • Setup guides for 5 paths — HF Spaces, Docker, local, Railway, Render
  • 1-year email support — deployment help, customization guidance
  • Free updates — bug fixes, new features, docs
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Deployment Paths

Pick what works best for you.

🤗 HuggingFace

5 min
FREE
Recommended

🐳 Docker

10 min
$0–$20/mo
Full control

💻 Local

3 min
FREE
Dev-only

🚂 Railway

8 min
FREE
Auto-deploy

📊 Render

8 min
FREE
Easiest

Why Codex?

Problem: AI agents hallucinate. Chatbots make up facts. Research tools lack citations.

Solution: Codex feeds real, sourced intelligence directly to your agent. Self-healing contradictions. Transparent citations. No BS.

Result: Agents your users actually trust. 🚀