Each agent is delivered as transparent, documented Python code, ready to modify and extend.
You can connect new APIs, plug in local models, or fine-tune behaviors — without touching a proprietary editor or platform.
Every component follows LangChain’s open architecture: tools, chains, memory, and logic are easy to edit or expand.
Start from a clean foundation that works out of the box, and evolve it as your project grows.
Agents are optimized for speed, reliability, and autonomy.
They can chain multiple tasks, reason with structured or unstructured data, and execute complex workflows — locally or in Docker.
Run everything on-premise or on your own cloud.
No third-party API calls, no telemetry, no data leaving your environment.
Choose from a growing library of ready-to-run AI agents for research, content, and automation.
Skip the blank page. Each agent is a working Python project that you can run, inspect, and extend right away.
They already include reasoning loops, structured memory, and tool integrations — so you can focus on your logic, not boilerplate setup.
Agents are designed as interlocking modules: reasoning, planning, search, and task execution can be rearranged or expanded. Use one as your base, merge several, or inject your own datasets and models.
Each agent speaks standard Python — ready for Docker, FastAPI, or your own CLI.
They plug into databases, APIs, and third-party systems without friction.
You decide where they live: laptop, private cloud, or production server.
Full Python source code — editable, documented, production-ready
LangChain-based architecture — modular and future-proof
Quickstart examples — to test, tweak, and deploy instantly
Perpetual license — use locally, privately, without API dependencies
Every agent ships with code, configuration, and examples to help you launch in minutes and scale when you’re ready.
