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Future AGI

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Open-source platform for building reliable self-improving AI agents.

Autonomous AgentsGeneral-Purpose 1.1kOpen source
View on GitHub
Updated 2026-06-15
Future AGI GitHub repository

What is Future AGI?

Future AGI is an open-source platform designed to help developers create AI agents that improve automatically through continuous feedback. It brings together simulation, evaluation, monitoring, protection, and optimization so that data from each stage feeds directly into the next.

The system works by letting users simulate edge cases before launch, run evaluations on live traces, apply real-time guardrails, and use collected signals to refine agent behavior over time. OpenTelemetry support and framework instrumentors make it compatible with existing stacks while keeping all components inspectable.

It targets engineering teams and organizations shipping production AI agents who need data sovereignty, high throughput, and a single source of truth instead of managing multiple disconnected services.

What you can build with Future AGI

Pre-deployment Simulation

Run controlled tests on agents to identify failure modes before they reach users.

Live Trace Evaluation

Capture production interactions and score them to measure real-world reliability.

Runtime Guardrails

Apply protective checks during inference to reduce harmful or incorrect outputs.

Install Future AGI

Install
pip install ai-evaluation
Quick start
# Sign up free:
#   app.futureagi.com

pip install ai-evaluation
  1. 1Sign up at app.futureagi.com for the free cloud tier or prepare a Docker environment for self-hosting.
  2. 2Install the Python package with pip install ai-evaluation.
  3. 3Initialize a project and connect your agent code using the provided SDK or OpenTelemetry exporters.
  4. 4Define evaluations and guardrails in the dashboard or configuration files.
  5. 5Run your first simulation or deploy the agent and review the resulting traces and scores.

Future AGI: pros & cons

Pros

  • +Single integrated loop covering the full agent lifecycle
  • +Apache 2.0 license with full self-hosting option
  • +High-performance gateway suitable for production traffic
  • +Broad framework support via OpenTelemetry

Cons

  • Currently distributed as a nightly build with possible instability
  • Self-hosting requires managing your own infrastructure
  • Advanced features may still be under active development
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Frequently asked questions

Yes, the managed cloud tier requires only a free registration and the Python client package.

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