Future AGI: The Open-Source Platform for Reliable AI Agents
Future AGI is an open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Learn about its tracing, evals, simulations, and guardrails.
🚀 Want to deploy Future AGI yourself?
Docker configs, system requirements, and installation guides — all on one page.
View Future AGI Tool Page →AI agents are transforming how we build software, but they come with a fundamental challenge: reliability. Agents hallucinate, make unexpected decisions, and behave differently in production than in development. Future AGI is an open-source platform built to solve this problem — giving you a unified toolkit to evaluate, observe, and improve your AI agents at every stage of development.
What is Future AGI?
Future AGI is an end-to-end platform that combines five critical capabilities into one self-hostable system:
- Tracing & Observability — Capture every LLM call, tool invocation, and agent decision with full context. See exactly what your agent was thinking at every step.
- Evaluations — Define custom eval suites for your agents. Run them during development, staging, and production to catch regressions before they affect users.
- Simulations — Test your agents against realistic scenarios without live data. Simulate edge cases, adversarial inputs, and unexpected user behavior.
- Datasets — Curate and version your evaluation datasets. Share them across your team and track performance over time.
- Gateway & Guardrails — Route LLM requests through a unified gateway with built-in safety guardrails. Control costs, rate limits, and content safety policies.
Why Self-Host Future AGI?
Running Future AGI on your own infrastructure gives you complete control over your data. No telemetry leaks, no third-party API dependencies, and no usage limits. All agent traces, evaluation results, and datasets stay within your infrastructure.
The platform is fully Docker-based, making deployment straightforward on any Linux server. With the Docker Compose configuration provided on our tool page, you can be up and running in minutes.
Key Features at a Glance
| 🔍 Tracing | Full LLM call tracing with span-based visualization |
| 📊 Evals | Custom evaluation suites with pass/fail scoring |
| 🎮 Simulations | Realistic scenario testing without production data |
| 📁 Datasets | Versioned datasets for reproducible evaluations |
| 🛡️ Guardrails | Built-in safety policies and content filtering |
| 🚪 Gateway | Unified API gateway with cost control |
Getting Started
Future AGI is licensed under Apache 2.0 and has over 1,500 GitHub stars. The community is active on Discord, and documentation is available at docs.futureagi.com.
To deploy, you'll need a server with at least 2 CPU cores and 4 GB RAM (4 cores / 8 GB recommended for production use).
🚀 Ready to make your AI agents reliable?
Get the Docker Compose file, system requirements, and installation guide.
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