future-agi/future-agi

Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.

What it solves

Most AI agents fail in production because teams use fragmented tools for evaluation, observability, and guardrails. Future AGI provides a unified platform that closes the feedback loop between simulation, evaluation, protection, and monitoring to help agents self-improve and become reliable for production use.

How it works

It operates as an all-in-one platform consisting of an OpenAI-compatible gateway and an OpenTelemetry-native tracing system. The system allows developers to simulate edge cases using realistic personas, evaluate performance using over 50 metrics (including LLM-as-judge), protect users with built-in guardrail scanners, and optimize prompts using six different algorithms. Production traces are then fed back into the system as training data for the next version of the agent.

Who it’s for

Developers and teams building AI agents for customer support, voice AI, RAG systems, autonomous agents, computer-use agents (CUA), and coding assistants who need a production-ready reliability layer.

Highlights

  • Unified Lifecycle: Covers the entire process from simulation and evaluation to protection, monitoring, and optimization in one platform.
  • High-Performance Gateway: A Go-based gateway supporting 100+ providers with low latency (P99 ≤ 21ms with guardrails active).
  • Extensive Evaluation: Includes 50+ metrics for groundedness, hallucination, and tool-use correctness.
  • Open & Self-Hostable: Apache 2.0 licensed core that can be self-hosted via Docker for data sovereignty.
  • Broad Integration: Native support for 50+ AI frameworks including LangChain, LlamaIndex, and CrewAI.

Related

  • Project
    vstorm-co/full-stack-ai-agent-template

    A production-ready project generator that scaffolds full-stack AI agent applications using FastAPI and Next.js, featuring built-in RAG, authentication, and enterprise integrations.

  • Project
    devchilll/scope

    A production-ready governance framework for enterprise AI agents that implements safety guardrails, compliance-as-code, IAM, and human-in-the-loop escalation.

  • Project
    Kritt-ai/open-kritt

    An open-source security research platform that orchestrates AI agents to find, validate, and rank vulnerabilities in code through focused, parallelized workflows.

  • Project
    ServiceNow/AgentLab

    A framework for developing and evaluating web agents across various benchmarks, featuring large-scale parallel experimentation and trace visualization tools.

  • Project
    langwatch/langwatch

    An open-source platform for AI production that allows companies to trace, test, route, and govern all LLM calls and coding agents.