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Future AGI

Open-source platform for evaluating, tracing and improving AI agents.

Future AGI builds an open-source, self-hostable platform for shipping AI agents that covers the lifecycle in one feedback loop: simulations of edge cases before launch, evaluations, tracing and observability in production, real-time guardrails, an LLM gateway, datasets and optimization. It positions itself as a replacement for stitching together separate tools for evals, observability, guardrails and simulation. The platform is Apache 2.0 licensed, with a free cloud tier alongside self-hosting.

Featured

The de-facto standard toolkit for building LLM applications and agents.

LangChain makes the LangChain framework and LangGraph, the low-level orchestration standard for stateful, controllable agents, plus the LangSmith platform for tracing, evaluating and monitoring them in production.

~$75M raised

4 pros · 4 cons

Serverless cloud built for AI and agentic compute.

Modal lets teams run inference, fine-tuning and arbitrary agent workloads as serverless Python without managing infrastructure — a common substrate for harness backends at scale.

4 pros · 4 cons

Durable execution for long-running agent workflows.

Temporal's durable execution engine is widely adopted to make agent pipelines reliable: state survives crashes, retries are automatic, and workflows run for minutes or months. A key piece of serious harness infrastructure.

$430M total · $300M Series D (Feb 2026) at $5B valuation

3 pros · 4 cons

Connections

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Sources

  1. GitHub repository
  2. Future AGI website