Future AGI
Open-source agent operations, security, and governance for agent evaluation, guardrails, observability.
What does this agent do, and when should you use it?
The repository describes Future AGI as: 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. This profile is a source-based catalog entry; an independent FARS review is still pending.
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.
- Evaluate controls for operating or governing agent workloads.
- Test observability, security, or deployment behavior in a sandbox.
- Integrate documented controls into an existing operations stack.
What are this agent's strengths and limitations?
- Public source and README are available for inspection.
- Focused on agent evaluation, guardrails, observability.
- Setup, model-provider support, and maturity must be confirmed against the current release.
- No independent FARS score has been assigned yet.
How do you install or deploy this agent?
Follow the current installation instructions in the [repository README](https://github.com/future-agi/future-agi#readme). Requirements and provider setup vary by release.
How do you use this agent?
Start with the examples and quickstart in the [repository documentation](https://github.com/future-agi/future-agi#readme), then test the workflow with limited permissions and non-sensitive data.