# Future AGI Open-source platform for evaluating, observing, and improving LLM and AI agent applications. ## Agent Decision Summary - Risk level: low - Source confidence: high - Recommended workflows: Browser automation, Evaluation and observability, Reusable skill workflow - Permission surface: low explicit permission surface in metadata - Agent JSON: https://www.openagent.bot/tools/future-agi.agent.json ## Summary Future AGI is an open-source platform for evaluating, observing, and improving LLM and AI agent applications. It covers tracing, evals, simulations, datasets, gateway workflows, guardrails, and self-hostable deployment. ## Guide Future AGI is an open-source platform for evaluating, observing, and improving LLM and agent applications. ### What it is It combines traces, evals, simulations, datasets, gateway workflows, and guardrails in a self-hostable platform. ### Why it matters Agent quality needs structured measurement and operations loops before workflows reach real users. ### How it works Instrument one agent path, add evaluation datasets, and use traces and guardrails to inspect regressions. ### FAQ - Is Future AGI open source? - Yes. The GitHub repository is listed under the Apache-2.0 license. - Who should evaluate Future AGI? - Teams shipping production LLM or agent applications should evaluate it as an evaluation and observability layer. ## What It Does It combines traces, evals, simulations, datasets, gateway workflows, and guardrails in a self-hostable platform. ## How To Evaluate Instrument one agent path, add evaluation datasets, and use traces and guardrails to inspect regressions. ## Why It Matters Agent teams need more than traces or one-off eval scripts. Future AGI is interesting because it combines evaluation, observability, simulation, datasets, gateway, and guardrails in one platform. ## Best For - Teams operating LLM and agent applications - Builders comparing self-hostable evaluation and observability platforms - AI teams that need simulations, datasets, and guardrails together ## Not For - Small prototypes that only need a few manual test prompts - Teams looking for a low-level agent framework rather than an operations platform ## What It Actually Does - Evaluation and observability together: Future AGI combines tracing, evals, datasets, simulations, gateway, and guardrails. - Why it matters: Production agent quality depends on multiple feedback loops, not just a dashboard. - Self-hostable platform: The project describes itself as self-hostable. - Why it matters: Teams with sensitive agent data often need control over telemetry and evaluation datasets. - Agent application focus: Future AGI is explicitly aimed at LLM and AI agent applications. - Why it matters: Agent systems need tool, trace, and workflow-level evaluation beyond plain chat completion metrics. ## Typical Use Cases - Agent regression testing: Track whether agent changes improve or degrade task performance. - Simulation workflows: Use simulations and datasets to test agent behavior before production traffic. - Guardrail monitoring: Pair traces with guardrails around risky model or tool behavior. ## How It Compares - When to choose Future AGI: Compare it with nearby tools by looking at hosting model, integration surface, license, and whether the official docs show the workflow you need. ## Fit Matrix - Browser automation: strong. Future AGI has multiple signals for browser automation, including matching tags, capabilities, category, or positioning. Required check: Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs. - Evaluation and observability: strong. Future AGI has multiple signals for evaluation and observability, including matching tags, capabilities, category, or positioning. Required check: Add one repeatable test case and confirm results can run again in review or CI. - Reusable skill workflow: strong. Future AGI has multiple signals for reusable skill workflow, including matching tags, capabilities, category, or positioning. Required check: Run one skill end to end and check whether it produces evidence or structured output. - Coding agent workflow: partial. Future AGI has at least one signal for coding agent workflow, but should be checked against a real task before adoption. Required check: Run a small repository change and inspect the diff, tests, and rollback path. - Local or private AI stack: partial. Future AGI has at least one signal for local or private ai stack, but should be checked against a real task before adoption. Required check: Verify hardware requirements, data path, storage, and whether all calls stay in your environment. - Robotics or embodied agent workflow: partial. Future AGI has at least one signal for robotics or embodied agent workflow, but should be checked against a real task before adoption. Required check: Separate simulator claims from hardware claims and verify safety boundaries before real-world operation. ## Evidence - verified: Future AGI is listed as open source. Source: License metadata: Apache-2.0 - verified: Future AGI has a recorded GitHub repository: future-agi/future-agi. Source: Resource facts and GitHub source link. - inferred: Future AGI supports these recorded deployment modes: self hosted, cloud. Source: OpenAgent decision signal metadata. - inferred: Future AGI is tagged with automation, workflow capabilities. Source: OpenAgent capability taxonomy. ## Missing Checks - Dedicated docs link is missing. - Repository freshness has not been recorded. ## Next Actions - Inspect repository: https://github.com/future-agi/future-agi - Open Homepage: https://futureagi.com ## Facts - Category: tools - Resource type: tool - Open source: yes - License: Apache-2.0 - Last verified: 2026-06-11 - GitHub repo: future-agi/future-agi - GitHub stars: 1127 ## Capabilities - automation - workflow ## Structured Use Case Tags - self-hosted-ai ## Getting Started - Open the GitHub repository: https://github.com/future-agi/future-agi - Visit the project website: https://futureagi.com ## Links - GitHub: https://github.com/future-agi/future-agi - Homepage: https://futureagi.com ## Structured Outputs - JSON: https://www.openagent.bot/tools/future-agi.json - Markdown: https://www.openagent.bot/tools/future-agi.md - Agent JSON: https://www.openagent.bot/tools/future-agi.agent.json - Canonical: https://www.openagent.bot/tools/future-agi