⚠️ Nightly release for early testing. Expect rough edges. Stable version coming out soon — please open an issue if you hit anything.
# AI Agents hallucinate. Fix it faster.
**The open-source platform for shipping self-improving AI agents.** Evaluations, tracing, simulations, guardrails, gateway, optimization. Everything runs on one platform and one feedback loop, from first prototype to live deployment.
Try Cloud (Free) · Self-Host · Docs · Blog · Discord · Discussions
Why Future AGI?
Most AI agents fail in production, and teams end up stitching together evals, observability, and guardrails that never close the loop. Future AGI collapses all of it into one platform and one feedback loop. Simulate edge cases before launch, evaluate what happens in production, protect users in real time, and turn every trace into signal for the next version. The result: agents that don't just get monitored, they self-improve.
| ### All-in-one No more stitching Langfuse + Braintrust + Helicone + Guardrails AI + a custom simulator. One platform covers the lifecycle: **simulate → evaluate → protect → monitor → optimize**, with data flowing back as a loop. | ### Open & self-hostable Apache 2.0 core. Every evaluator, every prompt, every trace is inspectable — **no black-box scoring**. Self-host for data sovereignty or use our managed Cloud. Drop in your own stack at any layer via OTel / OpenAI-compatible HTTP. | ### Built for production Go-based gateway with **~9.9 ns weighted routing**, **~29 k req/s on t3.xlarge**, **P99 ≤ 21 ms with guardrails on**. OpenTelemetry-native traces. 50+ framework instrumentors. Every claim reproducible via the committed benchmark harness. |
🚀 Quickstart (60 seconds)
Two ways, depending on how much you want to install:
The self-host path requires Docker Desktop or Docker Engine with Docker Compose available before running the installer.
| Cloud (fastest) | Self-host (Docker) |
|---|---|
**No install. Free tier.**
SOC 2 Type II · HIPAA · data stays in your region.
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**One command, full stack. Published images, no source build.**
Open [http://localhost:3000](http://localhost:3000).
For production, use `./deploy/setup.sh` to generate required secrets and pin the image version.
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Instrument your first agent
**Python**
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**TypeScript**
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Full docs → · Cookbooks → · API reference →
Core features
Six pillars. Each one replaces a tool you probably have.
| ### 🧪 Simulate Thousands of multi-turn conversations against realistic personas, adversarial inputs, and edge cases. Text **and voice** (LiveKit, VAPI, Retell, Pipecat). [Docs →](https://docs.futureagi.com/docs/simulation) | ### 📊 Evaluate 50+ metrics under one `evaluate()` call: groundedness, hallucination, tool-use correctness, PII, tone, custom rubrics. **LLM-as-judge + heuristic + ML.** [Docs →](https://docs.futureagi.com/docs/evaluation) | ### 🛡️ Protect 18 built-in scanners (PII, jailbreak, injection, …) + 15 vendor adapters (Lakera, Presidio, Llama Guard, …). Inline in gateway or standalone SDK. [Docs →](https://docs.futureagi.com/docs/protect) |
| ### 👁️ Monitor OpenTelemetry-native tracing across 50+ frameworks (LangChain, LlamaIndex, CrewAI, DSPy…). Span graphs, latency, token cost, live dashboards. Zero-config. [Docs →](https://docs.futureagi.com/docs/observe) | ### 🎛️ Agent Command Center OpenAI-compatible gateway. 100+ providers, 15 routing strategies, semantic caching, virtual keys, MCP, A2A. **~29k req/s, P99 ≤ 21ms with guardrails on.** [Docs →](https://docs.futureagi.com/docs/command-center) · [Benchmarks →](./agentcc-gateway/README.md#-benchmarks) | ### 🔁 Optimize Six prompt-optimization algorithms (GEPA, PromptWizard, ProTeGi, Bayesian, Meta-Prompt, Random). Production traces feed back as training data. [Docs →](https://docs.futureagi.com/docs/optimization) |
Deployment options
| Target | Status | Notes |
|---|---|---|
| Docker Compose | ✅ | Published images with docker compose up -d from a fresh clone |
| Production Compose overlay | ✅ | ./deploy/setup.sh generates secrets, pins image tags, pulls images, and starts the stack |
| Kubernetes / Helm | ⏳ | Official manifests and Helm charts are coming soon |
| AWS / GCP / Azure | ✅ | Run Docker Compose on a VM today; managed Kubernetes support is coming soon |
| AWS Marketplace | ⏳ | Coming soon |
| Air-gapped / on-prem | ✅ | No phone-home — contact sales |
Architecture
Every arrow is an open, documented interface: OpenTelemetry OTLP for traces, OpenAI-compatible HTTP for the gateway, Postgres / ClickHouse SQL for storage. Drop in your own stack at any layer.
Runtime: Python 3.11+ (Django 5.1 + Channels) · Go 1.23+ (gateway) · React 18 + Vite · Node 20+. Data: PostgreSQL (metadata) · ClickHouse (spans + time-series) · Redis (state) · RabbitMQ + Temporal (jobs).
Component breakdown (per-package) | Layer | Component | Code | |---|---|---| | Edge | **traceAI** — OpenTelemetry instrumentation | [`future-agi/traceAI`](https://github.com/future-agi/traceAI) | | Edge | **Agent Command Center** — OpenAI-compatible proxy | [`agentcc-gateway/`](./agentcc-gateway) | | Platform | **tracer** — OTLP ingest, span graph | [`futureagi/tracer/`](./futureagi/tracer) | | Platform | **agentic_eval** — 50+ metrics, LLM-as-judge | [`futureagi/agentic_eval/`](./futureagi/agentic_eval) | | Platform | **simulate** — persona-driven scenario generation | [`futureagi/simulate/`](./futureagi/simulate) | | Platform | **model_hub** — LLM routing, embeddings, datasets | [`futureagi/model_hub/`](./futureagi/model_hub) | | Platform | **accounts · usage · integrations** — auth, orgs, metering, connectors | [`futureagi/accounts/`](./futureagi/accounts) | | Data | **PostgreSQL** · **ClickHouse** · **Redis** · **RabbitMQ + Temporal** | — |SDKs & integrations
Future AGI is an open-source ecosystem — each SDK is independently usable, independently packaged, Apache/MIT-licensed.
Client libraries
| Repo | Install | Languages | Purpose |
|---|---|---|---|
| traceAI | pip install fi-instrumentation-otelnpm i @traceai/fi-core |
Python · TS · Java · C# | Zero-config OTel tracing for 50+ AI frameworks |
| ai-evaluation | pip install ai-evaluationnpm i @future-agi/ai-evaluation |
Python · TS | 50+ evaluation metrics + guardrail scanners |
| futureagi | pip install futureagi |
Python | Platform SDK — datasets, prompts, KB, experiments |
| agent-opt | pip install agent-opt |
Python | 6 prompt-optimization algorithms (GEPA, PromptWizard, …) |
| simulate-sdk | pip install agent-simulate |
Python | Voice-agent simulation via LiveKit + Silero VAD |
| agentcc | pip install agentccnpm i @agentcc/client |
Python · TS (+ LangChain · LlamaIndex · React · Vercel) | Gateway client SDKs |
Integrations
| LLM providers (100+) | OpenAI · Anthropic · Google Gemini · Vertex AI · AWS Bedrock · Azure OpenAI · Mistral · Groq · Cohere · Together · Perplexity · OpenRouter · Fireworks · xAI · Replicate · HuggingFace · + self-hosted Ollama · vLLM · LM Studio · TGI · Llamafile |
| Agent frameworks | LangChain · LangGraph · LlamaIndex · CrewAI · AutoGen · Phidata · PydanticAI · Claude SDK · LiteLLM · Haystack · DSPy · Instructor · Smol-agents |
| Voice platforms | VAPI · Retell · LiveKit · Pipecat |
| Vector DBs | Pinecone · Weaviate · Chroma · Milvus · Qdrant · pgvector |
| Tools & infra | Vercel AI SDK · n8n · MongoDB · MCP · A2A · Guardrails AI · Langfuse · HuggingFace Smol-agents |
How Future AGI compares
| Future AGI | Langfuse | Phoenix | Braintrust | Helicone | |
|---|---|---|---|---|---|
| Open source | ✅ Apache 2.0 | ✅ MIT | ✅ Elastic v2 | ❌ | ✅ Apache 2.0 |
| Self-host | ✅ | ✅ | ✅ | ❌ | ✅ |
| LLM tracing (OpenTelemetry) | ✅ | ✅ | ✅ | ✅ | ⚠️ via OpenLLMetry |
| Evaluation suites | ✅ 50+ metrics | ✅ | ✅ | ✅ | ⚠️ Limited |
| Agent simulation | ✅ | ❌ | ❌ | ❌ | ❌ |
| Voice agent eval | ✅ | ❌ | ⚠️ Cookbook | ❌ | ❌ |
| LLM gateway built in | ✅ 100+ providers | ❌ | ❌ | ✅ | ✅ |
| Guardrails built in | ✅ 18 + 15 adapters | ❌ | ❌ | ❌ | ❌ |
| Prompt optimization | ✅ 6 algorithms | ❌ | ❌ | ❌ | ❌ |
| Prompt management | ✅ | ✅ | ✅ | ✅ | ✅ |
| Datasets & experiments | ✅ | ✅ | ✅ | ✅ | ✅ |
| No-code eval builder | ✅ | ⚠️ | ⚠️ | ⚠️ | ⚠️ |
Based on publicly-documented features as of April 2026. Corrections welcome — open a PR.
Built for every kind of agent
- Customer Support: Ship support AI that customers actually trust
- Voice Agents: Test, evaluate, and improve voice AI end-to-end
- Internal Tools: AI copilots your whole org can rely on
- RAG & Search: Every answer grounded, every citation verified
- Autonomous Agents: Multi-step agents you can actually trust in production
- Computer-Use Agents (CUA): Agents that click with confidence
- Coding Agents: AI that writes code you can actually ship
Roadmap
Vote on the public roadmap → · GitHub Discussions · Releases · Changelog
| Recently shipped | In progress | Coming up | Exploring |
|---|---|---|---|
| - [x] Prompt optimization engine - [x] Taxonomy-based Feed Clustering - [x] Agent Runs in Dataset Experiments - [x] Simulate from Production Calls - [x] LiveKit Configuration via UI - [x] System Metric Filtering for Voice - [x] Agent Playground - [x] Dashboards - [x] Access platform via MCP - [x] Annotation Queues - [x] Command Center - [x] Open source Future AGI stack - [x] Eval Explanation Output Size Control | - [ ] Agent Changelog & Diff View - [ ] Smart Queue Assignment - [ ] Essential Node Library for Agent Builder - [ ] Full Execution Tracing for Agents - [ ] Multi-modal Support for Agents | - [ ] Agent Changelog & Diff View - [ ] Smart Queue Assignment | - [ ] Import agents to Agent Playground - [ ] Simulating CUA agents - [ ] Simulating Coding agents - [ ] Scheduled Simulations |
🤝 Contributing
We love contributions — bug fixes, new evaluators, framework integrations, docs, examples, anything.
- Browse
good first issue - Read the Contributing Guide
- Say hi on Discord or Discussions
- Sign the CLA on your first PR (automatic bot)
🌍 Community & support
| 💬 Discord | Real-time help from the team and community |
| 🗨️ GitHub Discussions | Ideas, questions, roadmap input |
| 🐦 Twitter / X | Release announcements |
| 📝 Blog | Engineering & research posts |
| 📺 YouTube | Walkthroughs & demos |
| 📊 Status | Cloud uptime + incident history |
| 📧 [email protected] | Cloud account / billing |
| 🔐 [email protected] | Private vulnerability disclosure (24h ack — see SECURITY.md) |
Telemetry
Self-hosted Future AGI collects deployment telemetry to help us size release testing and understand feature adoption. No trace data, no prompts, no API keys, ever.
What is collected: - Registration (once, on first boot): instance ID, version, deployment type, and the email addresses and domains of active admin users. - Heartbeat (periodic): anonymous aggregate usage counts.
Set FUTURE_AGI_TELEMETRY_DISABLED=1 in .env (or deploy/.env.production for the production overlay) to opt out. When disabled the instance still sends a single minimal census ping — instance ID, version, deployment type, no emails — once after the first start, and no heartbeats. The ping lets us count how many self-hosted installs are out there; turn networking off at the edge if you need full silence.
⭐ Star history
📄 License
Future AGI is licensed under the Apache License 2.0. See LICENSE and NOTICE.
You own your evaluation logic and your data. Inspect every evaluator, every prompt, every trace — no black-box scoring, no vendor lock-in.