The production framework

Agents don't die
in the demo.
They die in production.

CrewAI and LangGraph frame how your agent thinks. agentFast frames everything above that — durable execution that survives a crash mid-task, a human approval gate before it moves real money, memory, guardrails, evals, native multi-agent teams, and a live trace of every decision it made. Agnostic to the SDK underneath. Self-hosted, in your cloud.

Solo $89 · Team $199Runs in your infrastructureSource-available. Own it forever.
agentfast — support-agent — productionlive
$

↑ real flow: answer → escalate → pause → crash resume

Model-neutral · self-hostable · works with your stack
LangGraphCrewAIVanillaOpenAIAnthropicGeminiOllamaGroqMCPpgvectorPostgresRedisOTELLangSmithDockerLangGraphCrewAIVanillaOpenAIAnthropicGeminiOllamaGroqMCPpgvectorPostgresRedisOTELLangSmithDocker
01 — The problem

Everyone can build an agent now. Almost nobody can keep one alive.

The demo is the easy part. You know the feeling — it works beautifully on your laptop, you show it to someone, and it's magic. Then it meets the real world. The process restarts mid-task and the run is simply gone. It refunds the same customer twice because nothing was watching. It answers confidently with something it invented, and nobody notices for three weeks.

None of that is a model problem. It's missing infrastructure — the unglamorous layer between something that demos well and something you'd let near a customer.

88%
of AI agents never reach production
11%
of enterprises have agents actually running
47% → 9%
rollback rate, without evals vs with
02 — The stack

Seven layers you were going to build anyway. Already built.

LangGraph and CrewAI solved orchestration. Orchestration was never the hard part. Everything below is what stands between your agent and a customer — and none of it is what makes your product yours. It's SDK-agnostic, so you keep writing real LangGraph or real CrewAI and this sits underneath.

memory01

Memory that ships

Short-term buffer, long-term vector recall (pgvector), and an episodic event log. Wired in, not a TODO.

tools02

50 tools, MCP-native

Search, files, DB, email, Slack, tickets, code, git. Every tool is an MCP server. Add your own in one line.

observability03

Observability built in

Every run traced: step tree, token cost, latency. Export to OTEL or LangSmith. The dashboard you'd have built anyway.

guardrails04

Guardrails, not vibes

PII redaction in and out, safety filters, rate limits, and retrieval-grounded hallucination scoring on answers.

human-in-the-loop05

Human-in-the-loop

Risky tool calls pause for approval — and survive a process restart. Resume from the exact step. This is the hard part. It's done.

evals06

Evals in CI

Test cases scoring accuracy, hallucination, and tool-use correctness. Runs in your pipeline. Ship without breaking.

teams07

Native multi-agent teams

Fan a broad question out to sub-agents, each its own context window and budget. Every child's real cost rolls up into one number on the parent.

03 — The moment

Watch it survive a crash.

Most agent stacks are a chat wrapper with a system prompt — fine until something real happens. Here's the difference: a customer asks for a refund. The agent doesn't just fire it — it pauses for a human. Then we kill the process mid-approval. Restart it. The paused run is still there. Approve it, and the agent resumes from the exact step and finishes the job.

pause
It pauses

refund_request() is high-risk. The run stops and waits for a human decision.

crash
You kill it

Process dies mid-approval. State is checkpointed to Postgres, not lost in memory.

resume
It resumes

Restart, approve — the run continues from the exact step. No replay, no double-charge.

That's durable execution. That's the line between a toy and something you'd put in front of a paying client.

04 — Who it's for
highest LTV

Agencies & dev shops

Clone it once, ship agents to ten clients. White-label it. HITL keeps you safe on high-stakes actions. Bill for outcomes, not plumbing.

budget exists

Internal AI teams

Give your product teams a blessed, observable, safe base instead of ten snowflake agents nobody can debug.

move fast

Indie founders

You're the domain expert. Ship your vertical agent without becoming a LangGraph engineer first.

05 — What's in v1

Six SDKs. Fifty tools. Three working agents.

How it ships

It's being built in public — right now. The plan lands in the open, piece by piece: core production layer + LangGraph + SupportAgent first, then the other SDKs, then Research & Code agents. You watch every step, and you get the full source the moment it's tested and ready. No big-bang, no vaporware, no half-tested skeleton.

SDKs
LangGraph · CrewAI · Claude Agent SDK · OpenAI Agents SDK · Vanilla · Team

Switch via config. Real, idiomatic code in each — never a lowest-common-denominator wrapper. Team is agentFast's own native multi-agent orchestrator.

Templates
Support · Research · Code

Three working agents you can clone: KB support, cited research reports (single-agent or fanned out to a multi-agent team), and repo-fixing PRs.

Tools
50 · MCP-native

Grouped by agent. One wrapper pattern, one test harness — add your own in a line.

Deploy
docker compose up

Full stack locally in one command; one-command deploy to the cloud.

DX
Playground · Dashboard · CLI

Test prompts/tools/memory before you code. Observe every run. Scaffold with agentfast new.

Docs
Docs site · 2-hr course

Runnable examples and a full video course from setup to first deploy.

06 — Pricing

One price. Own it forever.

Source-available and self-hosted at every tier. Buy it once, run it in your own infrastructure, and keep the code.

Solo
$89one-time

For one developer shipping their own agent.

  • Full source, yours to keep — 12 months of updates
  • All 5 SDKs: LangGraph, CrewAI, Claude Agent SDK, OpenAI Agents SDK, Vanilla
  • All 3 reference agents and all 54 tools
  • Memory, guardrails, observability, evals
  • Durable human-in-the-loop that survives a restart
  • MCP both ways — consume any server, publish your agent as one
  • Single developer, unlimited personal projects
most popularTeam
$199one-time

For teams putting agents in front of real users.

  • Everything in Solo
  • Up to 10 developers on one licence
  • Use it on client work and commercial products
  • The approval queue and audit trail across your whole team
  • Priority issue triage
  • Private community channel with the founder
Enterprise
Let's talk

For regulated teams and anyone who needs it in their own cloud.

  • Everything in Team
  • Unlimited developers
  • Self-hosted in your own infrastructure — data never leaves your boundary
  • Security review and architecture support
  • Custom SDK adapters and tool integrations
  • Invoicing, MSA, and a direct line to the founder

Source-available commercial licence — own it, run it, modify it. Solo covers one developer; Team adds client and commercial work for up to 10. You just can't resell agentFast itself.

07 — What's shipped

v1 is complete.

This isn't a roadmap — it's the current state. Everything below is built, tested, and in the source you get on purchase. The flagship property (kill the process mid-approval, restart, resume from the exact step) is a real test against real Postgres with a real SIGKILL, not a screen recording.

Adapters6 SDKs — LangGraph, Vanilla, CrewAI, Claude Agent SDK, OpenAI Agents SDK, and agentFast's own native Team orchestrator
AgentsSupportAgent on all 5 single-agent SDKs, plus ResearchAgent and CodeAgent
Multi-agent teamsA supervisor fans out to sub-agents with their own context window and budget — every child's cost rolls up into one number on the parent
Production layerDurable HITL, guardrails, 3-tier memory, observability, evals, planning
StreamingLive SSE for every run — tokens, tool calls, approvals, re-attach after a drop
Tools54 production tools, MCP servers by config, agentFast itself publishable as MCP
DeployDocker Compose, Railway, Fly, GCP, AWS, Vercel

In flight

Dashboard live viewThe streaming run view, alongside the existing step tree
Multi-worker streamingRedis-backed event bus for horizontally scaled deployments
08 — FAQ

The engine got easy. The infrastructure didn't.

Straight answers about what agentFast is, what it runs on, and why the hard part was never the model.

No — and the difference is the whole point. A boilerplate is code you copy once and own alone; the day you clone it, it starts drifting from everyone else's. agentFast is infrastructure: the durable-execution engine, the approval gate, the audit trail, the eval harness — the parts that are the same hard problem for every agent team, maintained in one place and improved for everyone at once. You still write your agent. This is the layer it runs on.

You should — agentFast runs on them, not instead of them. But an SDK is an engine, not a car. LangGraph gives you orchestration; it gives you nothing for the moment your agent restarts mid-task and loses the run, or fires a refund twice because no one approved it, or invents an answer no one catches. That gap between 'orchestrates' and 'survives production' is exactly what this fills — while you keep writing real LangGraph or real CrewAI underneath.

Production is the only thing it's for. It ships the parts that separate a demo from a deployment: durable execution (an agent that survives a process crash mid-task and resumes from the exact step), a human approval gate on risky actions that survives a restart, PII redaction in and out, cost and latency tracing on every run, a complete audit trail of every decision, and evals that fail your CI before a regression ships. It's built to sit in front of paying customers on day one.

Because the buyers who most need this — anyone touching money, health, or regulated data — can't send their prompts, tool outputs, and audit logs to someone else's cloud. agentFast runs entirely in your infrastructure. Your data never crosses your boundary, and you're not locked to a vendor's platform. That's a deliberate line against the hosted agent platforms: your intelligence, your infrastructure, your control.

It's source-available. You get the full source, own it, run it anywhere, and modify it however you like. Solo covers one developer for your own projects; Team covers up to 10 and adds client and commercial delivery. The one thing no tier allows is reselling agentFast itself — that's what funds the updates instead of the project getting cloned once and abandoned.

Any model — OpenAI, Anthropic, Gemini, Ollama, Groq — via a model-neutral layer, so you're never locked to one vendor and can self-host. Tools are MCP-native, in both directions: consume any MCP server the ecosystem publishes, and expose your own agent as an MCP server other agents can call. The 54 tools that ship are plug-and-play; adding your own is a one-liner.

Each SDK sits behind a thin adapter, so a breaking change hits a small, contained surface instead of your whole codebase — and fixing it once fixes it for everyone on that adapter. That's the quiet advantage of infrastructure over a copy you maintain alone: you're offloading the ecosystem-churn maintenance, not inheriting it.

It's being built in public right now, in stages, and tested hard as it lands — durable kill-and-resume is a real automated test against a real database with a real process kill, not a slide. You get the full source, yours to keep, plus 12 months of updates. I'd rather hand you something that survives production than rush you a half-tested skeleton.

09 — From the founder

I built agentFast because I'd rebuilt this exact plumbing too many times. At Einstein Labs we've shipped agents across support, sales, coding, commerce and finance — and every single one started with the same two-to-four weeks of memory, tools, tracing, guardrails and human-in-the-loop before the real work began.

Orchestration is solved — CrewAI and LangGraph decide how an agent thinks, and they do it well. What nobody frames is everything above that: what happens when a tool fails, when a human has to sign off, when the process dies mid-run, when someone asks what it cost. Everyone hand-rolls that layer, badly, over and over. So I packaged ours, and made it indifferent to what runs beneath it.

It's built. Not a roadmap — 5 SDK adapters, 3 reference agents, 54 tools, and a kill-the-process-and-resume test that runs in CI. You get the source on purchase. If it doesn't run on day one, I'll refund you myself.

Agents Einstein Labs has already shipped
Praxiom AI · AI product manager (live flagship)Polaris · AI coding agentBodhi · Agentic commerce conciergeVega · AI derivatives-intelligence engineAstra · AI sales agentAccord AI · Autonomous negotiation agent

We don't think we understand this problem. We've shipped it, repeatedly. agentFast is the harness we wished we'd had the first time.

AC
Abhishek Chatterjee
Founder · Einstein Labs
in Verify me on LinkedIn →