The open engine for AI that makes work more efficient

A secure, model-agnostic platform for connecting your systems and running AI apps. Build with NimbleBrain or bring your own, then deploy in your infrastructure with complete control of your data.

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4.8/5

IPinfo, Brontide, AEP Hawaii, Consortium Equity, Bayze, Scout, Colorcase, Adam Neeley, Code Four Media, cxjoe, Oxygen Ventures, IPSDI, WebCare Digital, Boulder Equity Partners, Kamaaina Kids, People Culture Talent, LeadForce Solutions, Bassethound, Precision Outbound

The NimbleBrain open-source platform

Run agents on your systems, inside your boundary.

A runtime, an app framework, and the connectors between them.

A runtime you host

It holds the agents, the state and the audit trail, and runs where your data already is.

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Your infrastructure

Kubernetes, a VM, or a laptop.

Readable state

Plain files you can diff and roll back.

Apache 2.0

Read it, fork it, keep the version you hold.

Meets your business where it already is.

Connects to 1,000+ systems you already run, under credentials you hold.

  • Slack
  • Salesforce
  • HubSpot
  • Stripe
  • Notion
  • Jira
  • GitHub
  • Google Drive
  • Zendesk
  • Shopify
  • Asana
  • Airtable
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Case studies

How innovative companies lead with AI

14xMore concentrated outreach

Know Which Broker to Call Before You Send the First Email

A vendor tier rating told them who was in good standing. It did not tell them who places their kind of loan. So we scored for the second thing.

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A lender's desk in late afternoon light, a broker list annotated in pen beside a landline phone, with someone mid-call out of focus behind
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Security by design

Private, verifiable,
and inside your boundary.

Three promises, and none of them asks you to take our word for it.

  • Verifiable

    You do not have to trust the claim, because you can read the thing that makes it.

    • Apache 2.0

    Read it, fork it, and keep running the version you hold. The licence cannot be withdrawn from you later.

    Read the source

  • Private

    For most customers we never hold your data, because the runtime executes inside your own boundary.

    • Runs on your infrastructure, or ours if you prefer
    • Credentials sit with their owner and are never pooled
    • Any model provider, including one on your own hardware
    • Nothing is trained on your data

  • Isolated

    A session is handed one workspace. The identifier that would address a second one does not exist in that context.

    1. 1 A session opens against one workspace
    2. 2 It is handed that workspace’s tools, and no others
    3. 3 Membership is re-checked on the next run
How isolation works

Why teams choose NimbleBrain

The questions a platform team asks before it puts anything in front of production, answered in the architecture rather than in a contract.

  • Open source

    Apache 2.0. Read it, fork it, and keep running the version you hold. The licence cannot be withdrawn from you later.

  • No vendor lock-in

    The model is a setting. Point at a frontier API, a cloud you already buy, or your own hardware, and change it without touching an agent.

  • Runs where your data is

    Kubernetes, a VM, or a laptop. Agents reach your systems under credentials you hold, and nothing has to leave the boundary you draw.

  • Every run is a record

    Inputs, tool calls and output are kept and attributed to a person and a workspace, so a decision can be reconstructed rather than inferred.

  • Isolated by construction

    A conversation reaches exactly one workspace. Reaching another is denied rather than merely gated, so a mistake cannot cross a tenant.

  • Built on MCP

    Tools arrive over an open protocol, so a bundle written here runs in any conformant client and you are not buying a plugin format.

Any model. Any cloud. No rewrite.

Anthropic, OpenAI, Gemini, Meta Llama, DeepSeek, Qwen, Kimi, Mistral, GreenGPT, AWS, Google Cloud, Azure, Nebius, NVIDIA, Hugging Face, Ollama, vLLM, OpenRouter

FAQ

Frequently asked questions

The questions that come up before a first engagement. Anything else, ask us directly.

Do we have to send our data to you?

No. The runtime executes in your infrastructure and reaches your systems under credentials you hold. We do not need a copy of anything to make it work.

What happens if we stop working with you?

You keep a running system. The runtime is Apache 2.0, your schemas and skills are plain files you already hold, and the agents keep executing.

There is no export step, because nothing is held on your behalf.

Are we locked to one model provider?

No. The model is configuration. Point at a frontier API, a cloud you already buy, or something on your own hardware, and change it later without touching the agents.

How do we know what an agent actually did?

Every run keeps its inputs, its tool calls and its output, attributed to a workspace and a person. A decision can be reconstructed after the fact rather than inferred.

What does it connect to?

Billing, tickets, the project tracker, the warehouse, and the internal service with no public API. Connectors are MCP servers — point the runtime at any one and it appears alongside the rest.

A connector is installed, not commissioned.

Can we use it with what we already run?

Yes, and that is the usual case. It adopts a layer at a time — runtime, apps, agents, skills, connectors, governance — so nothing has to be replaced up front to get value from the first piece.

How small can we start?

One workflow. That is the intended size of a first engagement, and the point at which it should be obvious whether a second is worth doing.

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Get involved

Come and build it with us

The runtime is Apache 2.0 and the work happens in public. Read the code, open an issue, or argue with us about where it should go.

One workflow is the right size to start.

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