We build the control plane for agentic AI
xpander.ai is a vendor-neutral platform for building, running and governing AI agents — on any model, any framework, and in any environment you choose, including your own.
SOC 2 TYPE II CERTIFIED
GDPR COMPLIANT
Read about our latest funding round
xpander raises $7.5M to democratize AI agents and help every company become AI-native, without vendor lock-in.
ABOUT XPANDER.AI
Why we exist
A short version: we make it possible to run AI agents in production without giving up control of your models, your infrastructure, or your data.
Most organizations do not have a model problem. They have a governance problem. The models are capable enough, the frameworks are mature enough, and the use cases are obvious enough — but very few teams can say with confidence which agents are running in production, what those agents are allowed to touch, or who signed off on them. So the work stays in prototypes.
xpander.ai exists to close that gap. We give platform and engineering teams a single control plane for the whole agent lifecycle. Build an agent no-code with Omni, low-code in Agent Studio, or code-first with our SDK and REST API — then run it under one policy engine that governs who can build, run, approve and publish. Every agent is registered. Every tool call lands on the record. Every credential stays in a vault, out of model context.
We are deliberately vendor-neutral, and we think that is the only defensible position to hold. Claude, GPT, Gemini, Llama, Qwen, Mistral, Deepseek or your own fine-tune. LangChain, Strands Agents, Agno, or a framework you wrote yourself. Our cloud, your VPC, your Kubernetes cluster, on-premises, or fully air-gapped. The control plane is the constant; everything underneath it stays your decision.
What we believe
Neutrality is a feature
Betting your agent layer on a single model vendor is a bet you will eventually have to unwind. We keep the cost of substitution close to zero, on purpose.
Governance belongs in the runtime
Permissions, approvals and audit trails have to be enforced where the agent executes — not described in a document nobody reads. If it is not enforced, it is not a control.
Your environment, your data
Self-hosted means self-hosted. Agents run in your own cluster, with no data egress, no training on your traffic, and no vendor able to inspect what executes.
One platform, three ways in
One governed runtime underneath, whether you are starting fresh, building together, or bringing agents you already have.
Omni
No-code. Describe the agent you want in plain language and Omni assembles it, wires up the tools, and hands it back ready to run.
Multiplayer AI workspace
Build and talk to agents together. Shared threads your whole team can join, one published agent everyone can use, and per-user scoping so nobody is stepping on anybody else’s work.
From your existing AI tools
Built on a laptop, running in the cloud. Omni connects to Claude Code, Codex, Cursor or any MCP client, reads the agent you already built locally, and redeploys it — governed, scheduled, shared and audited.
TRUST
Trust, in writing
We would rather be audited than taken on faith. Our reports, subprocessors and current security posture are published, not described.
SOC 2 Type II certified, with reports available on request
GDPR compliant, with data residency determined by where you deploy
A full audit trail of every tool call, exportable to your SIEM
A secrets vault that keeps credentials out of model context
Self-hosted deployments egress no operational data to us
Come see it in your own environment
Talk to us about running governed agents inside your own cloud, your own cluster, or a fully air-gapped network.