Sovereign AI consulting

Code, data and prompts that stay yours

Agents in your sensitive processes without depending on one provider. We agree which processes stay under your control and keep their code, data and prompts with you.

Where AI dependency hides

Nobody owns the list of your agents' dependencies.

One agent can call a model, embeddings, a vector store, tracing and a cloud.

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    Where it stallsPrompts written against one provider's API.

    What we do A model layer lets models swap.

  2. 02

    Where it stallsData and logs go to unchecked regions.

    What we do Sensitive steps stay in your environment.

  3. 03

    Where it stallsA vendor or integrator holds the keys.

    What we do Keys, accounts and repositories in your name.

How we work

Every dependency listed, every exit tested

Code, data, prompts and keys stay in your name.

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    Everything your agents depend on, listed

    We list each model, store, cloud and tool, who holds its account, and which processes must stay yours.

    • Data flows by provider, region
    • Cost exposure per provider
    • Which exit comes first
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    Built to switch providers

    A model layer lets an agent run hosted or open-weight, and an evaluation set judges every replacement.

    • Model-agnostic architecture
    • Open-weight fallback where needed
    • Your cloud account and region
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    The keys stay in your hands

    Every critical dependency gets a tested exit plan, so you can change a provider, or us.

    • Your keys, accounts, repositories
    • Runbooks for provider changes
    • Your evaluation sets and weights
Engineering in the open

We help build what agentic AI runs on

Open standards, open-source tooling and published research, all public, so you can check our engineering before you hire us.

Shaping agentic AI

The first agentic AI engineering company to join the Agentic AI Foundation

The Linux Foundation formed it around Anthropic's MCP, OpenAI's AGENTS.md and Block's goose. AWS, Google and Microsoft are platinum members. In its own words: “Together, we're shaping the future of agentic AI.”

Open source

We build open-source agent tooling that other engineering teams install

9M+ PyPI downloads
3,900+ GitHub stars
31 public repositories

Framework contributors

When the framework breaks, we fix it at the source

We maintain our own open-source agent framework and contribute fixes to the frameworks our agents run on, through official partnerships with their teams. Breaking changes reach us before they reach your codebase.

Research

Our engineers and PhDs publish peer-reviewed research

Peer-reviewed papers on agent architectures, evaluation and AI security, and an open benchmark anyone can rerun against our results.

Track record

Frontier AI teams now build on what we shipped first

Our client agents were in production before most of today's agent frameworks had a stable release. You get a team that already knows what breaks between a promising demo and a system people rely on every day.

Engagement models

Ways to start

Each path starts with a free call with a founder or senior AI engineer. A build goes ahead only after its Proof of Value meets the agreed threshold.

Technology

A stack where every layer is replaceable

An evaluation decides when a replacement passes.

  1. Model Swapped after an evaluation run
  2. Agent framework Open source and model-agnostic
  3. Evaluation Decides when a replacement passes
    • Evaluation sets
    • Tracing
    • Cost per task
  4. Your environment Where agents, data and keys live
    • AWS
    • Azure
    • GCP

How we choose the stack

FAQ

Questions about sovereign AI

What does sovereign AI mean for an agentic system? +
That your company decides which processes must stay under its own control, and for those can change the model, the cloud or the vendor behind an agent without rebuilding it, keep data where it has to stay, and hold the keys, code, prompts, evaluation sets and any fine-tuned weights itself. We treat it as a property of the system that can be tested, dependency by dependency.
What does sovereign AI consulting include? +
Three pieces of work. First, a dependency register for each agent: data flows by provider and region, cost exposure per task, and which dependency needs an exit first. Second, the engineering: a model layer between your agents and every provider, an evaluation set for each model change, and an open-weight fallback for sensitive, critical steps, in your cloud account and region. Third, a tested exit plan for each critical dependency, with keys, accounts, repositories, evaluation sets and weights registered to your company.
Do we have to stop using hosted models? +
No. Many systems keep a hosted model for most steps because it is the best fit. The point is that the switch is possible: a model layer between the agent and the provider, an evaluation set that tells you whether a replacement is good enough, and an open-weight fallback for the steps where it matters most.
Are open-weight models good enough for our use case? +
It depends on the step. Narrow tasks such as extraction or classification often run well on smaller open-weight models, while long multi-step reasoning may still need a larger hosted one. We answer the question with an evaluation run on your own cases rather than a public leaderboard.
Can the agents run entirely in our own environment? +
Yes, in your cloud account and a region you choose. Running on your own hardware with open-weight models is possible and scoped per project, because your team then runs the capacity: we size it with you and write the runbooks before handover.
Does this make us compliant with GDPR or the EU AI Act? +
We help you assess what those requirements mean for the system and engineer for them: data residency, logging, human oversight and documentation. We do not certify systems or give legal advice; your legal and compliance team makes that call with the evidence we produce.
What is in an exit plan? +
For each dependency: what replaces it, how data and configuration move across, which evaluation proves the replacement works, roughly how much effort the switch takes, and who on your team runs it. The plans are tested on the dependencies that matter most, not only written down.
Will we depend on Vstorm afterwards? +
No. Vstorm goes on the dependency register like any other supplier. The code, keys, accounts and runbooks are yours, there is no license or platform fee, and your team can change providers, or change us, without asking.
Sovereign AI consultation

Find out what your agents depend on

Bring one agent or planned build; we show which dependencies need an exit first.