Because you build it. We bring the harness and the engineers. The model of your business, the agents that run on it, and the decision trail behind them stay yours.
We work with banks, lenders, credit bureaus, insurers, health systems and manufacturers: enterprises where the systems of record cannot be replaced, the data cannot be copied out of them, and the agents have to work inside both constraints.
The difference shows up at the end of the project, not at the start.
You are not starting from nothing. The harness runs from day one. It is much the same at every company, so it was never going to be your advantage. Your engineers and ours build the part that is.
This is what sovereign AI actually means. Your data stays in the systems that already hold it. Your models are swapped by configuration, with no dependency on a single provider. Your environment is wherever you already run: your own cloud account, your own Kubernetes cluster, your keys, and no data leaving your boundary.
You do not hand over the model of your business to get the AI. That is the trade most enterprise AI asks for, and it is the one you do not have to make.
An agent is a language model plus a harness, and the language model is the smallest part. We bring the rest already built: ontology, guardrails, lineage, connectors and the agent runtime, all of it running as containerized services. It sits on your Databricks or Snowflake, not instead of them.
What it does →Forward deployed engineers work inside your environment, learn how the systems actually behave, and build alongside your team. We hand over when your people can run and extend it without us.
How a build runs →A customer, a member, a product, an asset. Several systems each hold part of it and their definitions conflict. NuStudio resolves the entity where it already lives, carries the policy that governs each field, and gives your engineers a foundation to deploy agents against. Each tab is a representative first entity for that sector.
Resolved across five systems. Nothing left the bank.
What your team owns at the endSystems are representative of each sector. Attributes and outcomes illustrate a typical first entity, not a specific customer deployment.
If you run Databricks or Snowflake, keep them. Their semantic layers describe metrics over data already in the platform, and an agent can answer questions against that accurately. We read from them like any other source.
The systems that run your company are not in the warehouse, and the job is not to answer a question but to change a record and prove it was allowed. The harness does that part, above what you already bought and inside the boundary your security team already defends.
| Your team builds it | Closed ontology platform | The NuStudio harness | |
|---|---|---|---|
| First governed agent | Two to four quarters of infrastructure first | Fast, after the platform commitment is signed | One quarter, on the systems you already run |
| Your data platform | Yours, and you wire everything to it | Expects your data to move toward it | Stays where it is; we read it in place |
| Policy enforcement | Whatever your team has time to build | Their policy engine | Rules compiled from your obligations, checked before and after every call |
| API surface | You write it | Theirs | Several hundred endpoints, already written |
| Who owns the ontology | You | They license it to you | You, in an open spec in your repository |
| If it ends | You keep it | A migration project | You keep the ontology, the agents and the code |
Describes the three routes most enterprises actually weigh, as of late 2026. Not a comparison with any one vendor’s current terms.
Most enterprises have one: a pilot that worked in a notebook and never reached production, or a workflow nobody will automate because nobody can prove it was done correctly. That is the right place to start, because the reason it stalled is almost always the environment rather than the model.
Discovery takes a few weeks. We map the systems behind it, the policy that governs them, and what it would take to put one governed agent into that workflow. You get a written answer either way.