Bring your data to AI.
With European security.

A data platform that deploys in your cloud, designed specifically so you can use your data with AI securely and with European regulatory compliance guarantees. It centralizes data from all your systems — structured and unstructured —, deduplicates it, connects it, describes it in a semantic graph and protects it. The result: your AI behaves as if it were trained on all your data and always answers with the truth of your business, with answers traceable to the source data, atomic access control and under maximum security.

The layer that compiles your security policy into every query, designed to work with AI. It authorizes by identity and delegation chain, and goes down to the exact row, column, document and redacted version. It is enforced in the infrastructure, rewriting the query before it touches the data, never through instructions to the model; and when in doubt, it denies. Every query is traced end to end under a single audit identifier.

A layer that describes what each piece of data is and how it relates to the rest: what customer means, which contracts belong to it, which conversations go with which. You need it because a database stores fields, not meaning: the same customer is a different object in every system, and fields with similar names carry different senses. With the graph, AI does not have to work it out on every query: it reads it. Without it, the model fills the gaps by inference, and that is where the errors appear.

Opendome takes data from the CRM, the ERP, financial platforms and the rest of your sources, and deduplicates it, connects it, describes it and protects it. From a customer identifier you reach any related data, whether it sits in one system or another. Your systems remain the source.

Yes, and not only with that one. Opendome does not integrate with a specific model: it exposes the data through API and MCP, so it can serve any LLM or orchestrator. What changes is how the data arrives: because it is deduplicated, connected and described, whoever asks resolves it in a single query, without chaining calls across systems or inferring what is missing. The answer comes from the source data, not from a reconstruction.

Yes, in the sense that the model receives the data the query authorizes: without that it cannot answer. What is not needed is sending it to an external provider. Opendome offers the model as a service hosted in a private cloud, so inference happens inside your perimeter and under European jurisdiction, and the data never leaves your control.

In your own infrastructure and in an open format, within your jurisdiction. It is not copied to a provider's cloud, so control over it is technically verifiable and does not depend on a contractual clause. Remaining under European jurisdiction, it stays beyond the reach of the US CLOUD Act.

Because the model stops reconstructing context for every task. Without prepared data, AI fills the context window, launches several calls and spends tokens inferring what it should be able to read directly. With data deduplicated, connected and described, the same question resolves in a single query: around 80% fewer tokens, with the same question and without changing model.

There is no charge for accessing your data or for each operation AI performs against it. It is the opposite of the headless shift the large vendors are adopting: they expose your system as an API and bill every call an agent makes against your own information, so cost grows with use. In Opendome the core is open source and the data lives in your cloud, so accessing it carries no charge.

No company-wide project is needed before seeing results. Opendome is deployed by business domain — what we call galaxies: sales, finance, people, logistics — and each one moves on its own. A galaxy can be running with agents in two or three months, with governed access and compliant with European regulation. The next ones build on what is already there.

Opendome provides services and develops technology. The base of that technology is open source, and on top of it we have a commercial solution that simplifies and automates the administration of the system. In any case, services are part of our DNA: we get involved in the projects and support the deployment from start to finish.

Yes. To do it, Opendome has created two unique technologies, developed on that same open base. One generates compiled versions of the content by security policy, hiding in each version the information that policy requires to protect. The other anchors each fragment of content to the structured entity it belongs to: the customer, the contract, the project. The result is far richer context than a transactional system's, because what was said in a call stays linked to the customer it was said about.

The same piece of content, generated as many times as access policies affect it. Each version hides what that security policy requires to protect and the rest stays intact. Whoever queries does not receive the original filtered on the fly, but the version that corresponds to them. Each one is indexed separately, with its own embeddings, so not even a semantic search can retrieve what was hidden.

For security and compliance, quality of results, traceability and cost. With MCPs there are as many doors as systems, each with permissions inherited from a model designed for people, and no common record of what the AI queries. An MCP gives access to a system, but does not say what a customer is in each one or which holds the correct data, so the agent works it out and fills the gaps by inference. Nor does the answer keep a reference to the source data, so there is no way to check where it came from. And reconstructing context on every query consumes tokens that prepared data would not need.

No. Business memory already exists: it is in the data. Memory systems rebuild it separately, out of summaries and inferences, and summarizing loses the link to the data that produced it: the recollection can no longer be checked. It is also a copy, so it ages; when the data changes, the summary does not. With Opendome semantic and episodic memory stay where they are, in described and connected data, and only procedural memory belongs to the agent: how to do things.

Every query is authorized by identity and delegation chain, and the effective security policy is compiled down to the exact row, column, document and redaction version. It is not a matter of filtering the answer after reading the data: the security policy travels inside the query, so denied data does not leave — not even through the vector index, because each redacted version is indexed with its own embeddings. The system denies by default: without explicit permission, there is no access.

On an open source base. The core is Apache 2.0, with no proprietary licenses: you can audit the code, check what it does with your data and operate it yourself, with no black box in between.

Access policies are yours, applied in your infrastructure and leaving an auditable record of every query. Sovereignty stops depending on trusting a provider and becomes something you can verify.