Enterprise digital twin
Omniscient links your documents, tools and databases into a knowledge graph, then uses it to answer your questions, run your processes and power your agents. One foundation, one permission model, nothing else to install.
European hosting · Can run entirely on your own infrastructure
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Three customers: Bureau Vallon (contract ends 31/03, billing incident open for 12 days), Gérard & Fils (30/03, disputed delivery) and Tessier SA (28/03, support ticket unanswered).
One platform instead of
The information exists. It is in a PDF contract, an email thread, a CRM record, a shared workbook. What's missing isn't data. It's the link between the data.
The question from the top of this page
Which customers have a contract expiring this quarter and an unresolved incident?
No single document holds the answer
Twelve files mention contracts, eight mention incidents, none mentions both. Cross-referencing is left to you, one customer at a time.
The answer is where two links meet
The contract is attached to its customer, and so is the incident. You just look for the customers where both meet, and every link keeps the document it came from.
A search engine returns documents. Omniscient returns an answer, with its sources, because it knows how your business objects relate to each other.
Everything you connect comes in through the same door and becomes graph. Everything you do with it plugs into that graph. There is no separate tool per use, and nothing else to deploy alongside.
Your sources
The foundation
Your business objects and their links in one place: customers, contracts, projects, incidents, invoices, people.
What plugs into it
Answers in plain language, sourced and verifiable in one click.
Scenarios triggered by the clock or by an event.
Assistants specialised by domain, each with its own scope.
Anomalies and risks flagged before they cost anything.
One foundation, one permission model, one platform to run.
The graph is the foundation. The other five capabilities plug into it and share the same permission model: you are not installing five products.
The foundation
A living map of your company: the entities, their relationships, and the document that justifies each one.
The five capabilities below read from and write to this same graph. An entity corrected once is corrected for the assistant, the automations, the agents and the models.
The knowledge graph, explained without jargon
What plugs into it
An assistant that searches your data, cites its sources, and knows when to return a table, a diagram or a spreadsheet.
Data flows designed visually, scheduled, and watched.
Business scenarios that read, decide, write and notify, triggered by an event or by the clock.
Assistants dedicated to one domain, with their own instructions and their own data scope.
Models that learn the shape of your graph in order to flag what stands out.
Four movements. The first three happen once, the fourth every day.
A visual editor links your shared drives, SQL databases, APIs, Google Drive, SharePoint, HubSpot and Notion. Credentials are declared once, then reused everywhere.
PDF, Word, PowerPoint, Excel, CSV and images: extraction reads tables and the text inside images too.
Ingestion identifies your entities (customers, contracts, projects, incidents, people) and links them. Duplicates are merged: "Dupont Ltd", "Dupont Limited" and "dupont" become one customer.
Every node keeps a link back to the document it came from, downloadable in one click.
The assistant searches the graph and the documents at once, then writes an answer with citations. Tables, diagrams, spreadsheets or documents: the answer takes whichever shape is useful.
Every claim is clickable and leads back to its source document.
What you just asked for by hand, an automation will do on its own: on a schedule, when an email arrives, when a file lands, or when the graph changes.
With a human approval step before anything sensitive, if you want one.
Four workspaces, one knowledge base.
The daily entry point. Ask a question, get a sourced answer, leave with a file if you need one.
Four concrete situations, from sales to compliance.
Sales leadership
Prepare the Bureau Vallon account review: live contracts, exchanges, incidents, overdue invoices.
A sourced briefing in seconds, where it used to mean opening the CRM, the mailbox, the shared drive and the ticketing tool.
Executive and finance
Which suppliers keep running late, and which projects depend on them?
Dependency chains surface in the graph, and an automation raises the alarm the moment a new delay hits a critical project.
Customer service
Every incoming email is classified, attached to the right customer and routed to the right team.
The automation reads the mailbox, qualifies the request, drafts the reply and submits it for approval before sending.
DPO, quality, compliance
Where is personal data stored, and who has access to it today?
The graph gives the map, the audit log gives the history, the export gives the evidence.
A platform that reads the whole document estate is only worth having if it honours the access rules already in place. That was the first constraint we solved.
Five ready-made roles, custom roles, and sharing decided object by object: private, chosen people, chosen roles, or the whole organisation.
Permissions apply during the search, not after it: an answer cannot cite a document its reader isn't allowed to open.
In shared mode, each organisation gets its own isolated space, right down to the graph and the search indexes.
A password entered into a connection never comes back out, not even for the person who entered it. Revoking a share cuts access from the next run onwards.
Who asked what, which automation wrote where, at what cost. Exportable as CSV or JSON for your audits.
European hosting when we run it, or a full installation on your own infrastructure when nothing may leave.
Same product, same code. What changes is who holds the infrastructure.
Open an account, we run the platform. Nothing to install.
Your own instance, operated by us.
Nothing leaves your network. You keep control of everything.
Not sure which one? The choice usually settles in an hour's conversation about your actual constraints.
Thirty minutes, over video, on your own cases. We build the demo from your material, not from a canned dataset.
How a quote is built