Solutions
What you can do with your own data
Eight ways into the same platform, depending on what brings you here. Each one describes a real problem, what Omniscient changes about it and what it takes.
The knowledge graph, without the jargon
A search engine finds documents. A graph links what they contain, and answers questions no single document holds.
Read
Searching your enterprise documents, and finding the answer
Finding them is the hard part, and so is trusting what you read. An answer that cites no source is worth no more than a rumour.
Read
AI without hallucination: an answer you can check
A language model always has an answer, even when it does not know. What separates a reliable answer from a merely plausible one is not its tone, it is what you can check.
Read
Connecting your tools: where your data comes in
An assistant is only worth what it is allowed to read. So the first question is not what it can do, but what you can plug it into.
Read
Security: an assistant that reads no more than its reader
The worry is legitimate and it is always the same one: by handing your documents to an AI, are you opening up to everyone what only a few were allowed to read?
Read
Sovereign AI on your data, without letting it leave
The question is not whether AI is useful. It is where the documents you feed it end up, and who can reach them.
Read
The AI Act, and what it asks of whoever deploys an AI
The European AI regulation does not address vendors alone. A company that puts an assistant in the hands of its teams also has things it must be able to show.
Read
Automating your processes: what repeats no longer has to be done
An incoming request to qualify, a report due every Monday, an alert to pass on. These tasks follow a rule, and a rule can be automated.
Read
Choosing where to start
Where do you start when everything needs doing?
The eight pages above describe the same platform, seen from eight different problems. If your teams spend their days looking for documents, start with document search. If your questions cut across several tools and no single file holds the answer, read the knowledge graph page first. If leadership hesitates because an AI that makes things up is not acceptable, the page on answer reliability addresses that exact objection. If the question is what the platform can plug into, go to connectors. If it is who will read what once the sources are connected, the security page answers that. If the blocker is where the data lives, go to sovereign hosting. And if the subject is time lost to repetitive work, automation is your way in.
What artificial intelligence changes in a small or mid-sized company
A company of two hundred people has no less scattered data than a group of twenty thousand, it has fewer people available to go and find it. That is where generative AI gives the most: it reads what nobody has time to read again, and it returns a written answer rather than a list of files to open. It still has to read your data rather than its own memory, and that is the whole difference between a consumer assistant and an enterprise platform.
Do you have to replace your document management or internal search?
No. Document management stores files, enterprise search finds them again, and both keep their use. What neither can do is answer a question whose answer is written in no single file, because it follows from several at once. Omniscient sits on top of what you already have, reads your sources where they are, and forces no migration.
What if our data cannot leave the country?
That case is planned for, not an exception. The vendor is French, shared hosting is European, and installation on your own infrastructure exists for organisations whose data does not leave the network. In that last mode the language model runs on your side too, which answers both the GDPR constraint and the internal rules that forbid calling an outside service.
Let us see what it does on your data
A demonstration is built on your own cases. Tell us what you are trying to get, and we show you the path to the answer.