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Local AI that’s accurate on your documents.

Anyone can run a model locally. We make it accurate on your documents and prove it on your own cases, on your own server.

Designed for on-premises Designed for GDPR and the EU AI Act No data to third parties

Your company network External cloud: blocked

Concept preview

The problem

Your most valuable data is the data you can’t paste into ChatGPT.

Cloud AI

Powerful, but your data has to leave the building.

Not allowed for sensitive data

Simple local AI and RAG tools

Private and can search your files, but often misreads your terms, picks the wrong passage, and gives no way to check its quality.

Not reliable enough out of the box

Sovereign AI

Designed to run on your server, understand your terms and find the right passage, with quality you can check.

Private and reliable

66 % of German companies using AI say data protection holds them back. (Bitkom, 2026)

Why us

Searching your files is easy. Getting the right answer is the hard part.

RAG tools can search your files. Small models still misread jargon and pick the wrong passage. We close that gap.

Finding information

Matches similar words

Searches by meaning, using your terms

Your terms

Misses your jargon

Adapted to your documents

Proof

Quality unknown

Tested on your own cases

Effort

Needs ML know-how in-house

Set up and maintained for you

How it works

Three steps to an assistant you can trust.

Step 1

Install on your server

We set up a small open model on your own hardware or private cloud. Nothing is sent outside.

Step 2

Fit it to your documents

We adapt it to one workflow using knowledge from your team, so it speaks your language.

Step 3

Ask, check, decide

Your team asks questions in plain language. Each answer is designed to link to the document it came from.

Data flow

How your data stays safe

The system is designed so that everything happens inside your network. Nothing is sent to an external AI service.

For your IT

Designed to fit how your company works

Reads real-world documents

Designed for scanned PDFs, tables, spreadsheets and email threads, not just clean text.

Respects access rights

Designed so people only get answers from documents they are allowed to see.

Connects to your systems

Designed for file servers, SharePoint and document management systems, staying current as documents change.

Runs where you want

On your own server, or on a dedicated instance in a German data centre if you prefer not to run hardware.

Use cases

Start with one workflow.

Service & maintenance

“Has this fault happened before, and how was it fixed?”

Contracts & policies

“What notice period applies to this supplier?”

Customer requests

“Which team should handle this email?”

Design partners

Become a design partner.

We’re building it with a small group of companies (20–250 staff) whose documents can’t leave the building. You shape the product and get early-partner terms.

  • Early access and direct influence on what we build
  • A working prototype on the documents for one workflow, on your own server
  • Early-partner pricing if you decide to continue

Apply as a design partner

A 30-minute call about your workflow.

Talk to us about your workflow Early-partner terms are agreed together.
Prefer email? yadavd@uni-greifswald.de

Team

The people behind the project

A founder backed by experts in knowledge graphs, security and life sciences.

Portrait of Dipendra Yadav

Dipendra Yadav

Founder

LLMs for privacy-critical domains

Portrait of Sumaiya Suravee

Sumaiya Suravee

Knowledge graph

Information extraction and ontologies

Portrait of Min-Hsuan Hsieh

Min-Hsuan Hsieh

Cybersecurity & finance

Security testing and financial engineering

Portrait of Naveen Kumar

Naveen Kumar

Biotechnology

Single-molecule biophysics and modelling

FAQ

Common questions

Does any of our data leave our company?

With an on-premises setup, no: the model, your documents and all questions stay on your own server. If you choose a dedicated instance in a German data centre instead, data is processed there under a data processing agreement.

How is this different from RAG tools or installing an open model ourselves?

Anyone can install a model or a RAG tool. Backed by our research, we adapt search and model to your terms, test it on your own cases before go-live, and keep it current.

Is it ready to use today?

Not yet. We are building the first version together with a small group of design partners, so their workflows shape what we build first.