Advanced AI. Your IP stays inside.

Cloud AI makes you send your IP out. We do the opposite. We build advanced AI tools for enterprise research. They run on your systems, and they can run fully offline. Your designs, your code, and your results stay inside.

Cloud AIYour data goes to the AI. You lose control of it.
ResidentIPThe AI comes to your data. Nothing goes out.

In development · Designed for fully offline use

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01 / The tools

Research. Analyze. Build.

You can have advanced AI and keep your IP. You do not have to choose.

We put advanced models, code tools, and data tools into one local research system. It uses the terms and the rules of your field. It shows its sources, so your team can check each result.

Search what your company knows.
Read large sets of documents, data, and code. Find links across teams and years.
Run deeper research.
Compare sources. Test ideas. Use code and analysis tools to answer hard questions.
Build tools for your field.
Use your terms, your methods, and your rules. Keep useful work, so your team can use it again.

02 / Offline by design

Built to run fully offline.

The models and the tools run on your systems. In fully offline mode, no outside AI service is necessary. Disconnect the network cable, and the work continues.

Data stays inside.
Tools run inside.
Results stay inside.

Within your systemsIn development

Models and research tools run next to your data.

03 / The risk

Your IP is not the price of AI.

Your IP has value, and other people want it. Competitors want it. Attackers want it. Some AI services train their models on customer data.

Cloud AI runs on systems that you do not own. To use it, you send your IP out. Then you cannot control who keeps it or who learns from it.

See how your IP stays inside

04 / Keep the value

The models change. Your knowledge stays.

Your company must own the value that it makes with AI. Keep your research, your tools, and your checked results. Build on them when better models arrive.

Build with us

05 / Research in practice

What can your team do next?

Bring your question

Engineering

Why did this part fail?

The knowledge: Incident reports. Test data. Design changes.
The work: Compare past failures. Find the causes that fit this case.
The result: A report with sources, open questions, and tests for an engineer to review.

Research & development

What do we test next?

The knowledge: Lab notes. Test data. Past studies.
The work: Compare results. Find useful patterns. Check an idea with analysis tools.
The result: A research plan with sources and clear steps for the team to review.

Operations

Why did this process change?

The knowledge: Process records. Audit reports. Change approvals.
The work: Find the reason for a past change. Check if that reason still applies.
The result: A clear record of the decision, its sources, and questions for the process owner.

Software

Where did this defect start?

The knowledge: Source code. Change history. Defect reports.
The work: Follow the defect through the code. Find the change that caused it.
The result: A report with the cause, the related changes, and tests for a developer to review.

These examples show the work that we want to support. They are not a live product demo.

06 / Build with us

Bring a hard problem. Keep your IP.

We look for enterprise teams to build with us.

What must your team find, test, or make? Tell us about the task and about your rules for private data.

Talk about your project [email protected]