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The operating system for AI.

One context layer. Any model. Your servers.

Every employee gets a personal AI assistant that knows their company.

On-Premise · Model-Agnostic · European

The problem with enterprise AI

Knowledge is scattered

Documents in SharePoint, notes in heads, processes in wikis. No employee has the full picture.

AI has no context

Companies use ChatGPT, but AI doesn't know their processes, customers, or internal language.

Data sovereignty at risk

European companies depend on US cloud providers. GDPR compliance is questionable.

Three layers. One system.

Claude Mistral GPT Open Source
Layer 2

Personal Brain

Each employee's individual context: writing style, preferences, meeting notes, personal workflows. AI that adapts to you.

Layer 1

Company Brain

The organization's collective knowledge: processes, documentation, internal language, institutional memory. The foundation everything builds on.

The intelligence layer is replaceable. The context stays. Switch models anytime without losing what makes your AI valuable.

What makes Contextell different

Model-Agnostic

Claude today, Mistral tomorrow, open-source next week. The intelligence is replaceable, the context stays.

On-Premise

Your data on your servers. No US cloud. GDPR-native. AI Act ready.

Personal AI for every employee

Each team member gets a personal brain connected to company knowledge. Productive from day one.

Growing value

The longer Contextell runs, the smarter it gets. Context accumulates. Switching costs rise naturally.

Built in Berlin

Backed by the Berliner Startup Stipendium. Built at HTW Berlin. European by design. Proof of concept running productively since Q1 2026.

BSS Stipendium HTW Berlin European by Design

Built for knowledge-intensive industries

European mid-market. 100 – 2,000 employees.

Energy

Legal

Finance

Engineering

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a brain?

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