Sovereign AI, on your data
Your models, your data, your perimeter
Conversational assistant, augmented search and automatic labeling: Hyperfluid AI works directly on your data, without ever sending it to an external model. European models (Mistral) or self-hosted (vLLM, KServe), all the way to air-gapped networks.
Specifications
Models
Mistral, vLLM, KServe
Data access
Via unified API (MCP)
Data
Never exported
Deployment
Up to air-gap
Use cases
Query your data in natural language
A conversational assistant turns your questions into queries on your tables, with your access rights enforced on every query.
From natural language to SQLAugmented search over your documents
Progressive retrieval first explores summaries, then the relevant content, instead of plain vector similarity.
Beyond classic RAGAutomatic labeling at scale
Automatically classify and annotate columns and tables with AI. Labels enrich your data catalog and drive your access policies.
Batch labelingIn action
The analyst querying their data
An analyst wants to explore sales without writing SQL
- 1 Open the AI assistant in the console
- 2 Ask the question in natural language
- 3 The AI queries the tables via the unified API, inside the perimeter
- 4 Get the answer, with access rights enforced
Answer obtained without exporting a single record
The team structuring its assets
Thousands of columns to document and classify
- 1 Launch an AI labeling pipeline
- 2 The AI proposes labels and categories in batches
- 3 Labels feed your data-catalog governance
- 4 Access policies build on these labels
Data assets documented and governed
Key benefits
Ready to put AI to work on your data?
Discover how Hyperfluid sovereign AI leverages your information assets, without compromising them.
Request a demo