Data & Lakehouse
Data you can query, trace and move.
- Medallion architecture, data vault, modelling
- ETL, OCR, document ingestion
- Iceberg lakehouse, Trino engine, catalogue and lineage
- Streaming and high-volume processing
Critical systems engineering · Montpellier, France · since 2024
Long-term embedded engineering, architecture audits, support across your whole open source stack — on systems that are not allowed to fail. And because you only run well what you understand, we build the internal cloud we deploy on your side.
Our product
Our expertise
Data, security and governance, artificial intelligence. Three fields we design, audit and operate.
Data you can query, trace and move.
Architectures where a leak is not an option.
Your models on your side, your data never leaves.
Open source
BUSL-1.1 · Apache-2.0 au 18 août 2030
An S3-compatible authorization gateway that applies an OPA/ABAC policy to every request before re-issuing it to storage under a per-tenant identity.
This is not a byte proxy with an authorization hook bolted on: the request is deserialized into a typed value, the decision is made on that value, and the same value is re-issued to storage. Of the 99 protocol operations, 23 are enforced and forwarded, 76 refused — there is no third category. A test fails if the table and the documentation drift apart.
MIT OR Apache-2.0
A gRPC client for SideroLabs Talos, with mTLS by default and a typed API generated from the official proto files.
Talos has no shell: you do not log into it, you talk to it. We needed this client to operate our clients' clusters.
Apache-2.0
A Trino client for Rust, with authentication and the spooling protocol.
Written and maintained by our engineers. Used in production inside Hyperfluid.
Apache-2.0
An authentication and identity management server, written in Rust.
A community project we contribute to and sponsor.
Our open source expertise
Every item on this list runs at a client under contract, runs inside Hyperfluid, or falls within our support contract. None is here on the strength of having read about it.
The problem
A modern critical platform needs, at the same time: someone who knows the lifecycle of a cluster on an immutable system, someone who can size distributed storage, someone who has already watched a query engine collapse under load and knows why, someone who writes authorization policies rather than firewall rules, and someone who knows what it costs when a model does not fit on a single card.
Each of those profiles exists in small numbers. All five on the same team, available at the same time, in your labour market and on your salary scale: no. This is not hard recruitment, it is recruitment that does not conclude — and while it does not conclude, the platform runs anyway.
So what we rent is not engineering hours, it is a combination that already exists. It works together, it runs these components in production elsewhere, and it wrote part of the tooling it uses. Our engineers move into your teams for as long as it takes, and what they know stays when they leave. ▪
Missions
Quatre engagements en cours ou clos, décrits par la pile qui tourne et par ce qu'elle a produit.
Forward Deployed Engineer · ongoing, more than 12 months
An internal data platform rebuilt as code, as a GitOps flow, and self-service.
Advisory and implementation · ongoing
A Kubernetes base on an immutable OS, and a GPU inference chain for public research.
Sovereign cloud · ongoing
A data and inference cloud operated under public control.
Data & AI · fixed-term engagement
A heterogeneous document base made searchable, every answer citing its document.
Get in touch
Three paths, depending on what you are after: Hyperfluid, engineers embedded in your teams, or a data stack or security audit. The address below reaches the engineers directly.