Machines ofConsequence

Your data lives in systems that don’t talk to each other.

Your organization already holds the intelligence it needs. It is spread across silos and legacy systems, so no one can see all of it at once.

Critical industries in Europe are left behind in the current tech wave. Because of compliance and legacy, they struggle integrating the latest software and AI models with real operational impact.

We bring regulated organizations legibility and actions of consequence, leveraging the entire power of frontier stacks and models through deterministic execution.

Built for critical environments, Galahad collapses the trade-off between time-to-value, performance and customization.

Your organisation, as a model to act on.

Open the ontology

Built for systems that cannot fail.

Secure by design, for finance, defence and industry.

Every decision leaves a record

Every decision is logged and every approval traceable to a person. The trail is append-only.

Deterministic

Same input, same output, every time. No hidden state, no drift between runs.

European conformity

A French company. GDPR compliant, AI Act compliant.

Connected to your existing systems

We read your systems where they already are. Read-only by default, writes opt-in, no migration.

Where your data actually runs

Monarch installs inside your own infrastructure, mono-tenant. Every read executes under a role built for the purpose you are acting under.

  • Installed inside your infrastructureMono-tenant, one ontology, one database, on your own machines.
  • Galahad hosts no customer dataWe operate no production tier for your data, anywhere.
  • Permissions live in the databaseOne role per purpose, granted column by column, and the executor is never the table owner. The prompt cannot widen them.
  • Evaluation environments on ScalewayOur demo runs on Scaleway, the European cloud Airbus uses for its proprietary data.
  • This page calls no third partyNo analytics, no trackers, no third-party CDN. Open the network tab and check.

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Our manifestoMachines ofConsequenceMagloire T. Guillet · 49 theses · 13.08.26