Self-hosted & edge AI
Intelligence that stays on your premises.
Maurits Embedded Systems helps organisations use private AI that runs locally — in your server room, office, home, or directly on embedded and IoT hardware — so confidential information never needs to leave your control.
Privacy by design — local inference, deliberate architecture
We help you deploy models and pipelines that run where your data already lives: on your own dedicated servers, secure office networks, private appliances, and your own embedded platforms. The objective is simple — powerful AI without exposing your confidential information to someone else's cloud.
- Data residency aligned to your policies — including air-gapped patterns where required
- Operational control: upgrades, logging, retention, and access boundaries you define
- AI governance baked into delivery: roles, approvals, and change control you can evidence
- Edge-first options for latency, bandwidth, and offline continuity
Embedded & edge
Bring inference closer to sensors and controls — leveraging your own local AI capabilities.
Built for teams that need outcomes — not another SaaS dependency
Self-hosted AI stacks
Design, hardening, and handover for on-prem and private cloud inference — tuned to your privacy standards and internal security policies.
Edge deployment
Practical pipelines for offices and devices where bandwidth, latency, or continuity matter — with sensitive prompts and artefacts kept off the public internet.
Security-minded delivery
Architectures that assume sensitive workloads: least privilege, encryption, logging you can trust, and minimised data movement by default.
When AI runs outside of your own systems, your risk profile changes
Cloud assistants can be extraordinarily capable — but they can also route sensitive prompts, documents, and metadata through systems you do not operate. Providers may retain data for safety monitoring, quality review, abuse prevention, or longer-term product improvement — including training and evaluation workflows where human reviewers may be in the loop.
For many teams, the question is not whether a vendor is trustworthy — it is whether your organisation can accept those default data flows at all.
Security best practice, privacy standards, and sensible AI governance
Self-hosted AI only earns trust when the surrounding discipline matches the sensitivity of the data: clear ownership, controlled integrations, retention you can explain, and monitoring that supports investigation without turning every log line into a new risk. We help you keep prompts, context windows, and model outputs inside the networks and devices your organisation already governs.