Every organization should run AI on its own terms.
Language
Vision
Retrieval
AI is consolidating into the hands of a few providers. If someone else can change, revoke, or monitor your AI, it was never yours. deeplit® is the alternative we built.
Founded 2024, Delft
Full sovereignty over your AI
100%
Single-tenant
Compliance by design
GDPR · EU AI Act
Designed to support both from day one
2 ways to run it
- Language
- Vision
- Voice
- Multi-modal
- RAG
5
One platform, every modality
Design decisions
Committed once, held since
- 01Your data, never ours
- 02No external dependency
- 03A cost you can forecast
- 04No lock-in, including to us
Your data, never ours
Models, queries, and documents stay yours. No third party in the data path.
No external dependency
Nothing calls out unless you allow it. Fully disconnected on your own hardware.
A cost you can forecast
A monthly license on your hardware, or a flat hour on ours. Never per token.
No lock-in, including to us
Open weights, your data, your history, exportable on the day you ask.
Your data, never ours
Models, queries, and documents stay yours. No third party in the data path.
Four commitments behind every design decision.
What we believe
Your data, never ours- No external dependency
- A cost you can forecast
- No lock-in, including to us
What working with deeplit® looks like.
You always get an engineer.
The first conversation answers technical questions.
Clear on what we carry.
Built to support GDPR and the EU AI Act. No compliance overclaims.
Short path to live.
deeplit® Cloud starts the same day, Private in about two weeks.
A company built on one conviction.
Independence as the product.
The longer an organization rents its AI from someone else, the harder it becomes to leave. deeplit® is built so that leaving is never a question, because there is nothing to leave. The infrastructure is yours.
Full control of the whole stack.
Your data, your models, your hardware, your rules. No external dependency, no third party in the loop. deeplit® handles the deployment complexity so you do not need an ML infrastructure team to get there.
Frequently asked questions
deeplit® started as a consultancy, not a company trying to invent a product from scratch. Every design decision in the platform comes from shipping on-premise AI systems into regulated environments. The sectors the team has delivered into include pharma labs, clinical documentation, logistics, finance, and voice-first applications. What is on the website is hardened from what worked. What is not on the website is the things we tried that did not.
Three things that most "private AI" offerings do not do together. First, on your own hardware deeplit® runs fully disconnected from the internet as a first-class mode. No phone-home, no license server, no cloud service the platform calls to keep working. Second, the compliance surface and the MLOps surface are one platform, not two products glued together. Most "private AI" offerings ship model serving and leave access control, audit, retention, and model lifecycle for you to assemble. We ship the whole thing. Third, the team has been inside compliance reviews, change-control boards, and procurement cycles before writing the first line of product code. The platform is designed for how regulated organizations actually work, not how vendors wish they worked.
Which models lead changes week to week. Naming specific models on a website dates the site immediately. Being tied to a specific model would also contradict the whole point: deeplit® is built so you are never locked to one. You choose from open-weight models across language, vision, voice, and multi-modal on your own workload, hardware, and risk terms. We help you evaluate during scoping. Swapping a model later is a configuration change, not a migration.
Your organization is the data controller under GDPR. You carry most of the legal obligations. deeplit® is built so those obligations are readable, documentable, and auditable: access control, audit logging, retention, and data residency are core features, not add-ons. "GDPR compliant" is a property of how a controller operates, not a property of software. We say what is true; we do not stretch the phrase.
Your ML team builds models. deeplit® builds the environment those models have to run in under production conditions: access control, audit logging, retention, identity integration, model lifecycle, rollback, and the tooling that makes validation tractable. That is the better part of a year or more of work your ML team will not be building features during, and most of it is not the kind of work ML engineers want to do. deeplit® lets your team keep their time on the models and the applications. Building infrastructure does not produce business outcomes. Models running against your data do.
