Modern AI should not cost you your privacy. Harp Guard builds language-model solutions where your data lives — on your own hardware, inside your own network. From the first design session to the running deployment, one principle holds: what is yours stays yours.
Three deployment models — you decide where your data may go.
Self-hosted, on-premise AI: the model and the application run entirely on your own hardware, under full data sovereignty.
For regulated and confidential data: legal, medical, HR, trade secrets.
Local and cloud combined: sensitive data stays on-premise while compute-heavy work scales to the cloud.
When you want frontier-model quality without exposing the sensitive parts.
Vetted cloud models with encryption and EU data residency, configured by us for GDPR compliance.
For public-facing content and low-risk automation.
2–3 weeks, fixed scope
We map your data, constraints, and use case.
Deliverable: a written recommendation — models, hardware, data flow, and a realistic cost estimate. Usable even without us.
Fixed price — coming soon
4–8 weeks
A working deployment on your infrastructure, with real data and a small group of users — measured against success criteria agreed in advance.
Deliverable: a running pilot and a criteria-based decision — continue, adjust, or stop.
ongoing
Either we run the system — monitoring, updates, model swaps — or we train your team and hand over the keys.
Deliverable: a system you own — no vendor lock-in.
After every step, you decide whether to continue. Everything built so far stays yours — it runs on your infrastructure from day one.
Tell us about your project and your data constraints — we will propose the safest architecture that fits.
Placeholder bio. A few words about this developer — background, role on Harp Guard, and what they care about most.
He has spent seven years at Prusa Research building firmware for 3D printers used all over the world — software that has to work reliably and securely. He brings the same approach to implementing local and hybrid LLM solutions.
