●Private & Secure AI
Your most valuable data — client files, patient records, designs, source code — can power AI without ever leaving your control. We deploy AI inside your own infrastructure, on your terms, and hand you a written record of exactly where every byte goes.
inside your boundary
01The wall most companies hit
of enterprise IT leaders name data privacy as the single biggest barrier to adopting AI — ahead of cost, ahead of integration.
You want AI working on your most valuable information — contracts, patient records, designs, code, client books. But every prompt to a public AI service crosses your network boundary into someone else's infrastructure. For a law firm, a clinic, or a regulated business, that's not a technicality. It's the reason the project never starts.
And it's not theoretical: most employees already paste company information into AI tools, usually through personal accounts, with no oversight at all. The answer isn't to avoid AI. It's to run it where your data already lives.
02The difference, drawn
The same workload, two architectures. One sends your data out. One keeps it in.
Typical AI setup
exposedEvery prompt crosses your boundary into someone else's cloud.
The Palanax way
containedThe model runs inside your boundary. Nothing leaves.
03What "private" actually means here
Not a privacy policy. Not a checkbox in someone else's console. A real architectural choice about where the model runs and where your data goes.
Self-hosted, on your hardware.
Open models (Llama, Qwen, Mistral and others) served on your own servers with vLLM, Ollama, or TGI. Your data never leaves the building.
Private cloud tenant.
When on-premise isn't practical, models deployed in your own cloud account, in-region, with no third party in the data path.
Air-gapped and audited.
For the most sensitive environments — isolated, logged, and reviewable.
In every case: access controls, full audit logging, and monitoring built in from the start, not bolted on after.
04The artifact nobody else gives you
The artifact nobody else gives you
A written, plain-language record of exactly where your data lives, what touches it, and how it maps to the regulations you answer to — the proof you can show your board, your auditor, or your regulator.
Competitors claim their setup is secure. We hand you the proof, in writing, that you can show your board, your auditor, or your regulator — mapped to DPDP, GDPR, and your sector's rules.
05How we engage
A ladder, not a leap. Each rung proves the next.
- 01
AI Exposure Check
Where is your data already flowing into AI tools today? We find the top risks and show you what a safe setup looks like.
Free · 30 minutes - 02
Shadow AI & Exposure Audit
A full map of AI usage across your organization, a data-flow diagram, ranked risks, a usable safe-AI policy, and a recommended architecture. The output is the spec for everything that follows.
from £1,500 · 1–2 weeks - 03
Secure AI Workspace
A private AI workspace for your team: self-hosted or private-tenant models, access controls, usage policy, and staff training. Fixed price.
from £3,000 · 2–3 weeks - 04
Private AI Workflows
One real workflow on your sensitive data, deployed inside your environment — private retrieval over your documents, secure extraction, an internal knowledge assistant — with the compliance annex included.
from £6,000 · 3–5 weeks - 05
Private / Sovereign Deployment
Full on-premise or private-cloud LLM infrastructure: serving, monitoring, audit logging, and integration. The destination, sold once the groundwork is proven.
from £15,000
Prices shown in GBP. India pricing available — ask us.
06A fair question
For some teams, a hyperscaler's private offering is exactly right — and we'll tell you if it is. But three things send clients to us instead.
Find out where your data is going
You'll learn more about your own AI risk in half an hour than most companies know in a year.
No retainer required to start. No obligation after the review.