QentroClient and financial records
Customer, client or financial information that should stay inside your organization.
When Private AI makes sense
Some work is too sensitive for a public AI tool.
Many teams want the benefits of AI but cannot send certain information to an outside service. Private AI setups let you use AI on that work while keeping control of the data.
Proprietary know-how
Designs, pricing, processes and other intellectual property you cannot risk exposing.
Contract or policy limits
Customer agreements or internal policies that restrict where data can be stored or processed.
Operational data
Infrastructure telemetry, asset, vendor and incident records that should stay in your environment.
Deployment options
Match each task to the right setup.
Not every task needs the same level of control. We recommend the simplest setup that protects the data involved, and many clients use more than one.
Local AI
AI models run on hardware you own, on-site or in your data center. Data never leaves your environment.
- Best for your most sensitive information
- Open-weight models sized to the task
- No data sent to outside AI services
Private Cloud
AI runs inside your own cloud account, under your access controls and data policies.
- Best for internal business data
- Scales without buying hardware
- Fits your existing cloud security setup
Hosted AI with Controls
Business-grade AI services, configured with reviewed data terms and clear rules on what goes in.
- Best for lower-risk, everyday work
- Data-use terms reviewed before rollout
- Clear guidance for your team
What you get
Private by design, practical in use.
Privacy is set before anything is built, then carried through to the tools your team uses every day.
A privacy design you approve
- A map of where your sensitive data lives and where it may go
- The right setup for each task: local, private cloud or hosted
- Model selection matched to the work and your hardware
- Limits on what AI can see and which systems it can touch
Working AI your team can trust
- AI assistants, agents or workflows built on your private setup
- Connections to your existing systems and documents
- A person approves sensitive or high-impact actions
- A simple governance guide: ownership, usage rules and reviews
How it works
From sensitive data to working AI.
The same approach Qentro uses everywhere, with privacy as a design input from day one.
Map
Identify the work, the data involved, and what must stay private.
Choose
Select the setup and model for each task, and agree on the privacy design.
Build
Build and connect the AI, test it on real work, and set access limits.
Operate
Train your team, review usage, and keep the setup secure as it grows.
Have sensitive work you want AI to help with?
Tell us what the work is and what data is involved. We will suggest the simplest setup that keeps it under your control.