internal knowledge search
Supported when the architecture needs controlled access to internal information.
PRIVATE AI INFRASTRUCTURE
Use AI with internal data without treating control as an afterthought.
Linden Infrastructure Labs designs private and hybrid AI environments around the sensitivity of the data, the latency the business needs, and the amount of control the organization wants to retain.
USE CASES
Private AI is usually about organizational data, not AI hype.
The right architecture depends on what the business wants the model to see, where the information lives, and how much exposure is acceptable.
RAG
Supported when the architecture needs controlled access to internal information.
private inference
Supported when the architecture needs controlled access to internal information.
document analysis
Supported when the architecture needs controlled access to internal information.
internal assistants
Supported when the architecture needs controlled access to internal information.
speech interfaces
Supported when the architecture needs controlled access to internal information.
controlled model access
Supported when the architecture needs controlled access to internal information.
ARCHITECTURE OPTIONS
- private cloud
- on-premises
- hybrid
- selected external APIs
- model routing
WHY THIS IS DIFFERENT
Private does not automatically mean better. The architecture should match the problem: data sensitivity, cost, model capability, latency, and control requirements.
The point is to make the control boundary deliberate instead of accidental.
PRIVATE AI
Discuss Private AI Infrastructure
Tell us what information the AI needs to touch and how much control you want to keep.