Patent-Pending Architecture · April 2026

The trust boundary
enterprise AI still lacks

AI adoption in the enterprise is not limited by model capability. It is limited by the absence of a structurally enforced boundary between AI systems and raw sensitive data. Sentridock builds that boundary in hardware.

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62%
Experimenting
23%
In Production
1/5
Have Governance
62%
Experimenting with AI agents
McKinsey 2025 — enterprises running AI pilots
23%
Actually scaling in production
McKinsey 2025 — the gap is structural, not technical
1/5
Have mature agent governance
Deloitte 2026 — yet 74% plan agentic deployment
The Structural Gap

Current approaches
all fall short — architecturally

API guardrails, DLP layers, agent connectors, and model safety tuning all share one fatal flaw: they operate inside the trust domain they are meant to protect.

Approach
Where Control Sits
Remaining Exposure
API Guardrails / DLP
Inside software trust domain
AI still sees raw data before policy fires
Agent / Connector Models
Assumes host + connector trust
Integrity not verified — raw data reachable
Secure Bridges
Access control layer
AI workflows depend on raw-data reachability
Model Safety Tuning
Inside the model only
Bypassed entirely by context injection
Core insight: The weakness is architectural position, not just policy quality.
How Sentridock Works

A closed loop —
six stages, one enforced boundary

The transformation happens before any software path reaches raw data. That is the only position that cannot be bypassed.

01 ——→
01 ↓
Raw Data
Screens, files, apps, sensors
02 ——→
02 ↓
Perception
Display framebuffer or HID capture
03 ↓
03 ↓
Trust Boundary
Hardware-enforced · Non-bypassable
Hardware Enforced
←— 04
04 ↓
Transform
Many-to-one irreversible sanitization
Hardware Enforced
←— 05
05 ↓
AI Reasoning
On protected abstractions only
↑ 06
06
Controlled Actuation
Governed output back to enterprise
↩ Loop closes — back to Step 01
⬡
Why hardware? Software guardrails live inside the trust domain they protect — and can be bypassed. A hardware-enforced boundary is structurally external: the transformation happens before any software path reaches raw data.
Why Sentridock

Control over conditions,
not just connections

✕ Conventional AI Stack
Connects AI to systems
  • Focuses on connecting AI to systems inside the software trust domain
  • Assumes host or connector trust — integrity not enforced
  • AI can reach raw enterprise data before any policy fires
  • Point feature or optional capability — easily bypassed
✓ Sentridock Boundary Model
Defines the conditions under which AI may operate
  • External, boundary-centric control layer — architectural position
  • Makes no trust assumptions — enforces the boundary structurally
  • AI never reaches raw data — mandatory, non-bypassable
  • Infrastructure control plane — not a feature, not optional
This is where moat and enterprise relevance begin. Control over conditions — not just connections.
Early Access

We are building the trust boundary
enterprise AI still lacks

Sentridock is in early design-partner stage. We are working with regulated-industry organisations whose AI ambitions are currently constrained by trust and governance.

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Path A
Seed Investor
Join as a seed investor in Sentridock Inc. Full deck and data room available under NDA.
Path B
Strategic Partner / New BU
Explore IP injection and BU formation. Founder joins as BU Head / Chief Architect.