OAIS Sentinel Guard
Enterprise AI Governance Platform

Govern AI Before
It Governs You

Sentinel Guard enforces organizational policy at the point of AI interaction — before data leaves your boundary, before actions execute, before risk materializes.

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OSFI E-23 Compliance Deadline
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May 1, 2027 — Mandatory for all federally regulated Canadian FIs
The Problem

Ungoverned AI Is an
Unbounded Liability

Enterprise AI adoption has reached 78% of organizations. Most have no mechanical enforcement over what their AI systems can access, transmit, or execute.

OSFI E-23 Is Non-Negotiable

Finalized September 11, 2025. Every federally regulated financial institution in Canada must establish enterprise-wide model risk management frameworks covering all AI and ML models. Effective May 1, 2027. Non-compliance carries enforceable penalties.

EU AI Act Deadline: August 2026

Organizations operating in or serving European markets face mandatory compliance requirements for AI systems used in regulated contexts. The window to prepare is closing.

Current Solutions Fail Open

Existing tools rely on probabilistic filters, policy documentation, and post-hoc auditing. When an unknown input arrives, the system permits it. When an adversarial prompt bypasses a filter, the failure mode is silent data exposure.

The market has moved from "should we govern AI?" to "how do we govern AI before a regulator or a lawsuit forces us to?"

The Solution

Sentinel Guard

An AI governance platform that sits between your organization's users — or AI agents — and the AI services they interact with. It enforces organizational policy before any AI action is taken.

Pre-Action Policy Enforcement
Every AI interaction is evaluated against organizational rules before execution. Compliance, data protection, and sensitivity controls are applied at the prompt layer — before content reaches any AI platform.
Fail-Closed Architecture
If a policy cannot be evaluated, the interaction is blocked, not permitted. Unknown inputs are stopped by default. Ambiguity resolves to non-action.
Immutable Audit Trail
Every AI interaction, every policy decision, and every governance action is logged with full provenance. Audit trails are append-only and cryptographically verifiable.
Deterministic Containment
Governance is enforced through mechanical gates that are architecturally incapable of being bypassed by the AI systems they govern. This is not a filter layer — it is a containment boundary.
Real-Time Intervention
Policy violations are intercepted and prevented in real time, not flagged for post-hoc review. The system acts before data moves, not after.

What Sentinel Guard Is Not: It is not an autonomous agent, a prediction engine, or a replacement for human judgment. It is a containment and control substrate — governing what data enters and exits AI interactions, and what actions AI systems are permitted to take.

Why Different

Categorically Different

Sentinel Guard does not compete with existing AI governance tools on their terms. It occupies a category they cannot credibly enter.

Filter-Based ApproachesCompetitors Sentinel GuardOAIS
Failure Mode Fails open — unknown inputs pass through Fails closed — unknown inputs are blocked
Bypass Risk High — adversarial prompts routinely defeat filters Zero — execution path is architecturally locked
Governance Layer Post-hoc documentation and risk assessment Pre-action enforcement at the interaction boundary
Audit Integrity Log-based, mutable Append-only, cryptographically verifiable
Worst Case Silent data exposure, regulatory headline A safe action is routed to human review unnecessarily

Existing platforms — Credo AI, Holistic AI, Monitaur, Arthur AI, IBM watsonx.governance — focus on model lifecycle management: risk assessment, documentation, bias detection, and compliance reporting. These are necessary but insufficient.

They address regulatory AI governance (documentation, bias).
Sentinel Guard addresses operational AI safety (deterministic behavior, real-time intervention).

One failure mode costs you a headline. The other costs you a few minutes of an analyst's time.

Market Resilience

Why Demand Survives
Regulatory Uncertainty

The demand story has three legs, not one. Regulation is the strongest today, but it is not the only one.

01

Regulatory Mandates

OSFI E-23, EU AI Act, and anticipated federal AI legislation create enforceable compliance requirements with specific deadlines.

02

Enterprise Liability

Organizations deploying AI agents face a binary choice — governance that is mechanical and deterministic, or liability that is unbounded and inevitable. This risk exists independent of any regulatory framework.

03

Operational Necessity

As AI systems move from experimental to production, enterprises need real-time governance to prevent data exposure, unauthorized actions, and unauditable decisions. The regulatory mapping is a configuration layer, not an architecture rebuild.

Go-to-Market

Beachhead: Canadian Insurance

Concentrated where regulatory pressure is most acute and competition is thinnest — Canadian federally regulated financial institutions, beginning with insurance.

Hard Compliance Deadline

Every federally regulated insurer must have enterprise-wide AI governance frameworks operational by May 1, 2027. The clock is running.

Comprehensive Scope

E-23's definition of "model" explicitly includes AI and ML methods — encompassing LLMs used for underwriting, claims triage, pricing, and customer communications. Third-party models included.

Thin Competition

No established AI governance vendor has purpose-built solutions for Canadian regulatory requirements. The incumbents focus on EU AI Act and US frameworks.

Embedded Distribution

OAIS's founding team brings senior experience from within the Canadian financial services industry, with direct relationships into target buyer organizations.

Validation

Credibility Markers

Architecture Validated

Undergone validation testing including deliberate adversarial input injection. The system correctly identifies, intercepts, and prevents policy violations under hostile conditions.

Patent Pending

Core governance mechanisms are the subject of patent filings, establishing defensible intellectual property.

Active Pilot Conversations

Warm engagement with federally regulated Canadian insurers through co-founder relationships within the beachhead market.

Market Validation

Recent AI governance acquisitions valued at ~40x revenue on ~$100M ARR. Strategic acquirers are paying premium multiples, confirming every major platform now needs this category.

The Team

Built by Practitioners,
Not Observers

Founder & Architect

Daniel Fruman

Designed and built the Sentinel Guard architecture. Over a decade of hands-on experience in healthcare privacy compliance and data governance, building and enforcing governance systems in regulated Canadian environments. The architect who understands the regulatory problem from the inside.

Co-Founders

Founding Team

Three co-founders with senior experience spanning institutional investment management, insurance operations, and financial services. Combined expertise in enterprise governance, regulatory compliance, actuarial science, and risk modelling — drawn directly from the industries Sentinel Guard is built to serve.

Request a Pilot Briefing

If your organization is preparing for OSFI E-23 compliance, evaluating AI governance solutions, or assessing operational risk from AI deployments, we welcome a confidential conversation.

Or reach us directly at info@oais.ai