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Proof-of-Trust™ (PoT™)

Patented pre-execution AI validation with cryptographic attestations — block unsafe decisions before they run.

Pre-execution AI validation + cryptographic attestations for finance, healthcare, and regulated systems.

🛡️
USPTO Patent Granted

Cryptographic pre-execution attestation framework for AI decision validation — the only patented multi-dimensional trust protocol.

<100ms
Average Detection Latency
4D
Parallel Validation Dimensions
100%
Pre-Execution Coverage
📋

Proposal

AI Decision Submitted

Validation

4D Analysis <100ms

📊

Trust Score

Pass/Fail Determination

🔐

Attestation

Cryptographic Proof

Try the Demo

What you'll see in <60 seconds:

  • ✓ Live trust score calculation
  • ✓ Cryptographic attestation file
  • ✓ Regulatory compliance log
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Why SentinelPoT

Prevent Failures

Pre-execution validation blocks unsafe AI decisions before they cause damage. Stop errors in finance, healthcare, and infrastructure before they happen.

Satisfy Regulators

Built-in compliance checks and immutable audit trails meet SEC, FDA, FINRA, and HIPAA requirements. Defend your decisions with cryptographic proof.

Protect Reputation

Defensible, explainable, and resilient AI systems maintain stakeholder trust. Deploy AI where consequences matter with confidence.

How Proof-of-Trust™ (PoT™) Works

Four parallel validation dimensions execute in <100ms, blocking unsafe decisions before execution and issuing cryptographic attestations for approved actions.

1

AI Decision Proposed

Agent submits action for validation

2

Parallel Validation

PoG™
PoE™
PoR™
PoC™
3

Trust Score

Composite risk assessment

4

Approve / Reject

Execute or escalate

🛡️

Proof-of-Guardrails™ (PoG™)

What: Policy constraints and hard-stop violations

How: Pre-execution boundary enforcement prevents unsafe actions before they cause damage

Result: Zero tolerance for policy violations

💡

Proof-of-Explainability™ (PoE™)

What: SHAP, LIME, and fidelity metrics

How: Generate machine-verifiable explanations with human-readable narratives

Result: Defend every decision to regulators and stakeholders

🔄

Proof-of-Resilience™ (PoR™)

What: Adversarial testing and drift detection

How: Continuous stress-testing ensures models resist attacks and maintain integrity

Result: Protection against data poisoning and model manipulation

Proof-of-Compliance™ (PoC™)

What: Live regulatory oracle integration

How: Auto-updating rules validate against FDA, SEC, FINRA, HIPAA, GDPR in real-time

Result: Always compliant, even as regulations change

Output: Cryptographic PoT™ Attestation

Every approved decision receives a tamper-proof attestation containing decision hash, validation scores, timestamp, and digital signature—creating an immutable audit trail for regulatory defense.

Real-World Use Cases

How Proof-of-Trust™ (PoT™) would have prevented catastrophic AI failures

Note: The following are hypothetical remediation examples based on publicly documented incidents. PoT™ capabilities are illustrated for educational purposes to demonstrate potential preventative applications.

🏘️

Housing: Greystar / RealPage Rent-Setting Lawsuit ($141M Settlement)

⚠️ The Incident

Greystar and 25 other firms paid $141M to settle claims they used RealPage's algorithm to coordinate rent prices, inflating rents and reducing competition.

❌ Where It Failed
  • Lack of Transparency: No clear rationale for rent increases
  • No Guardrails: Algorithm maximized revenue but ignored antitrust rules
  • No Real-Time Auditability: Issues discovered only after years of harm
  • Consensus Gap: No external validators or regulators in-loop
✓ How PoT™ Would Have Helped
  • PoG™: Encode antitrust rules directly into rent-setting logic
  • PoE™: Rent adjustments tied to machine-verifiable rationale
  • PoC™: Real-time checks via regulatory oracles
  • Consensus Validators: External auditors/regulators validate before execution
  • PoR™: Stress-test system for collusion scenarios
🏦

Finance: Wells Fargo Fake Accounts Scandal ($3B in Fines)

⚠️ The Incident

Wells Fargo created millions of fake accounts to hit sales metrics, leading to $3B fines and reputational collapse.

❌ Where It Failed
  • Lack of Guardrails: Incentives pushed fraud without checks
  • No Auditability: Millions of accounts went unverified
  • Consensus Gap: No external validation of account creation logic
✓ How PoT™ Would Have Helped
  • PoG™: Enforce business logic preventing fake accounts
  • PoC™: Real-time regulatory validation
  • Consensus Validators: Independent auditors required before account creation
⚕️

Healthcare: UnitedHealth / Change Healthcare Ransomware Attack

⚠️ The Incident

In 2024, a ransomware attack on Change Healthcare crippled U.S. medical claims processing nationwide.

❌ Where It Failed
  • No Resilience: Critical systems lacked stress-tested backups
  • No Guardrails: Single point of failure in infrastructure
  • No Real-Time Auditability: Breach unnoticed until widespread disruption
✓ How PoT™ Would Have Helped
  • PoR™: Mandatory stress testing of healthcare workflows
  • PoG™: Enforce segmented controls
  • Consensus Validators: Regulators validate system readiness before deployment
💼

Consulting: Deloitte AI Report Failure (AUD 440k Refund)

⚠️ The Incident

Deloitte delivered a $440k government report that used AI (Azure OpenAI GPT-4o). The report contained fabricated references and citations. Australian government demanded corrections and partial refund.

❌ Where It Failed
  • No Guardrails (PoG™): AI-generated references unchecked
  • No Compliance Validation (PoC™): Regulatory/academic standards not verified
  • No Auditability: Initial draft lacked cryptographic provenance or trust attestation
✓ How SentinelPoT™ Would Have Helped
  • PoG™ (Proof of Guardrails): Automatic validation against trusted citation databases
  • PoC™ (Proof of Compliance): Enforcement of academic and contractual standards before delivery
  • Trust Certificates: Immutable proof of all validation steps for legal and regulatory defense

Competitor Comparison

Reasoning Transparency
SentinelPoT™ ✓ Full Coverage
OpenAI Guardrails ~ Partial
Anthropic Constitutional AI ~ Partial
Others ✗ Limited/None
Pre-Execution Guardrails
SentinelPoT™ ✓ Full Coverage
OpenAI / Google / AWS ~ Partial
MLflow / Kubeflow ✗ None
Compliance Validation
SentinelPoT™ ✓ Full Coverage
Google / AWS ~ Partial
Others ✗ Manual/None
Resilience Testing
SentinelPoT™ ✓ Full Coverage
Major Cloud Providers ~ Partial
MLflow / Kubeflow ✗ External Only
Immutable Auditability
SentinelPoT™ ✓ Full Coverage
OpenAI / Google / AWS ~ Partial
Others ✗ Standard/None
Consensus (Proof-of-Trust)
SentinelPoT™ ★ Unique Patent
All Others ✗ None Available

Other tools check boxes. SentinelPoT™ closes the loop.

Is Your AI System at Risk?

Can you explain every AI decision if regulators audit you tomorrow?

Without explainable AI, you're operating blind. One unexplainable decision could trigger millions in fines.

What happens when your AI makes a catastrophic error?

Post-mortem analysis won't save your reputation. Pre-execution validation prevents disasters before they happen.

Are your AI systems compliant with evolving regulations?

Manual compliance checks can't keep pace with regulatory changes. Automated oracle integration ensures real-time compliance.

Could adversarial attacks compromise your AI decisions?

Hackers are targeting AI systems. Without resilience testing, you're vulnerable to manipulation and data poisoning.

Do you have an immutable audit trail for every AI action?

When litigation comes, incomplete logs destroy your defense. Cryptographic attestations provide bulletproof evidence.

What's your Plan B when AI systems fail in production?

Downtime costs millions per hour. Distributed consensus ensures continuous operation even when validators fail.

Request Executive Brief

Get detailed information about how SentinelPoT can protect your AI systems from catastrophic failures.

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