AI Assurance & Control Validation

Prove Your AI Controls Actually Work

Your AI policy says employees can’t put customer data into public AI. We test whether that actually holds — discovering the AI really in use, then proving with synthetic data whether sensitive data can slip through.

Shadow & embedded-AI discovery
Synthetic-data leakage testing
Evidence-graded control scoring
Board-ready assurance roadmap

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How It Works

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Trusted by Leading Compliance Teams, including

AI Assurance & Control Validation

One Assessment, Four Answers

We don't ask if you have a policy — we test whether it holds, using safe synthetic data across every path a real employee could use.

What AI Is Actually in Use?

AI Assurance — What AI Is Actually in Use

We discover the AI really running across your business — sanctioned tools, shadow AI your team adopted on its own, and AI features hiding inside SaaS you already bought.

Shadow-AI & embedded-AI discovery
Risk-based, multi-signal inventory
Inventory-confidence rating you can defend

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Can Sensitive Data Reach It?

AI Assurance — Can Sensitive Data Reach It

We test whether PII, PHI, secrets, and source code can actually flow into AI across every path a real employee could use — paste, upload, browser, desktop, and API.

Five data paths tested, not assumed
Personal vs. enterprise accounts
Synthetic, uniquely-marked records only

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Do the Controls Hold?

AI Assurance — Do the Controls Hold

We validate each control against the strength of evidence behind it — not a questionnaire. A passing technical test earns a high score; a confident interview does not.

Evidence levels E0–E3, not opinions
Proven-exposed gaps surfaced, never averaged away
Mapped to NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10

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What Do We Fix First?

AI Assurance — What to Fix First

You get a board-ready assurance rating and a prioritized 30/60/90 roadmap — most steps actionable with tools you already own, then re-tested to verify the fix.

Board-ready assurance rating
30/60/90 remediation roadmap
Re-test to verify fixes actually landed

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Our Process

How an AI Assurance Engagement Works

A structured, repeatable method — Discover, Map & Tier, Baseline, Validate, Assure, then Re-test. Predictable timeline, evidence at every step.

1

AI Assurance — Discover

We map the AI actually in use across your business — sanctioned, shadow, and embedded inside SaaS you already own — and rate how complete that inventory is.

2

AI Assurance — Map & Tier

We tier each AI use case by risk (T1–T4) so testing effort lands where the exposure is highest, not spread evenly across low-stakes tools.

3

AI Assurance — Baseline

We baseline your existing controls against a 137-control, 12-domain catalog mapped to NIST AI RMF, ISO/IEC 42001, and OWASP — so you see exactly what’s covered and what isn’t.

4

AI Assurance — Validate

We test whether each control actually holds across every data path — using synthetic, uniquely-marked data — and grade every result on the strength of evidence behind it.

5

AI Assurance — Assure

We deliver a board-ready assurance rating, proven-exposed gaps, and a 30/60/90 remediation roadmap — then re-test to verify the fixes landed.

6

AI Assurance — Re-test & Sustain

We re-test the fixes to confirm they actually hold, then stand up continuous AI assurance as new tools, models, and use cases appear.

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Why ioSENTRIX?

We Don't Ask If Your Controls Exist. We Test Whether They Work.

Offensive-security-led validation of your AI controls — using synthetic data, across every path a real employee could use. Governance firms ask; we test.

5

Data Paths Tested, Not Assumed

Paste, file upload, browser, desktop, and API — plus personal vs. enterprise accounts. We test whether sensitive data can actually reach AI on each path, because a control that blocks one often quietly misses another.

0

Real Sensitive Data Touched

We test with synthetic, uniquely-marked records — fake PII, PHI, secrets, and source code. Your real data never leaves your environment or touches ours. Safe by construction.

E0–E3

Evidence Levels, Not Opinions

Every control is graded on the strength of evidence behind it. A confident interview can't earn a high score — only a passing technical test can. Proven-exposed gaps are surfaced, never averaged away.

< 2 wks

From Policy to Proof

A focused baseline in about two weeks: what AI is really in use, which controls hold, which fail, and a 30/60/90 plan you can usually action with tools you already own.

Our Process