How it works
From baseline to defensible evidence
Interrogait applies multiple deep explainability probes to AI models, collecting structured evidence across every test. The result is a defensible, auditable understanding of AI behavior.
What Interrogait does:
1. Baseline and observe
Capture baseline behavior and decision patterns for each model.
2. Analyze explanations
Evaluate model explanations and how they change under scrutiny.
3. Stress-test behavior
Run adversarial probes against structured and unstructured inputs to expose rationalization, deception, and justification signals.
4. Collect evidence
Store behavioral signals, artifacts, and metrics in evidence bundles.
5. Contextualize risk
Map evidence to compliance requirements and trust scoring.
Researchers have found that nearly all frontier LLMs have the ability to strategically scheme, while justifying this behavior.
Deceptive LLM behavior can take various forms, from simple hallucinations through complex, strategic, and covert intent-based mechanisms.
OUR APPROACH
Achieving AI Assurance
Our approach to AI assurance is founded on the simple belief that every AI system that matters must be interrogated before it can be trusted.
Explanations are claims
Explanations are not facts; they're simply claims to be tested
Attribution is just the beginning
Attribution is useful, but it's not causal; understanding behavior requires depth of interrogation methodologies
Adversarial interrogation
Adversarial interrogation allows us to move beyond static testing to dynamic approaches that aim to match or exceed the capabilites of the subject model
Nuanced signals are critical
Detecting rationalization, shifting justification, and various forms of deception require overt targeting of signals that aren't possible with traditional explainability
Intentional stress-testing
Depth of interrogation is not structurally feasible in passive explainability approaches; we aim to systematically stress-test to uncover critical signals otherwise lost
Evidence is paramount
While charts and graphs are useful, our approach aims to capture immutable evidence that's contextualized to regulatory frameworks and directly useful to auditors
DEPLOYMENT
Flexible deployment gives you options
Whether you'd like to run completely on-prem or in the cloud, we have you covered.
Cloud or On-Prem
Interrogait is containerized to run in the cloud or on-premises.
Data Sovereignty
Your data is always your own; no sensitive data ever leaves your control.
Model Discoverability
Models can be discovered in both cloud and on-premises hosting platforms.
Sophisticated Throttling
Multi-threaded and threshold-sensitive testing ensures models are tested efficiently within your defined parameters.
Immutable Architecture
Cases, tests, and evidence are designed to be immutable, ensuring their integrity is protected for use in audits.
Outcome
Behavioral assurance, not just explainability
Interrogait turns AI behavior into a measurable, defensible signal for stakeholders, auditors, and regulators.
Evidence-first approach
Immutable artifacts provide audit-ready proof.
Risk visibility
Trust scores surface emerging issues early.
Actionable outputs
Findings map directly to controls and remediation.