AI no longer just answers.
It enters decisions, uses tools and produces effects on business processes. When a diagnosis, an assessment or an automated action has real consequences, it is not enough for the answer to sound convincing.
A convincing answer is not yet a verified answer.
One principle. Three levels of control.
Quvant brings evidence and verification to the transition between what AI produces and what an organization decides or allows to be executed.
01DECISIONS
What supports the decision?
Verify what supports an AI decision.
Quvant Review examines evidence, alternative hypotheses and limitations before a conclusion is used, approved or defended.
02CONTROLS
Does the control respond?
Observe how a control responds.
Control Validation subjects a declared control to an agreed test and makes the test conditions and observed response inspectable.
03ACTIONS
May it act now?
Quvant Auriga
Before an action takes effect, Auriga is designed to determine whether it may proceed, should be escalated for approval, or should be stopped.
In development
Discover Quvant Auriga →
Quadriga examines. Auriga governs.
From verifying decisions to governing actions.
Quvant Review and Control Validation are the paths to start from. Operational governance of actions is the level Quvant is building.
Not another answer: the basis to re-examine it.
Decision · Evidence · Alternatives · Limitations · Integrity
Quvant organizes the elements needed to understand on what basis a result can be used and what still requires verification.
SYNTHETIC EXAMPLE
“Connection pool saturation.” But deadlock has not been ruled out.
- CANDIDATE CONCLUSION
- Connection pool saturation.
- EVIDENCE
- The available evidence chain is consistent and referenced in the record.
- OPEN ALTERNATIVE
- Deadlock on a long-running transaction.
- STATUS AND LIMITATIONS
- Partial consensus. Not validated for regulatory submission.
Synthetic example. Not a customer case or evidence of accuracy.
Explore the full record →
Quadriga. Dissent is part of the method.
Quadriga coordinates four AI functions on the same case, each with a distinct responsibility. One formulates the hypothesis, one challenges it, one recomposes the analysis and one verifies the candidate conclusion.
FORMULATE · CHALLENGE · RECOMPOSE · VERIFY
The goal is not to produce more answers. It is to make evidence, alternatives and limitations visible before a result is used.
Four required functions. The result is complete only when all four have fulfilled their role.
PRODUCT PREVIEW
Inside a Quvant Review
A demonstration case shows how a conclusion is examined through four separate responsibilities while keeping evidence, alternatives, limitations and stop conditions visible.
Static preview with synthetic data. This is not a live session and contains no customer data.
- Demonstration case
- Review of a conclusion about an access incident
- Status
- Review completed
Synthetic dataCandidate conclusion
The access control operated as expected.
Quadriga
Analyst
Separates available facts from assumptions and identifies what supports the conclusion.
Critic
Looks for contrary evidence and alternative explanations that could change the outcome.
Synthesiser
Reconciles what holds, what remains uncertain and what requires further verification.
Blind Validator
Evaluates the original input and candidate conclusion without receiving the preceding debate.
Demonstration outcome
HALT — insufficient evidence
The conclusion is not promoted because independent evidence that the control reacted in the observed case is missing.
Reviewable record
Observed
Not demonstrated
To reopen
For those accountable for the result.
Quvant is designed for those who must use, approve or justify an AI-supported decision, and for those who must verify the controls governing automated actions.
CTOs, CISOs, engineering and security leaders, risk, internal audit and compliance — together with the consultants, MSPs, MSSPs and integrators who support them.
B2B software, digital services, cybersecurity and suppliers to regulated organizations are the first contexts in which Quvant can make its value immediately observable.
When Quvant comes in.
Before closing an incident, downgrading a vulnerability, using an AI analysis in an audit or relying on a software control without observing its response.
Monitoring, governing and verifying are not the same thing.
Guardrails enforce boundaries.
Observability shows what happens.
AI governance platforms organize policies, risks and controls.
Quvant examines the evidence behind a decision and the observed response of a declared control.
These functions can coexist within the same system. They answer different questions.
When control must be demonstrable.
AI Act · NIS2 · DORA
Auditors, customers, management and authorities may ask on what basis an AI decision was used, which controls were in place and what was actually verified.
Quvant makes evidence, alternatives, test conditions and result limitations inspectable.
Quvant supports verification and governance. It does not certify regulatory compliance.
WHAT WE ARE BUILDING
Control before AI produces real effects.
Quvant is evolving towards an AI Control Plane that applies policies, approvals and evidence to AI agent actions before execution.
Payments · Email · API calls · Tool use · System changes
Each action may be allowed, blocked or referred to a person, leaving a verifiable record of the decision.
Quvant starts with the verification of decisions and controls. This is the operational level we are building.
THE FIRST STEP
Bring a real decision or control.
Tell us what the AI produced, what you need to decide or which control you want to verify. We will help define the right scope and path.
The engagement is led directly by the founder, with experience in auditing, management systems and the application of AI to verification and control processes.