Assurance Overview
Designed for the assurance gap between AI capability and operational approval.
Corentis is being built to help organisations deploy AI in regulated workflows with clearer governance, human oversight, and evidence that can support practical accountability. Policy Composer is the mechanism that turns written policy into visible workflow controls.
The Problem
As AI moves into more important work, organisations need more than raw capability. They need a way to make deployment visible, bounded, reviewable, and easier to justify.
Corentis is designed for the assurance gap between AI capability and operational approval: the space where teams need enough evidence, review structure, and control visibility to decide whether a workflow should proceed.
Without that structure, useful pilots can stall, governance teams struggle to assess what is happening, and evidence becomes fragmented across systems and teams.
What Corentis Adds
Corentis is designed to add deployment discipline around AI-supported workflows through testing, approval steps, runtime visibility, and evidence generation.
The aim is practical accountability: clearer control visibility for organisations and review-ready outputs for the people asked to assess what happened. Policy Composer helps by translating plain-English policy into review gates, escalation logic, blocked actions, and evidence requirements.
Bounded Deployment
The product is designed for controlled, reviewable use rather than open-ended automation.
That matters for organisations, advisors, and public-support reviewers who need to assess seriousness, operational realism, and risk awareness.
one workflow at a time rather than broad, unmanaged automation
human oversight at points where review or escalation is required
clear records of approvals, overrides, and notable exceptions
review-ready outputs that support audit, assurance, and governance work
Oversight Flow
How control, review, and evidence connect in practice
This sequence is intended to show how governed deployment becomes reviewable operational behaviour rather than a vague governance claim.
01
Workflow is defined
The use case, policy conditions, and points of human oversight are made explicit before operational use begins.
02
Review and control logic is applied
Testing, review gates, escalation rules, and deployment conditions are attached to the workflow rather than left implicit.
03
Live use remains visible
Exceptions, approvals, overrides, and notable events are recorded as the workflow operates.
04
Evidence supports accountability
Outputs can be exported in a form that supports governance meetings, assurance review, audit support, or procurement scrutiny.
Illustrative Oversight Output
A clearer view of what review-ready accountability can look like
Shown here as a prototype-style surface so the assurance case is easier to assess at a glance.
Controls
Workflow conditions mapped
Policy rules, review requirements, blocked actions, and escalation logic are attached to the workflow before operational use.
Oversight
Human review stays explicit
Named reviewers can approve, reject, override, or escalate outputs where scrutiny is needed.
Runtime
Notable events remain legible
Exceptions, overrides, and alerts are surfaced as operational events rather than left implicit.
Evidence
Exports support later review
Review packs and Evidence Vault artefacts can be shaped for governance meetings, procurement review, internal assurance, or audit support.
Prototype event trail
Intended to show the kind of reviewable workflow state Corentis is being built to expose.
01
Sensitive action routed to approval gate and unsafe direct send blocked
02
Runtime exception preserved with review context
03
Evidence bundle prepared for assurance discussion
Current Product Stage
What this page is showing and what it is not claiming
This page is intended to help reviewers understand the practical governance direction of Corentis without confusion about maturity or status.
Current stage
01
Early product direction with a working V1 demo
Corentis is being presented at an early stage with a careful, bounded claim posture and a working local V1 demo in financial services.
Exists now
02
Illustrative governance views plus interactive workflow proof
The current materials show prototype process logic, a working local complaints-assistant demo, worked examples, and sample evidence framing rather than claiming live customer deployment.
Designed to do
03
Support review and accountability
The product direction is to make important workflows easier to inspect, review, and justify later.
Claim discipline
04
Deliberately careful scope
The product is framed around bounded workflow control, not broad promises about automating regulation or removing human judgement.
What Corentis Is
- A governance and assurance layer around AI-supported workflows
- A way to turn plain-English policy into operational controls, review gates, escalation logic, and evidence requirements
- A way to add human oversight, review gates, and clearer deployment discipline
- A source of review-ready outputs that support accountability and audit support
What Corentis Is Not
- Not a claim that regulation can be automated away
- Not evidence of live customer deployment or production operation
- Not a generic promise that AI can be trusted without careful workflow design
- Not a substitute for human accountability in important deployment decisions
- Not regulatory approval, endorsement, or a replacement for legal or compliance judgement
Human Oversight
Corentis is being built on the assumption that important AI-supported workflows still require human oversight. Review gates, escalation points, and approval logic are central to the product direction.
That makes it easier to understand where judgement stayed with people rather than being obscured by the surrounding process.
Evidence And Audit Support
Corentis is intended to generate evidence trails that support governance meetings, internal assurance, audit support, procurement review, and other scrutiny-facing processes.
The goal is not to create more paperwork. It is to make the evidence that already matters easier to collect, structure, and reuse.
Public-Interest Framing
The public-interest case is practical rather than rhetorical.
If advanced AI is going to be used in important workflows, organisations need better ways to understand how it is being deployed, where human oversight remains, and what evidence can be shown later.
Corentis is being built to help meet that need in a way that is commercially useful, operationally grounded, and careful in its claims.
Next Step
Continue with an assurance-focused discussion if the control posture looks credible.
The most useful next conversation is usually about policy-to-control translation, human oversight points, evidence expectations, and why the current scope is deliberately bounded.