Why Corentis?

A practical checkpoint for AI adoption in regulated workflows.

Corentis Shield is built for the moment AI moves from suggestion to action.

AI is moving from chat to action.

AI agents are starting to draft replies, update records, recommend decisions and trigger workflows. That makes them useful, but it also means organisations need a way to check outputs before they become real-world actions.

62%

of surveyed organisations are at least experimenting with AI agents.

Source: McKinsey, The State of AI 2025.

50%

rise in worker access to AI in 2025.

Source: Deloitte, State of AI in the Enterprise 2026.

21%

rise in AI-related incidents from 2024 to 2025.

Source: BCG, When AI Acts Alone, 2025.

$4.3bn

in estimated losses associated with AI-related risks across one EY sample.

Source: EY, Responsible AI survey 2025.

The risk is unchecked action.

A risky AI output is easier to manage while it is still a draft. The risk grows when it reaches a customer, a case record, a workflow or a live system. Once an AI action has happened, the cost is usually higher, the fix is slower and the evidence trail is harder to rebuild.

Customer support advisor wearing a headset and working on a laptop.
Human workflows
Sensitive workflows are still human workflows.

payment-pressure message sent to a vulnerable customer

complaint closed without enough evidence

CRM update added without review

guidance response drifting into advice

workflow action triggered too soon

Selected evidence signals

The case for Corentis sits across regulated-service pressure, accelerating AI adoption and the need for operational AI governance.

FCA complaints data

UK financial services firms received 1.85m complaints in 2025 H1.

This was a 3.6% increase from 2024 H2. Since 2021 H1, complaints have stayed relatively constant between 1.7m and 2.0m.

Financial Conduct Authority, 23 October 2025

McKinsey global AI survey

88% of respondents in McKinsey’s 2025 global survey reported regular AI use in at least one business function.

Only approximately one-third reported that their companies had begun scaling AI programmes.

McKinsey & Company, 5 November 2025

IBM / Ponemon

63% of breached organisations lacked AI governance policies to manage AI or prevent shadow AI.

IBM also reported that 97% of organisations with an AI-related security incident lacked proper AI access controls.

IBM / Ponemon Institute, 2025

The checkpoint before the real world.

Corentis Shield checks the AI output, reviews the context, routes human review and records evidence before action. It gives teams a simple decision point: proceed, review, escalate or block.

AI output

Corentis Shield check

Proceed / Review / Escalate / Block

Evidence recorded

Why the action boundary matters

A lot of AI governance focuses on policies, model selection and post-event monitoring. Corentis focuses on the point where AI output is about to become operational action. That boundary is where review, escalation and evidence need to happen.

1

AI proposes

Draft reply, recommendation, case update or workflow action.

2

Corentis checks

Policy, risk, context, approval and evidence requirements.

3

Decision returned

Proceed, review, escalate or block before action.

4

Human review

Sensitive or uncertain cases go to the right person.

5

Evidence logged

Proposal, reason, decision, reviewer and timestamp recorded.

Assurance before action, not paperwork after the fact.

Corentis Shield is designed as a practical AI assurance mechanism. It does not just document AI risk after a system is live. It helps turn AI outputs into reviewable, evidence-backed decisions before they reach customers, teams or systems.

novel assurance mechanism
pilot-ready
helps identify risks from AI systems
creates reviewable evidence
supports safer adoption

Not just governance. Not just guardrails.

Generic AI governance

  • documents risks
  • tracks policies
  • supports oversight
  • often sits before or after deployment

Prompt guardrails

  • steer model responses
  • filter unsafe content
  • catch some input/output issues
  • may miss business context

Corentis Shield

  • checks output before action
  • reviews policy, risk, context and evidence
  • routes review or escalation
  • blocks risky outputs
  • records the decision

Most tools help describe the risk. Corentis creates the checkpoint before the risk reaches the real world.

One checkpoint pattern. Many regulated workflows.

Financial-services complaints and vulnerable-customer cases are the first proof point. The same checkpoint pattern can extend to insurance claims, pensions servicing, healthcare administration, housing, public-sector casework and enterprise customer operations.

financial services
insurance
pensions
healthcare admin
housing
public sector
enterprise operations

From product to regulated AI output benchmark.

Every pilot can strengthen a larger assurance asset: scenario packs, risk labels, expected decisions, evidence requirements, model-output results and benchmark reports. Over time, Corentis can help build a reusable way to test AI outputs in regulated workflows.

high-value scenario and data asset
evaluation harness
benchmark reports
reusable methodology
wider UK AI assurance ecosystem

Why fund this now?

AI agents are moving toward action. Regulated workflows need control before action, and evidence cannot be an afterthought.

Corentis starts with a concrete financial-services wedge: complaints and vulnerable-customer workflows. Funding would help validate the control pattern, build reusable evaluation assets, strengthen evidence generation and prepare design partner pilots without claiming the pattern is fully proven today.

A clear route from review to deployment.

Corentis can start with focused assurance reviews, grow through design-partner pilots, and scale through recurring software, API usage, private gateway deployments and sector-specific assurance packs.

AI Output Check Review

Assurance Lab pilot

Corentis Shield deployment

API / SDK / webhook / private gateway

Sector-specific assurance packs

The next step is validation.

The next phase is to validate Corentis Shield with design partners, expand the scenario library, harden the API/private gateway path, and generate pilot reports that show how AI outputs can be checked before live use.

Team of professionals reviewing a laptop during a business meeting.
Design partner pilot
Start with one workflow, review the evidence, then decide what to deploy.

Help test the checkpoint layer for AI agents.

Read the evidence packs

Investors and strategic fundersAvailable

Investor Overview PDF

A warm, commercial overview of the Corentis opportunity, the first wedge and the path from validation to regulated AI infrastructure.

Best for investors and strategic funders who want the market logic, wedge and proof plan in one place.

Product and technical readersAvailable

Runtime Checkpoint Explainer PDF

A plain-English explanation of how Corentis creates a control point between AI-generated intention and real-world action.

Best for readers who want the product idea quickly and clearly.

Strategic funders and investorsAvailable

Vision & Funding Readiness Overview PDF

A public-facing overview of the Corentis vision, the timing, the first wedge and the validation path for serious funding conversations.

Best for funders and investors who want to understand why now is the moment to build AI checkpoint infrastructure.