Private AI for regulated teams
Aprentiz is a private AI and governance platform in development for regulated teams. It connects your knowledge, sources and workflows—so you can inspect the evidence, own the decision and trace what happens next.
Built in the UKCloud + on-premisesHuman judgement retained
A POLICY REVIEW
Bring the relevant knowledge together.
A named owner. A recorded reason.
The work Aprentiz is built around
Regulated teams need to know which sources apply, what the evidence supports and who is responsible for the next step. Aprentiz brings those questions into one connected workflow.
Explore the platformUK advisory and wealth workflows, with compliance, legal, operations and technology leaders shaping the questions.
Bring a defined regulatory change together with your policy and evidence. Establish the scope, inspect the sources and identify what still needs a decision.
A review record with cited sources and visible gaps.
Give evidence requests, policy changes and control tests a named owner. Keep the rationale, retest and later reconsideration connected to the original question.
An accountable path from finding to follow-through.
Test a professional workflow before implementing it. Qualify the private AI, controls, integrations and recovery around the work you actually need to do.
A workflow and implementation contract worth testing.
From question to follow-through
Follow a fictional policy review through four steps. The purpose is practical: a clear scope, inspectable evidence, a human decision and a next action that stays connected.
A team needs to review a policy after a change. First, name the sources, business scope, decision owner and evidence the review will need.
A defined review, with a clear owner and boundaries.
REVIEW BRIEF
The scope is explicit before analysis begins.
Compare the admitted sources and policy. Separate what the evidence supports from what is missing or still needs professional interpretation.
A source-linked evidence map, including unresolved questions.
EVIDENCE MAP
The relevant policy passage is located.
The record of the control test is missing.
Application to the defined scope needs review.
A missing record cannot become positive assurance.
The responsible person inspects the evidence and records a decision, a hold or a request for more information. AI-assisted analysis informs that judgement.
An attributable decision, its rationale and its limitations.
HUMAN DECISION
Request the missing test record before deciding whether to change the policy.
Assign the next action, test the proposed change against the agreed criteria and retain the result. Reopen the question when new evidence changes its basis.
An action and retest history that can be reviewed later.
ACTION & RETEST
The earlier decision remains part of the record.
An illustration of the operating model, using a fictional scenario. No live analysis or professional determination is performed.
The Aprentiz Proving Ground
Two connected environments are designed to turn a professional process into a testable operating model—and then into an implementation with evidence behind it.
Workflow Proving Ground
Define the outcome, people, sources and exceptions. Test how analysis and human judgement fit together before automating the process.
Implementation Proving Ground
Translate the accepted workflow into requirements, controls, integrations and tests. Qualify changes against the original evidence and acceptance criteria.
Private AI, governance, source verification and retained evidence support both Proving Grounds.
Bring intelligence to your boundary
Cloud or on premises, the design is the same complete Aprentiz platform: private inference, governed knowledge, workflows, GRC, source verification and recovery.
In an agreed cloud environment
The complete Aprentiz platform in an approved cloud account, region and operating boundary. Private models, knowledge and evidence stay within the agreed processing routes.
Explore this profileOn your approved infrastructure
The same platform on customer-approved hardware, with locally governed data, inference and administration. Ordinary private work is designed to continue without a central model service.
Explore this profileBoth profiles are in development. Each environment is qualified for its data, access, security, workload and recovery requirements before use.
Understand private AIof responding financial services firms were already using AI in the Bank of England/FCA’s 2024 survey.
Read the 2024 researchThe opportunity now
The valuable next step is a workflow your organisation can understand, challenge and improve. Start with one important piece of work. Use what it teaches you to build the next.
Explore our research approach