Decide what is worth doing
Identify the business or public-service problem, test feasibility, understand risk and choose whether to build, buy, integrate, defer or stop.
IMPLEMENTATION + ASSURANCE
Implement artificial intelligence you can defend.
DDAI helps public bodies, enterprises and artificial-intelligence suppliers choose, procure, build and operate systems with clear human accountability and evidence that can withstand review.
One bounded problem One accountable owner One acceptance boundary One evidence baseline
THE CUSTOMER PROBLEM
The difficult part starts after the demonstration.
A prototype can show that a model is capable. It does not show that the workflow is worth operating, that the right people remain accountable, that data and permissions are controlled, or that a buyer or assurance team will accept the evidence.
DDAI helps organisations close that gap before artificial intelligence becomes an operational, procurement or governance problem.
Common triggers
- A leadership team must decide which use case is worth funding.
- A public body needs to procure or pilot an artificial-intelligence service.
- A supplier must answer enterprise or government evidence questions.
- A workflow needs to move from demonstration to controlled operation.
- A board, auditor or assurance team needs a defensible system record.
- A model, supplier or operating context has changed and the evidence must be reassessed.
WHAT DDAI DOES
From opportunity to accountable operation.
Design how it should work
Define the intended purpose, data and system boundary, model and supplier dependencies, human accountability, evaluation criteria and failure routes.
Deliver one bounded outcome
Build, integrate or assess the workflow against written acceptance criteria rather than treating a demonstration as production proof.
Leave the evidence behind
Create the system record, decisions, approvals, evaluations, training and handover material needed for review and future change.
SERVICES
Six ways to move from intent to accountable delivery.
AI Opportunity & Assurance Sprint
Choose the use cases worth pursuing and establish the technical, operational, procurement and evidence requirements for each.
Map the opportunityGoverned AI Pilot & Integration
Turn one bounded use case into a working pilot with evaluation, human oversight, failure handling and operational handover.
Scope a governed pilotAI Governance Operating Model & Evidence Baseline
Connect policies, roles, controls, incidents, suppliers and evidence to the artificial-intelligence systems the organisation actually operates.
Build the operating modelAI Procurement & Supplier Assurance
Help buyers assess supplier evidence and help suppliers answer enterprise or public-sector scrutiny with a controlled evidence record.
Review a buying or selling decisionAI Literacy, Leadership & Role-Based Enablement
Give leaders, commercial teams, assurance teams, technical teams and users the judgement and practical workflows their roles require.
Build role-based capabilityManaged Assurance, Reassessment & Evidence Operations
Keep system records, evidence, reviews and reassessments current without creating an unbounded managed-service commitment.
Discuss ongoing evidence operationsPUBLIC-SECTOR DELIVERY
Responsible procurement needs more than a supplier questionnaire.
DDAI supports public bodies and suppliers across England, Scotland, Wales, Northern Ireland and relevant European procurement markets.
We can help define the use case, procurement evidence, evaluation criteria, human-oversight requirements, controlled pilot, operational handover and first evidence baseline.
HOW AN ENGAGEMENT WORKS
One problem. One scope. One decision.
1. Define
Agree the system, intended purpose, buyer or service trigger, accountable owner, reviewers, exclusions and delivery boundary.
2. Design
Map the workflow, data, suppliers, permissions, risks, acceptance criteria, human oversight and evidence requirements.
3. Deliver
Run the sprint, assessment, training or implementation work inside the agreed boundary.
4. Evidence
Record decisions, approvals, evaluations, gaps, remediation and handover material.
5. Continue or stop
Make an explicit decision to deploy, remediate, procure, reject, expand or move into a recurring Evidary workflow.
ONE COMPANY · TWO COMMERCIAL MOTIONS
DDAI establishes the evidence. Evidary keeps it current and verifiable.
DDAI identifies and delivers the use case, operating controls, training and first evidence baseline.
Evidary maintains the resulting AI Evidence Passport, approvals, signed versions, verification, monitoring and reassessment where recurring software is appropriate.
Evidary is not mandatory for every consultancy engagement. DDAI work is designed so the evidence can move into Evidary without being reconstructed when the customer needs a living, independently reviewable record.
See how DDAI and Evidary work togetherWHO WE WORK WITH
Built for organisations that must answer to someone else.
Public bodies
Teams procuring, piloting or operating artificial intelligence in public services.
Artificial-intelligence suppliers
Companies selling into enterprise, regulated or government buyers.
Regulated and high-accountability organisations
Teams facing board, audit, customer, sector or legal scrutiny.
Assurance and delivery partners
Firms that need a repeatable evidence method while retaining professional judgement.
Selective small and medium-sized businesses
Organisations with a bounded, high-value workflow or a live buyer evidence request.
Evidence-led delivery, not a compliance shortcut.
DDAI provides implementation, assessment, training and assurance support within an agreed scope. Legal classification, certification, conformity assessment and regulatory decisions remain with the appropriate professionals and authorities.
Tell us what must be decided, built or proved.
Start with one system, one buyer or service trigger and one accountable owner.