---
title: "Data and AI Project Methodology | Data-Driven AI"
canonical: "https://data-driven.com/data-driven-ai-project-methodology/"
description: "See how Data-Driven structures discovery, design, implementation, handover, governance, and support for data and AI projects."
---

Project delivery

# A delivery method built around _clear review points_

Move from discovery to support with clear records, owners, checks, and sign-off.

![Diagram of the five delivery phases from discovery and assessment through maintenance and support](/_astro/DD-Website-Image-box-collection-3-e1765355041971-1024x630.DNfp9_58_Zhr96J.webp)

How projects run

## Define the review points before work begins

The Data-Driven AI Project Methodology runs from discovery and design, through build and test, to handover and support. Each phase has a stated goal, a working record, and a review before the next one starts.

[Review the lifecycle](#delivery-lifecycle)

Project steps

## The lifecycle keeps decisions visible

Each project sets its own outputs. These records keep the scope, risks, design, tests, and owners clear as work moves on.

Phase 01

### Discovery and assessment

Learn how things work now. Meet the key people. Agree the problems, KPIs, users, data needs, and signs of success.

**Working record:** project charter, scope statement, RAID register, and first architecture review.

Phase 02

### Solution design

Plan how the team will bring in, store, use, govern, report, and share data. Check the plan against the security, compliance, and architecture needs in scope.

**Working record:** high-level and low-level designs, architecture diagrams, and the security and compliance plan.

Phase 03

### Implementation and testing

Build and test the agreed work in short sprints. Use plans, reviews, test proof, and feedback to check it against the acceptance criteria.

**Working record:** configured environments, tested pipelines or reports, and sprint reports.

Phase 04

### Handover and documentation

Give the team the guides, training, files, and review proof set in the scope. Share the knowledge they need to run the work.

**Working record:** handover files, user guides, and the review after launch.

Phase 05

### Maintenance and support

Agree the support after launch. Set service levels, review dates, ways to raise issues, and the move into day-to-day work.

**Working record:** support reports, health checks, and a plan for later improvements if they are in scope.

Project checks

## Governance lives in the working record

Keep roles, risks, sign-offs, and test proof clear from start to finish.

Accountability

RACI and named approvers

Risk record

RAID register

Quality evidence

Peer review and testing

Decision points

Approvals and acceptance

### Confirm certification currency during assurance review

Data-Driven links its quality and security work to ISO 9001:2015 and ISO/IEC 27001:2022. Check the current certificate status and scope before you use it for a purchase or review.

[Review the certification page](/iso-27001-and-iso-9001-certifications/).

Team rhythm

## Turn each request into a decision record

The team may include an account manager and data architect. It may also include engineers, data model and governance experts, report analysts, and change advisers. The scope sets the final team, meeting plan, and support.

1.  Document the request, intended outcome, scope, constraints, and timing.
2.  Agree the proposal, deliverables, roles, communication cadence, and escalation path at kickoff.
3.  Record progress, risks, dependencies, decisions, and review evidence in the agreed tools.
4.  Complete acceptance, documentation, and knowledge transfer before agreeing any ongoing support terms.

## Put review points around the project

Bring your current setup, goal, limits, and the proof each owner needs.

[Discuss the methodology](/contact-us/)

[Back to home](/)

## Want to learn more?

Explore the rest of the site or get in touch with the team.

[Back to home](/)