AI & Data Transformation

Everyone is talking about AI. Very few are shipping it.

Define Data helps founders, CTOs and Heads of Data turn AI ambition into production — strategy, architecture and hands-on implementation from a practice that has built enterprise AI, with the AI-ready data and revenue systems underneath.

Focused on CRM and revenue systems specifically? Try the GTM systems readiness check.

definedata · track-record
PROOF
20+
Enterprise customers on an AI platform we architected
15
People led across Product, Engineering and Data
1.5B
Events per year processed in analytics we built
12+
Years leading data, analytics and business systems
Built and shipped in production
RAG & semantic layer
Agent architecture
AI governance
AI-ready data platforms
RAG · semantic layer · governance enterprise AI

The inflection point

The gap between AI ambition and AI in production is where budgets go to die.

Every leadership team is under pressure to "do AI". Most have run a pilot, bought some copilots, maybe demoed a chatbot. Very little of it has reached production, and almost none of it is trusted with real decisions.

The blockers are rarely the models. They are unclear use cases, data that cannot be trusted, missing governance — no provenance, no permissions, no audit trail — and architectures that were never designed for AI. Meanwhile the spend continues and the board keeps asking what the AI strategy is.

Closing that gap takes strategy, architecture and delivery from a team that has shipped it.

Diagnostics

You may need this if

A few of these usually show up together once AI moves from slideware to something the business is actually meant to run on.

01

The board is asking for an AI strategy and there is not one

02

AI pilots impress in demos but never reach production

03

Nobody can say which AI use cases are actually worth the investment

04

Your data cannot be trusted enough to put AI on top of it

05

Provenance, permissions and auditability are unanswered questions

06

Copilots and chatbots everywhere, measurable value nowhere

07

Dashboards exist, but nobody trusts the numbers

08

Your CRM does not reflect reality, so automation and AI multiply the mess

What gets built

Strategy, architecture and delivery — one accountable partner

Define Data designs and delivers enterprise AI — and the data and revenue systems it depends on.

01

AI Strategy & Advisory

Discovery workshops, use-case prioritisation and AI roadmaps that translate business challenges into production AI — not pilots.

02

AI Architecture & Implementation

RAG, semantic layers, context engineering, agent architecture and evaluation — designed, governed and shipped.

03

AI Governance

Provenance, confidence scoring, permissions and auditability — so enterprise AI can be trusted, not just demoed.

04

AI-Ready Data Platforms

Cloud data platforms, metadata and semantic modelling that give AI trusted enterprise information to build on.

05

Semantic & Data Modelling

Metadata models, master data management and governed definitions — the business context AI answers rest on.

06

Enterprise Integration

Salesforce, NetSuite, HubSpot, Jira and operational systems joined into one information ecosystem.

07

GTM & Revenue Systems

CRM architecture, lifecycle design and trusted reporting — the revenue layer, kept honest.

08

Trusted Reporting

Board-ready metrics on numbers leadership can actually run the business on.

09

Workflow Automation

Automation that removes manual reconciliation without creating noise — across CRM, data and AI workflows.

David Kernan, founder of Define Data

Who builds this

A practice built on shipped enterprise AI

Define Data is led by David Kernan — former Head of Data & Product at an enterprise AI platform, where the team architected RAG, semantic layers, vector search, context engineering and AI governance for 20+ enterprise customers — backed by a network of trusted specialists across data, engineering and design.

Microsoft AI Transformation Leader AWS Certified AI Practitioner Salesforce Data Architect Salesforce Administrator Power BI CIPP/E

Free diagnostic

The Data & AI Readiness Check

A five-minute self-score across data foundations, AI readiness, governance, reporting trust and automation. You get an instant scored report and a practical 30/60/90-day plan for where to focus first.

Focused on CRM and revenue systems specifically? Try the GTM systems readiness check.

What it scores 5 min
  • 01

    Data foundations

  • 02

    AI readiness

  • 03

    Governance

  • 04

    Reporting trust

  • 05

    Automation

Instant scored report plus a 30/60/90-day plan — no call required to see your results.

Start here

See where you stand on AI

Score your data and AI readiness in five minutes, or book an AI Readiness Assessment to find out what is between you and AI in production — before spending money on the wrong thing.