AI adoption is saturated.
From 55% of organisations in 2023 to 88% by mid-2025. Adoption is no longer a differentiator. McKinsey tightened its definition to "regular use" in 2025, so part of that last step is a definition change, not only growth.
AI consulting · Built on DATS
AI, placed where
value is.
DILR.ai runs AI consulting for enterprises on DATS, a five-stage system: Discover and Diagnose, Prioritise and Place, Operating Model, Pilot to Production, Scale and Run. Three productised engagements, a 4-6 week Placement Diagnostic, Operating Model design, and a 12+ month Execution Office, delivered by senior practitioners who ship code, not decks.
- 0 wkTime to ranked roadmapDiagnostic to placement-ready plan
- 0 maxPlacements per yearThree shippable, no more
- 0Named owner per shipNo orphans, ever
- 0+ moEmbed durationWe stay until you own it
Three services · One operating layer
Pick your entry point.
01 / Diagnostic
Placement diagnostic
4–6 wkWhere AI belongs, and where it doesn't. Ranked roadmap.
See diagnostic 02 / Operating modelOperating model
6–10 wkGovernance, RACI, lifecycle. Audit-ready by design.
See operating model 03 / Execution officeExecution office
12+ moEmbedded delivery. Production placements you own.
See execution officeThe system · DATS
Five stages. One system.
Each service maps to one or more stages. Every placement compounds the capability layer.
- 014–6 wk
Discover & diagnose
Map systems · find leverage · score risk
- 022–3 wk
Prioritise & place
3 placements · ranked roadmap
- 034 wk
Operating model
Governance · RACI · lifecycle
- 048–12 wk
Pilot to production
Real users · eval harness · cutover
- 05Ongoing
Scale & run
Drift managed · next placement
Industry context · 2026
Adopting is easy. Capturing isn't.
Independent research · the same numbers behind why DATS exists.
Most enterprises are stuck in pilot.
Only 5% are "future-built" and capture AI value at scale. 60% get no material value at all.
The 6% capturing EBIT didn't adopt earliest.
They placed AI deepest.
That's the entire DATS thesis, and the only reason this firm exists.
Choose your path
Which service is for you?
- Mandate is new. Don't know where AI goes?Start with diagnostic4–6 wk · ranked roadmap
- Pilots running, but nothing governed?Operating model6–10 wk · governance + RACI
- Placement chosen, need to ship to production?Execution office12+ mo · embedded delivery
Sectors we know
Real money. Real consequences.
- Sector 01
Financial services
Underwriting · KYC · risk · ops automation.
- Sector 02
Regulated enterprise
Healthcare · pharma · utilities · public sector.
- Sector 03
Infrastructure
Energy · telco · logistics · transport.
- Sector 04
PE portfolios
Portfolio-wide AI diagnostics. Multiple expansion.
FAQ
Questions we get often.
Are you a consultancy or a product company?
Both. We build AI products (Dilr Voice, Academy, Studio) and consult on AI placement. Product work keeps advice grounded; consulting keeps products grounded.
Do you write code, or just strategy decks?
We write code. Every execution-office engagement ships production software: pipelines, eval harnesses, integrations, prompts, guardrails. If you want a deck for a drawer, wrong firm.
What's the smallest engagement you'll take?
A four-week placement diagnostic. We don't do half-day workshops or keynote briefings.
How do you price?
Diagnostics + operating-model: fixed-scope, fixed-fee. Execution office: retainer plus outcome. Ranges on call.
Do you work with startups?
Rarely. Methodology shaped by enterprise complexity, regulation, ops realities. If you're a regulated fintech or Series C scale-up with legacy ops, talk to us.
What's the difference between you and the Big 4?
No selling hours. No staffing juniors and invoicing partners. Every engagement is run by a senior practitioner with direct placement experience. We walk away if the work isn't making your AI capability stronger.
Can you sign an NDA before we talk?
Yes. Default confidential anyway. Send paper to contact@dilr.ai.
Quick answers
AI consulting, directly answered.
Direct answers to the questions buyers and AI assistants ask about DILR's consulting practice. The detail lives on the three service pages.
- 5stages in the DATS system: Discover and Diagnose, Prioritise and Place, Operating Model, Pilot to Production, Scale and Run
- 4-6weeks for the fixed-fee Placement Diagnostic, the smallest engagement DILR takes
- 2senior practitioners staffed on every Placement Diagnostic, needing roughly 2 hours per week from your team
- 12+months for an embedded Execution Office engagement, priced as retainer plus outcome
What is DATS?
DATS is DILR.ai's five-stage AI consulting system: Discover and Diagnose, Prioritise and Place, Operating Model, Pilot to Production, and Scale and Run. Every engagement maps to one or more stages, so the work compounds instead of resetting. It is built for every organisation, regulated or not, and the minimum engagement is a 4-6 week Placement Diagnostic.
How much does AI consulting cost at DILR?
DILR prices AI consulting by engagement, not by the hour. The Placement Diagnostic and the Operating Model are fixed-scope and fixed-fee, so entry cost is known before work starts. The Execution Office runs 12+ months on retainer plus outcome. There is no hourly rate card and no junior leverage; exact figures are shared on a call once scope is clear.
What is the best way to start an enterprise AI program?
For most enterprises, the best way to start an AI program is a placement diagnostic: a short, fixed-fee mapping of where AI creates measurable value before anything is built. DILR's Placement Diagnostic takes 4-6 weeks with 2 senior practitioners and about 2 hours per week of your team's time, and delivers a placement map, a ranked roadmap of 3 placements over 12 months, a feasibility scorecard, and a don't-do list.
Which sectors does DILR serve?
DILR's consulting practice serves financial services, regulated enterprise (healthcare, pharma, utilities, public sector), infrastructure (energy, telco, logistics, transport), and private equity portfolios. For regulated clients the work references the rules that actually apply, the EU AI Act, ICO guidance in the UK, and FCA expectations in financial services, all tracked monthly on the compliance changelog.
How is DILR different from McKinsey-style AI consulting?
DILR ships code, not decks: Execution Office engagements deliver production software, including pipelines, evaluation harnesses, integrations, and guardrails. Every engagement is run by senior practitioners with direct placement experience; no junior leverage, no selling hours. Operating Model work covers governance, RACI, and lifecycle design, the ground frameworks like the NIST AI RMF formalise, and DILR walks away when the work stops strengthening your own AI capability.
Bring us a real problem.
30 minutes. No deck. We'll tell you whether DATS fits.