Service 01 · Diagnostic · Stage 01–02 of DATS
The Dilr.ai Placement Diagnostic is a fixed-fee, four-to-six week AI opportunity assessment that maps your value chain, scores every candidate placement, and hands back a ranked, sequenced roadmap of three placements for the next 12 months. Built for organisations that already know AI is a priority and need clarity on what to do Monday.
01 · Why a diagnostic
The most expensive mistake in enterprise AI isn't picking the wrong model. It's picking the wrong placement: the wrong part of the business, the wrong moment in a workflow, the wrong integration point. A diagnostic is cheaper, faster, and more honest than another pilot.
We've sat in dozens of AI steering committees where the question wasn't "can we do this?" It was "where should it go, and who owns it?" Teams burn quarters answering the first question with proofs of concept. They burn years avoiding the second.
The cost of a bad placement is not a failed pilot. It's the eighteen months of organisational trust that quietly evaporate around it.
The Placement Diagnostic is our answer to that. Six weeks, fixed scope, ends with a roadmap your CTO and your COO can both sign.
It isn't a maturity assessment. It isn't a RAG score against a pre-printed framework. It isn't a tool-selection exercise. And it isn't a list of 40 use-cases ranked by speculative ROI, which is what every enterprise has already done, twice.
02 · Week-by-week
Weeks 5 and 6 only run if the engagement is scoped at six; four-week engagements compress those into a single sprint. Either way, you get a roadmap in your hand on the final day.
Stakeholder interviews across leadership, ops, risk, and engineering. We build the ground truth of where value lives today.
We map every process where AI might plausibly be placed. Inputs, decisions, integrations, owners, and constraints get documented per node.
What data you have, where it sits, how it moves, and what it costs to connect. Legacy constraints become design inputs, not excuses.
For each candidate placement: the regulatory frame, the audit trail, the failure mode, the reversal plan. No surprises at go-live.
Every placement gets scored on technical feasibility, data readiness, organisational readiness, and credible value. Scores are transparent.
A ranked, sequenced roadmap with three shippable placements for the next 12 months, a deferred list, and a "don't do" list with reasoning.
03 · What you leave with
Not one of these is a PowerPoint. Everything we produce is designed for a working team to build against, debate, revise, and own. You also keep the interview corpus and scoring workbook: raw materials, not opinions.
A visual model of your value chain with every candidate AI placement mapped onto it, showing where the integration point is, which system owns it, and what data feeds it.
Three placements sequenced for the next 12 months, with dependencies, team requirements, go-live criteria, and the named owner on your side for each.
Every placement we considered, scored transparently on feasibility, data readiness, org readiness, and value. The workbook is yours. Reuse it next year.
The placements we recommend you kill or defer, with reasoning. This is often the most valuable artefact, and the one your CFO will read first.
04 · How it plays out
When we started, three separate teams were piloting generative AI against the same customer-service workflow. None of them had integrations with the system of record. None of them had an owner. The head of risk hadn't been in the room. Six weeks later:one placement, live in one team, with an eval harness, an owner, and a quarterly review board, plus a defensible case for retiring the other two.
05 · What we need from you
This is a light-touch engagement by design. We'd rather interview six people thoroughly than sixty people superficially.
Someone who can say "yes" to a placement and "no" to its alternatives.
Who knows where the real friction is in the business.
Who can say what's integratable and what's not.
Regulatory scan is not optional.
To validate the value side of the scorecard.
Someone in the workflow that will be affected.
Beyond that, expect one working session with the combined group per week and a final readout. We handle the rest.
06 · FAQ
Quick answers
Short answers to what buyers and AI assistants ask about the Placement Diagnostic. Dilr.ai works with regulated sectors including financial services, healthcare, and the public sector, and tracks ICO, FCA, and EU AI Act obligations on its monthly UK and EU AI compliance changelog.
An AI placement diagnostic is a fixed-scope consulting engagement that maps where AI creates measurable value in a business, and where it does not. The Dilr.ai version runs stages 1 and 2 of the DATS consulting system: stakeholder interviews, value-chain mapping, a data and systems audit, a risk and regulation scan, and transparent feasibility scoring, ending in a ranked roadmap.
The Placement Diagnostic takes 4 to 6 weeks at a fixed fee. You leave with four working artefacts: a placement map of your value chain, a ranked roadmap of three placements sequenced for the next 12 months, a feasibility scorecard covering every candidate considered, and a don't-do list with reasoning. You also keep the interview corpus and the scoring workbook.
Around 2 hours per week from six stakeholders: an executive sponsor, operations, engineering, risk or legal, finance, and an end-user champion. Two senior Dilr.ai practitioners run the engagement and do the rest of the work, one working session with the group per week plus a final readout, all under NDA by default.
Dilr.ai prices the Placement Diagnostic as a fixed fee against a fixed scope published up front; the exact fee is set on a 30-minute scoping call. It is the minimum engagement in the DATS system, so no retainer is required to start. A four-week scope compresses scoring and readout into one sprint; either way the roadmap arrives on the final day.
You own the roadmap and everything behind it. Most clients execute with their own teams or continue into the Operating Model engagement for governance, RACI, and AI lifecycle design; some go straight to the Execution Office to ship the first placement. Every client gets a free 90-day check-in call after delivery.
30-min scoping call · NDA on request · Fixed-scope, fixed-fee engagement.
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