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Strategy, adoption and delivery that answer to the same plan.

Six practices, listed in the order clients usually need them. Most engagements start in one and pull in a second within a quarter.

A curve rising through five stages: assess, prove, roadmap, adopt, and fund marked optional. Below, five small charts show uncertainty falling while evidence, clarity, commitment and value realised rise across the arc.
Most engagements move along this arc. Uncertainty falls as evidence accumulates; funding is an option at the end, not the starting point. (open full size)

01

AI Strategy & Roadmap

Which AI is worth doing, in what order, owned by whom - and what it returns.

  • AI readiness & maturity assessment

    Scored assessment across data, technology, people and governance, with a gap plan.

  • Use-case discovery & prioritisation

    Workshop-driven backlog scored on value, effort and risk, sequenced into a roadmap.

  • AI strategy

    Where AI creates margin for you, what to build versus buy, and the budget and team shape it requires.

  • AI roadmap

    A 12–24 month sequenced plan with named owners, dependencies, decision gates and the point at which each initiative is judged.

  • Business case & ROI model

    Cost to run at your volumes, quantified return, payback period, and a sensitivity analysis showing what has to hold for the case to survive.

  • Build vs buy & model selection

    Decision memo backed by benchmark evidence and a running-cost model.

02

Adoption, Change & Enablement

The work that decides whether anyone actually uses what was built.

  • AI operating model

    Who owns AI decisions, which forum approves what, how initiatives are funded, and where accountability sits when something goes wrong.

  • Change programme design

    Stakeholder map, phased rollout plan, communications, and an honest read on where resistance will come from and why.

  • Workflow redesign

    The process around the tool rebuilt so the new capability fits how people actually work, rather than being added on top.

  • Role-based team training

    Separate tracks for executives, managers, engineers and analysts - each ending with people able to do something they could not do that morning.

  • AI champions & internal capability

    Identifying and equipping the people inside the organisation who will carry this after we leave.

  • Staff AI policy & acceptable use

    Practical internal guidance people will follow: what is allowed, what is not, what needs review, and who to ask.

03

PoC & Rapid Prototyping

A working prototype in weeks, with an evaluation report and an honest verdict on whether to continue.

  • PoC sprint

    A working prototype, an evaluation report, and an honest go/no-go.

  • Feasibility study

    Can this be built, with what data, at what cost, at what accuracy - before budget is committed.

  • Agentic & GenAI systems

    Retrieval, agent workflows, tool use, guardrails, observability and an evaluation harness.

  • Domain assistants

    Analytics, scheduling, document and compliance assistant patterns adapted to your data.

  • Forecasting & time series

    Demand and load prediction, anomaly detection and early-warning pipelines.

  • Computer vision with explainability

    Detection and segmentation pipelines with XAI, for regulated or safety-critical use.

04

EU R&D Funding Strategy

Where genuinely novel work can be part-funded - and when a call is not worth entering.

  • Funding radar & topic identification

    Ranked shortlist across Horizon Europe, EIC, Digital Europe, EDF, Eurostars, Interreg, LIFE and national schemes, mapped to your assets.

  • Call fit & go/no-go assessment

    A two-page verdict: win probability, what is missing, what entering would cost you.

  • Competitive landscape analysis

    Who won similar topics before, what they promised, and where the white space is.

  • Consortium building & partner matching

    Target partner map, introduction strategy, role and budget allocation, letters of intent.

  • Coordinator support

    Consortium orchestration, section owners, internal deadlines and quality gates.

  • Multi-year funding roadmap

    A three-year plan combining grants, tenders and your own R&D budget into one pipeline.

05

Innovation & Product

Turning research results and prototypes into something with a price, a market and a margin.

  • Research-to-product translation

    Turning project results into a sellable offer - the exploitation gap where most projects end.

  • AI product discovery & definition

    Problem framing, user and job mapping, feature scope, MVP definition.

  • Pricing & packaging

    Tier design, usage versus seat versus outcome pricing, and the margin model underneath.

  • Product unit economics

    Cost per task at production volumes, gross-margin projection, and the levers that move it.

  • Business model & business plan

    For EIC Accelerator, investors or internal approval - market sizing, go-to-market, financials.

  • Technical due diligence

    An independent verdict on a company's technology claims, team and architecture.

06

Proposal Drafting & Technical Writing

Proposals, deliverables and architecture documents written by people who could also build the thing.

  • Full proposal drafting

    Complete Part B - Excellence, Impact, Implementation - with work packages, Gantt and budget narrative.

  • Section-only writing

    The chapters that sink proposals: Impact, exploitation and IPR, key results, risk, data management, ethics.

  • Pre-submission expert evaluation

    Evaluator-style scoring on the official 0–5 scale, with a summary report and prioritised fixes.

  • Resubmission rescue

    Analysis of your evaluation summary report and a rewrite plan for proposals that fell just short.

  • Public tender & RFP response

    Bid strategy, technical offer and compliance matrix for national and EU procurement.

  • Post-award technical writing

    Deliverables, periodic reports, review presentations and amendments.