Consulting

AI Digital Consulting & Strategy: from ambition to a production agent in 6–8 weeks.

Most enterprise AI stalls between the slide deck and production. We start where the value is. A specific workflow, a measurable cost, a queue that never clears. And write a delivery plan that gets an agent into that workflow in weeks, not quarters. No transformation theatre, just a sequenced path from where you are to running software.

6–8 wks strategy to first production agent

60+ enterprise engagements delivered

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Outcomes

What you get, stated as results.

A ranked backlog of automatable workflows with modelled payback
A delivery roadmap tied to owners, dates, and budget
A governance model agreed before build begins

Capabilities

What this practice covers.

Opportunity mapping

We audit your operations for work that is repetitive, rule-bound, and expensive. The workloads where autonomous agents pay back fastest.

Delivery roadmaps

A phased plan tied to owners, budgets, and dates. Every phase ends in something running, not a report.

Operating-model design

How people, agents, and governance share the work once the system is live. Decided before the first line of code.

Business cases that hold

Cost, risk, and payback modelled against your real numbers, so the investment survives a finance review.

Vendor & platform strategy

Build, buy, or orchestrate. An honest recommendation independent of any single cloud or model provider.

Readiness assessment

Data, security, and change-management gaps surfaced up front, with a plan to close each before rollout.

The stack behind this service.

Real tools our team works in day to day, not a generic capability list.

Figma

Notion

Miro

How it works

A sequenced path, not a big bang.

6–8 wks

Strategy to first production agent

Locate the value

Two weeks inside your operation to find the workflows worth automating and rank them by payback.

Design the system

Target architecture, governance model, and a phased delivery plan your teams sign off on.

Prove it in production

A scoped first agent shipped into a live workflow. Evidence before commitment.

Scale on the plan

Repeat the pattern across adjacent workflows on the roadmap you already agreed.

Proof, Not Promises

Real engagements, the results attached to each one.

Roadmap approved by the board in 10 weeks

High-street homewares retailer, UK

22 workflows assessed, 5 recommended for a first wave

Regional property insurer, Pacific Northwest

14 ideas narrowed to 1 in 3 weeks

Logistics software firm, Denver

31 applications reduced to 19 within 12 months

Rural broadband provider, Appalachia

Ten industries. One audited standard.

Different regulations, different systems of record — the same discipline every time: agents that run inside guardrails and leave a record you can read.

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BFSI

Retail & CPG

Telecom

Technology

Healthcare

Public Sector

PropTech

Education

FinTech

AgriTech

Startups

Digital Consulting & Strategy case studies

Challenge, solution, results. What this practice has shipped.

Anonymised at the client's request. Each card states the pain point, what we built, and what changed. Plus the service type and country.

04 studies

Web UK

Replatforming roadmap for a high-street homewares retailer

High-street homewares retailer, UK

Challenge: The retailer's e-commerce platform was eight years old, customised beyond upgrade and maintained by one contractor. Peak-season outages were costing sales, and three previous replatforming proposals had stalled because nobody could agree on scope, sequencing or cost.
Solution: A ten-week consulting engagement: we audited the current platform and integrations, interviewed store, warehouse and marketing teams, and produced a phased roadmap with costed options. The board approved a headless commerce migration in three releases, with click-and-collect moved first because it carried the most risk.
Results: Roadmap approved by the board in 10 weeks
Phase one scoped at £340k against a £900k prior estimate
First release shipped 7 months later, before peak season

AI Agents USA

Agent readiness assessment for a Pacific Northwest insurer

Regional property insurer, Pacific Northwest

Challenge: Leadership had approved budget for AI agents in claims but had no view of which processes were suitable, what data they would need or what the regulator would expect. Three vendors had pitched three different starting points, and the internal team was unsure what to ask.
Solution: AGS ran a six-week assessment: we mapped 22 claims workflows, scored each for volume, rule clarity, data access and oversight requirements, and defined the approval and audit controls any agent would need. The output was a ranked backlog, a reference architecture and a first-year programme plan.
Results: 22 workflows assessed, 5 recommended for a first wave
Control framework accepted by compliance in 1 review cycle
First agent in production 4 months after the assessment

AI MVPs USA

Scoping an AI MVP for a Denver logistics software firm

Logistics software firm, Denver

Challenge: The product team wanted an AI feature for their freight-matching platform but had a list of fourteen ideas and one quarter of engineering capacity. Customers were asking for 'AI' without saying what they would pay for, and the founders needed a defensible choice.
Solution: A three-week discovery: customer interviews, a review of usage data and a feasibility check on each idea against the firm's data. We narrowed to one candidate, an exception-handling assistant for delayed loads, then scoped and built it as an eight-week MVP with defined success metrics.
Results: 14 ideas narrowed to 1 in 3 weeks
MVP used by 9 pilot customers within 8 weeks
Feature adoption reached 35% of active users at launch

Apps USA

Application consolidation plan for a rural broadband provider

Rural broadband provider, Appalachia

Challenge: Fifteen years of growth had left the provider with 31 internal applications, including four separate tools for logging customer faults. Staff re-keyed data between them, licences overlapped, and nobody owned a full inventory. Every new hire needed logins to a dozen systems.
Solution: AGS inventoried every application, its owner, cost and integrations, and ran workshops with each department. The resulting plan retired 12 systems, consolidated fault handling into one Dynamics 365 instance and set out a 12-month sequence with the cut-over risks and training needs for each step.
Results: 31 applications reduced to 19 within 12 months
Annual licence spend cut by $210k
Re-keying eliminated for fault logging across 4 teams

FAQ

Digital Consulting & Strategy: questions, answered.

How long does an agentic AI strategy engagement take?

Most engagements run six to eight weeks from kickoff to a first production agent. We spend the first two weeks locating the highest-payback workflows, then design the system, agree governance, and ship a scoped agent into a live workflow. Evidence before a larger commitment, not a report.

Do we need a finished data or AI platform before we start?

No. We start with the workflow that has clear payback and surface any data, security, or change-management gaps up front, with a plan to close each before rollout. Readiness is assessed as part of the engagement, never treated as a prerequisite that stalls the work.

Are your recommendations tied to a specific cloud or AI vendor?

No. Our platform and vendor strategy is independent of any single cloud or model provider. We give an honest build, buy, or orchestrate recommendation based on your stack and economics, so the decision serves you rather than a reseller relationship.

What do we actually get out of a strategy engagement?

You leave with three concrete artefacts: a ranked backlog of automatable workflows with modelled payback, a delivery roadmap tied to owners, dates, and budget, and a governance model agreed before build begins. Every phase ends in something running, not transformation theatre.

How do you decide which workflows to automate first?

We audit your operations for work that is repetitive, rule-bound, and expensive. The workloads where autonomous agents pay back fastest. Those are ranked by payback so the first agent lands where value is clearest, then the pattern repeats across adjacent workflows on the roadmap you already agreed.

Put Digital Consulting & Strategy to work.

Tell us the workflow. We'll show you the shortest path to a running agent.

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