AI consulting
AI consulting from strategy to working software
Elsewhen is an AI consultancy that builds custom AI into your business: agents inside the workflows that cost the most, wired to your systems and owned outright by you.
What is AI consulting?
AI consulting helps an organisation decide where AI should do work, then design, build and run the systems that do it. The scope runs from strategy and the business case through engineering and governance to operating the result, and the strongest engagements end with working software in production, which the client owns, as well as a plan.
Three kinds of AI consulting firm
Strategy firms advise on where AI fits and hand the plan to someone else to deliver. Systems integrators and software vendors implement a platform and fit your work to it. A build-focused AI consultancy, which is what Elsewhen is, scopes the work, builds custom systems on your data and hands over something you own.
Each has its place, and the difference shows up in who is accountable when the return does not arrive.
How Elsewhen works
We work in three ways, each starting from the work that costs the most: automating what you do with agents inside your costliest workflows, replacing what you rent by rebuilding SaaS as systems you own, and growing what you sell with products that were not buildable before these models existed. A senior UK squad sits with your team throughout.
| Strategy firm | Vendor or integrator | Build-focused AI consultancy | |
|---|---|---|---|
| Leaves you with | A roadmap | A configured platform | Working software you own |
| Who builds | Someone else | The vendor’s product | The team that scoped it |
| Paid for | Days of advice | Licences and implementation | The outcome, where possible |
| Lock-in | Low | High | None: your code and your IP |
What do AI consulting services include?
AI consulting services cover the whole path from idea to running system: AI strategy and the business case, agent development, the shared platform agents run on, data and cloud engineering, integration with existing systems, governance, and the product and interface design that lets people steer the work. Elsewhen groups them into three offers, each built on the same platform.
The three offers
Agentic Operations automates what you do, with agents inside the workflows that cost the most time and money. Agentic Modernisation replaces what you rent, rebuilding SaaS and legacy systems as custom agentic systems you own outright with no recurring licence. Agentic Growth grows what you sell, with AI search and discovery, agents that sell, personalisation engines and new products.
Which comes first is settled by the AI roadmap, built by measuring your workflows and ranking them by return, and each offer is set out in full on our services page.
One platform underneath
All three run on the same Platform: business context, headless agents, an orchestrator, a skills library and generative UI, built once with the first use case and reused by every agent after it. The second use case costs less than the first for that reason, and how we build production-grade AI systems on it is covered on our engineering page.
- Automate what you doAgents inside the workflows that cost the most time and money
- Replace what you rentRented SaaS rebuilt as a custom system you own outright
- Grow what you sellRevenue from the inventory, demand and data you already own
When should you bring in an AI consultancy?
Bring one in when AI work has stalled between pilot and production, when a SaaS renewal or legacy rebuild is coming up, when a workflow costs too much to keep running by hand, or when you need production systems faster than an internal team can hire for them. In each case there is a measurable return that nobody is yet accountable for.
Signals worth acting on
Pilots that impressed in demos but have no owner for production are the most common signal. Others are a renewal date on a tool whose per-seat price no longer makes sense when agents do the work, a back-office queue that grows with every new customer, and a board asking what the AI budget has returned. Each is a workflow with a cost attached, which makes it a place to start.
When to build it yourself
If you already have a senior AI engineering team with production experience and spare capacity, much of this can be built internally, and a short strategy engagement may be all the outside help you need. The case for a consultancy is speed and accountability: a squad that has shipped this kind of system before, working to a return it is paid against.
| Signal | What it usually means | Where to start |
|---|---|---|
| Pilots with no route to production | No shared platform and no owner | One workflow, measured and shipped |
| A SaaS renewal approaching | Paying per seat for work agents could do | Agentic Modernisation |
| A queue that grows with every customer | Cost that scales with volume | Agentic Operations |
| A board asking for the return | Spend without a business case | An AI strategy and ROI model |
How much does AI consulting cost?
The commercial model shapes the cost more than the day rate. Elsewhen offers three: outcome-based, where the fee sits against the return you asked for; time and materials at senior day rates with full transparency; and fixed price for a defined build. Whichever you choose, the return is modelled before the build and you own what is built.
Outcome-based pricing
Outcome-based commercials price the work against the cost saved, the revenue gained or the time returned, so Elsewhen backs its work with its own money. That needs a baseline everyone agrees on, so the first step is measuring the workflow as it is today, and it suits work where the return can be counted directly.
What changes the cost
The main drivers are the number of systems an agent has to work with, the quality of the data, the level of governance the workflow needs and whether the shared platform already exists. The first use case carries the cost of the platform, and each one after it ships faster and cheaper on what the first one built.
| Model | How it works | Suits |
|---|---|---|
| Outcome-based | The fee is priced against the return: cost saved, revenue gained or time returned | Workflows with a countable baseline |
| Time and materials | Senior day rates, with full transparency | Discovery and changing scope |
| Fixed price | A defined build for a defined price | A scoped first use case |
How long does an AI consulting engagement take?
It starts with a working session to find the right workflow, and that first workflow goes live in four weeks, built by agents and steered by senior engineers. After that the timeline depends on scope, but each new use case ships faster than the last because it reuses the platform, so the programme speeds up as it grows.
The first four weeks
The first weeks cover measuring the workflow, agreeing the baseline and the business case, building the agents and the controls around them in your cloud, and testing against real cases before go-live. On a credit management engagement, a working prototype ran in the client’s own cloud tenant within two and a half weeks, and the system went on to take £14m a year out of labour cost.
Why it gets faster
Delivery runs on an agentic software lifecycle in which agents do most of the engineering and senior engineers sign off what ships, which is about 60% faster than a conventional build. The bigger gain comes later, when the business context, permissions and integrations built for the first use case are already in place for the second.
- 1Working sessionFind the workflow and what it could return
- 2First four weeksMeasure, build, test and go live
- 3Next use casesEach ships faster on the shared platform
- 4Agentic EnterpriseAgents run operations, with people on the judgement calls
How do you measure the ROI of AI consulting?
Measure the workflow before anything is built, agree the baseline and track the same numbers once the system is live: hours returned, cost removed, revenue gained, errors avoided and cycle time. The return should be visible in the business’s own figures, which is why Elsewhen models it before the build and ties its fee to it wherever possible.
What the numbers look like
Agents onboarding loan portfolios took £14m a year out of labour cost and cut source-to-servicing cycle time by 92%. An audience copilot at a global marketing group returns £17m a year of planner time and runs in production across 62 countries. AI search for a European travel brand is worth £50m a year in additional booking revenue, based on reported financial results.
Leading and lagging measures
Cost and revenue take a quarter or more to show, so a good engagement also tracks the share of cases an agent completes without rework and the time from request to resolution, which move within weeks and give early warning of whether the larger numbers will follow. Both are reported from the first month.
- £14ma year of labour cost out, from agents that onboard loan portfolios in weeksRead the case study
- £17ma year of planner time returned at a global marketing group, from audiences built with synthetic dataRead the case study
- £50ma year in additional booking revenue for a European travel brand, based on reported financial resultsRead the case study
How do you choose an AI consulting partner?
Choose the partner whose senior people will build what they recommend, in your environment, against a return they are paid on. Check their production work and how it was measured, who owns the code and IP afterwards, how they handle your security review, and whether their architecture lets a newer model swap in without a rebuild.
Questions to ask
Ask for the systems they have running and what each returns, stated with how it was measured. Ask whether the people in the pitch are the people who build, how releases are tested and what the defect rate is, and what happens to the fee if the return falls short. Ask who owns the system, the code and the IP, and whether anything leaves your estate.
Working with Elsewhen
We are a London AI consultancy, and our teams work alongside yours in person. Elsewhen has offices in London, Manchester and Dallas, with a senior UK squad forward deployed with the people who do the work, and it is a Google Cloud Partner and a Crown Commercial Service supplier, named in the FT 1000 Europe’s Fastest Growing Companies 2026.
For the layer that makes AI work across a whole business, see what we do as an applied AI company.
- 2011Founded, with offices in London, Manchester and Dallas
- 200+Client engagements delivered
- 150People across strategy, design and engineering
Do you work with companies outside London?
Yes. Elsewhen is a London AI consultancy, with further offices in Manchester and Dallas. Most engagements run with a senior UK squad embedded with the client team, working in person in London and the South East and remotely across the UK and Europe.
Where the team sits
The squad is UK-based and forward deployed alongside the people who do the work, with no offshore handoffs, so the engineers who scope the system are in the room while it is built.
| Office | Address |
|---|---|
| London | 86-90 Paul Street, London EC2A 4NE |
| Manchester | 1 St Peter’s Square, Manchester M2 3DE |
| Dallas | 5960 Berkshire Lane, Dallas, TX 75225 |
Start with one workflow
Bring the workflow that costs you the most. Leave a working session knowing what it could return and what it would take to build.