AI and data strategy, centre of excellence set-up, and the technology decisions that have no AI in them. Scoped by the people who would deliver the result.
Every item carries a business case, an owner, and a target metric.
In brief
EigenSpark consulting is the work of deciding what a company should do about AI and technology before it spends anything building it. We assess the data, the systems, and the teams, then rank the opportunities against the business objectives the company is already measured on. A public sector bank started here and now runs a centre of excellence with 65+ AI use cases live. Another arrived for training and left with an operating model. Some engagements finish with a recommendation to build nothing.
The full scope
Modernise the legacy platform. Fix the integration layer that breaks every quarter. Build the data model that holds.
A steel producer came to us with an operations platform that had aged out. They needed a rebuild, an integration layer and a data model that held under load. We scoped it, engineered it, and it runs their operations today. Where the answer to your question is better engineering, that is the answer you get, and we build it.
See Custom AI & Digital Build →Why companies call
Five questions account for most of the consulting work we take on. Each one has a method behind it.
We rank every candidate use case against the objectives your board already tracks, and put the weak ones at the bottom in writing.
Usually the pilot was never scoped to survive production. We audit what you built, and tell you whether to finish it or stop paying for it.
One of those three, per use case, with the reasoning attached. We have no licence revenue riding on the answer.
A centre of excellence earns its cost above a certain volume of work. Below it, you want two good engineers and a clear owner.
Inference, infrastructure, retraining, and the people to operate it. We cost the running years as well as the build.
The engagements
Both are scoped and priced on their own. Neither requires the other.
The engagement that decides what is worth doing.
We work through your data estate, your systems, and the way your teams actually operate, then produce a ranked roadmap. Each use case carries a business case, an owner, a target metric, and a build, buy or stop recommendation. You approve the order before anything is designed.
Delivered across public sector banking
The engagement that makes the first win repeatable.
One working system is a project. A centre of excellence is what turns the next twenty into routine. We design the operating model, the intake and prioritisation process, the governance, and the skills map, then run it alongside your team until your own people are setting the agenda.
65+ use cases live at one public sector bank
What you receive
Your data, your systems, and the skills already in the building, read against what the work would need.
Every use case ordered, with the business case, the owner and the target metric written against each one.
A decision on every use case, and the reasoning behind it, including the ones we tell you to drop.
The architecture and the integration map, drawn against the systems you actually run.
Cost per use case: infrastructure, inference, retraining, and the people it takes to operate it.
How the work gets owned once we leave, and a centre of excellence where the volume justifies one.
Related
From a strategy engagement to a working centre of excellence.
→ Case studyTraining-led entry that became an operating model.
→ IndustryWhere most of this work happens, and the deepest page on the site.
→ ProductOften the first thing a roadmap recommends buying.
→ TrainingFor the people who have to sponsor the roadmap.
→ PillarWhat happens after the roadmap is approved.
→FAQs
No. The roadmap belongs to you and it is written so another firm could execute it. Most clients do continue with us, because the people who wrote the recommendation are the people who would deliver it, which removes a re-scoping cycle. Nothing in the engagement requires it.
Then that is the recommendation, in writing, with the reasoning. It has happened more than once. A recommendation to stop costs a fraction of a system nobody ends up using.
Yes. We review what exists, keep the parts that hold up, and tell you which parts do not survive contact with your actual data. You are not paying us to start again for the sake of it.
Someone who owns the business objective, someone who knows where the data really lives, and someone who can say yes to spending. Three people, a handful of sessions. We do not run month-long discovery workshops with twenty stakeholders.
No. A good share of the advisory work has no AI in it at all: whether to modernise a legacy platform or replace it, how to structure a data estate, what to do about an integration layer that keeps breaking. We take that work standalone and we bill it as what it is.
Tell us what you are trying to decide and what is riding on it. We reply within 48 hours.
Talk to us