You have a real problem, not a curiosity
The best projects start with a pain point someone can describe in one sentence. "Our returns rate is climbing and we do not know why" is a great starting point. "We want to do something with AI" is not.
"We stopped chasing AI trends and started asking which problems actually deserved a model. Revenue from our recommendation engine grew 23% in five months." — Head of product, mid-market e-commerce retailer, Glasgow
That quote captures what we believe. Most AI projects fail not because the technology is wrong, but because the question was never right. We exist to close that gap.
Artificial Intelligence built on principles that outlast the hype
Outcome before algorithm
We refuse to pick a model and then hunt for a use case. Every engagement starts with a measurable business outcome you need to reach. The algorithm follows.
Data honesty
If your data is not ready, we say so. Polishing a dashboard on top of broken pipelines wastes everyone's time. We audit first, build second.
Ownership stays with you
Models, training data, documentation. All of it belongs to your organisation. No lock-in, no proprietary wrappers you cannot inspect.
Smallest viable scope
Large transformation programmes have a habit of collapsing under their own weight. We scope tightly, ship a working prototype inside six weeks, and expand only when the first version proves its value in production.
Explainability is non-negotiable
If a stakeholder cannot understand why the system made a decision, the system is not finished. We build interpretability into every deliverable.
Maintenance is part of delivery
A model that drifts after three months is a liability, not an asset. Our handover includes monitoring scripts, retraining schedules and a runbook your team can follow without us.
6 weeks average time to first working prototype
14 production models currently maintained by clients independently
3 industries served since 2022: retail, logistics, financial services
Capability map
We do not sell generic AI. Here is exactly what we deliver, what it involves, and who it is for.
| Capability | What we do | Typical client | Timeline |
|---|---|---|---|
| Data readiness audit | Map existing data sources, assess quality, identify gaps, produce a prioritised remediation plan | Organisations considering their first AI project | 2–3 weeks |
| Predictive model development | Build, validate and deploy supervised or unsupervised models for forecasting, classification or anomaly detection | Retailers, logistics firms with 12+ months of transactional data | 6–10 weeks |
| Natural language processing | Document classification, sentiment extraction, entity recognition, summarisation pipelines | Financial services compliance teams, customer support operations | 5–8 weeks |
| Computer vision integration | Object detection, quality inspection, visual search. On-premise or cloud deployment. | Manufacturers and warehouse operators | 8–14 weeks |
| AI strategy workshop | A two-day facilitated session that produces a ranked backlog of AI opportunities, feasibility scores and a 12-month roadmap | Leadership teams exploring where AI fits their growth plan | 2 days + 1 week report |
Is this a good fit?
We are selective about the work we take on. These three signals tell us whether a collaboration will produce lasting value or just a shiny demo.
You can give us access to data
We do not need perfect data. We do need access to it. If internal politics or regulation will block data sharing for months, we are honest that the project will stall.
Someone will own the outcome
Every project needs an internal champion who will use the model, challenge its outputs and push for adoption. Without that person, even a technically brilliant solution gathers dust.
Large language models are genuinely useful for certain tasks: drafting, summarisation, code assistance, internal knowledge retrieval. We help clients deploy them where they make sense.
They are not, however, a substitute for purpose-built predictive models trained on your own data. A general-purpose LLM will not forecast your warehouse demand with the precision a custom model can, and it will hallucinate confidently if you ask it to.
Our recommendation is usually a blend. Use an LLM for the tasks that benefit from broad language understanding. Build a focused model for the tasks that need accuracy, auditability and low latency. Know which is which before you spend a penny.
We have helped two financial services clients integrate retrieval-augmented generation into their compliance workflows. The results were strong, but only because we spent the first three weeks structuring the document corpus properly. The model was the easy part.
Questions we hear most
A data readiness audit starts at £4,500. Model development projects range from £15,000 to £45,000 depending on complexity and data volume. Strategy workshops are priced at £6,000 for the full engagement including the written roadmap. We quote fixed fees after a scoping call so there are no surprises.
Yes. Most of our client communication happens over video calls and secure data-sharing platforms. We have delivered projects for organisations in Edinburgh, London, Manchester and Birmingham. On-site visits are available when needed, typically for kickoff workshops and final handovers.
You receive the model, full documentation, monitoring dashboards and a retraining runbook. We offer an optional three-month support period where we review model performance weekly and retrain if drift is detected. After that, your team runs it independently.
We deploy on AWS, Azure and GCP. If you already have infrastructure in one of those environments, we build within it. We also support on-premise deployment for clients with strict data residency requirements.
Most failed AI projects share one of three root causes: unclear success criteria, poor data quality that nobody addressed, or no internal owner to drive adoption. Our scoping process is designed to surface all three before we write a single line of code. If we spot a blocker we cannot resolve, we will tell you before you commit budget.
Start a conversation
Describe the problem you are trying to solve. We will reply within two working days with an honest assessment of whether AI is the right tool and, if so, a suggested next step.
Prefer a call? Ring us on 01713 900920 or email [email protected].
Legal
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All project engagements are governed by a separate statement of work signed by both parties before any work begins. Pricing, timelines and deliverables referenced on this website are indicative and subject to change based on project scope.
Enduring AI Value reserves the right to decline any engagement at our discretion. We operate under the laws of Scotland. Last updated: January 2026.
The results, timelines and figures mentioned on this website reflect past project outcomes and are not guarantees of future performance. Every AI project depends on data quality, organisational readiness and scope, all of which vary between clients.
Enduring AI Value is not liable for decisions made based on the general information published here. For advice specific to your circumstances, please contact us directly.