Intelligence dossier — 2026 edition
Artificial Intelligence services that change how your organisation makes decisions
We work with mid-size UK companies to design, build, and run AI systems that solve specific problems. Not general promises. Specific pipelines, specific models, measurable shifts in how fast and how accurately you operate.
Why this dossier exists
Most AI pitches start with a technology and work backwards to a problem. Ours starts with a question: what decision in your business takes too long, costs too much, or relies on a person who shouldn't be doing it? That question determines everything we build.
We are a seven-person consultancy based in England. Our founder spent nine years building recommendation engines for retail before realising that the real gap in the market wasn't better algorithms. It was better framing. Companies don't need a neural network explained to them. They need someone to sit in a room, look at their data, and say: here is what a model can do for you in the next 90 days, and here is what it can't.
This page is structured like a briefing document, not a sales brochure. Read the sections that matter to you, skip the rest. If something resonates, the inquiry form is near the bottom.
AI readiness assessment — where do you stand?
| Dimension | Low readiness | Moderate | High readiness |
|---|---|---|---|
| Data quality | Scattered spreadsheets, no central store | Warehouse exists, partial coverage | Clean, governed, API-accessible |
| Team capability | No in-house data skills | Analyst team, no ML experience | Data scientists on staff |
| Leadership buy-in | Curiosity only | Budget allocated, unclear scope | Executive sponsor, defined KPIs |
| Regulatory awareness | Unaware of AI Act obligations | Legal review pending | Compliance framework in place |
| Infrastructure | On-premise only, no GPU access | Cloud account, basic compute | Scalable ML pipeline, CI/CD |
Core capability: model selection and integration
We evaluate open-source and commercial models against your data, latency requirements, and compliance constraints. The output is a ranked shortlist with cost projections, not a vague recommendation to "use GPT."
For document-heavy workflows, we fine-tune smaller language models that run inside your firewall. A 7-billion-parameter model fine-tuned on 12,000 of your own records will outperform a 70-billion-parameter general model on your specific task, at a fraction of the inference cost.
Data pipeline design
We build extraction, transformation, and loading pipelines that feed your models with clean, timely data. Airflow, dbt, or custom orchestration depending on your stack.
Monitoring and drift detection
Models degrade. We set up automated monitoring that flags distribution drift, latency spikes, and accuracy drops before they reach your users.
Compliance review
The EU AI Act affects UK exporters. We map your use cases to risk tiers and prepare the documentation regulators expect, including data provenance records and bias audits.
Team upskilling
We run two-day workshops for your analysts and engineers covering prompt engineering, evaluation metrics, and safe deployment patterns. Practical exercises, no slides-only lectures.
How an engagement unfolds
Scoping call (45 minutes, free)
We listen. You describe the problem, the data you have, and the outcome you want. We ask pointed questions about volume, latency, and who will use the output. No pitch deck.
Data audit (1–2 weeks)
We examine a sample of your data under NDA. The deliverable is a written report: what's usable, what's missing, and what cleaning is required. This report is yours to keep regardless of whether you proceed.
Proof of concept (3–6 weeks)
We build a working prototype against a narrow slice of the problem. You evaluate it with real users. If the results don't meet the agreed threshold, we stop and you owe nothing beyond the audit fee.
Production build (6–14 weeks)
The validated model moves into your production environment. We handle containerisation, API design, load testing, and integration with your existing systems. Your team gets full access to the codebase from day one.
Ongoing support (monthly retainer, optional)
Retraining schedules, drift alerts, quarterly performance reviews. We also handle model version upgrades when new architectures become available that would meaningfully improve your results.
We deliberately keep our client roster small. At any given time we work with no more than four organisations simultaneously. This isn't a scarcity tactic. It's a constraint born from experience: AI projects fail when the consultancy is spread too thin to understand the client's data deeply enough.
If our calendar is full when you reach out, we'll tell you honestly and suggest a realistic start date. We don't take deposits for work we can't begin within 30 days.
Common questions we hear in scoping calls
No. We can operate as your entire ML function during the engagement. However, if your goal is long-term independence, we recommend hiring at least one data-literate engineer by the time we reach production build. We'll help write the job spec.
Everyone's data is messy. The audit phase exists precisely for this reason. We've built classifiers on datasets where 30% of labels were wrong by first training a label-correction model. Messy data is a solvable engineering problem, not a blocker.
The scoping call is free. The data audit is a fixed fee agreed upfront, typically between £3,000 and £8,000 depending on data complexity. Proof of concept and production build are priced per project based on scope. We don't bill by the hour for delivery work because it incentivises slowness.
Yes. We deploy on AWS, Azure, and GCP. If you have a strong preference or existing credits, we'll use your account. We also support on-premise deployment for clients in regulated sectors who cannot send data to the cloud.
All custom code, fine-tuned model weights, and documentation we produce during an engagement belong to you. We retain no licence to your data or outputs. This is non-negotiable and written into every contract.
Start a conversation
Describe your situation in a few sentences. We respond within two working days, usually sooner.
7 Leopold Field, Upton Bernhard, England, DQ80 0UV
Legal information
Forward AI Thinking collects only the personal data you voluntarily submit through our inquiry form: your name, email address, and message content. We use this data solely to respond to your inquiry and do not share it with third parties except where required by law.
We store inquiry data on encrypted servers within the UK for up to 24 months after our last communication with you, after which it is permanently deleted. You may request access to, correction of, or deletion of your data at any time by emailing [email protected].
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These terms are governed by the laws of England and Wales. Last updated January 2026.
The information provided on this website does not constitute professional advice. While we strive for accuracy, Forward AI Thinking accepts no liability for decisions made based on the content of this site without a formal engagement agreement in place.
References to specific technologies, frameworks, or third-party services are for informational purposes and do not imply endorsement or partnership. Performance figures cited on this page relate to specific client engagements and may not be representative of outcomes in different contexts.