AI Consultancy · folkfox
AI consultancy: the work that starts when the demo ends.
Most AI consultancy stops at the pilot. folkfox does the part nobody quotes for: evaluating what the system actually outputs, keeping it alive when a model is retired on sixty days’ notice, and proving what it costs per request. Founder-led, from Malta.
01 · Overview
The pilot was never the hard part.
AI consultancy is the work of getting an AI system into a business and keeping it working there. folkfox sells the second half of that sentence. Across the EU, 17 per cent of small enterprises use AI against 55 per cent of large ones, and the reason firms give most often for not adopting is missing in-house expertise, at 71 per cent. The constraint was never the model.
Getting a demo working is now genuinely easy, and that is the problem. The gap that shows up in the data is between instrumenting a system and knowing whether its output is any good: 89 per cent of teams have agent observability in place, but only 52 per cent evaluate output quality. Uptime and latency monitoring cannot see the failure modes that matter here. A system can be up, fast, cheap and confidently wrong.
So folkfox is not an AI automation agency that builds a thing and leaves. We take on the three jobs that sit after go-live and that no implementation vendor is filling: evaluation, model change management, and cost control per request.
| What we sell | Evaluation, model change management, AI cost control |
|---|---|
| Two ways in | A fixed-fee assessment, or a monthly retainer |
| Fees | Fixed where the scope can be defined |
| Sectors | Six lanes we already work in |
| Related | AI visibility, model briefings |
| Based | Malta, working across the UK, Ireland and Europe |
02 · After go-live
What actually breaks, and who pays for it
The model gets retired underneath you
This is the one buyers do not see coming. Anthropic states plainly that calls to a retired model stop working, notice has been as short as sixty days, and the vendor tells you to test your application against the replacement yourself. A system built once is a system that breaks on somebody else’s release schedule. That is a standing job, not a line in a project plan, and it is the reason folkfox sells a retainer rather than a handover.
Nobody can prove what it costs
The FinOps Foundation’s 2026 survey, 1,192 respondents representing over 83 billion dollars of cloud spend, found AI cost management is the single biggest skills gap its members name, and the capability most often missing is per-token and per-request visibility. Buyers cannot attribute AI spend to a workflow, so they cannot prove unit economics on it. Worth knowing before anyone tells you to put everything in the context window: OpenAI doubles its input price above 272,000 tokens, so that advice is quoted at a different rate than the one advertised.
The agent has no owner
Only 7.2 per cent of organisations name an individual responsible for what an AI agent does. Roughly a third apply the security controls they use for human staff to their agents, and a majority of executives report an AI-related incident or near miss in the past year. This is where an AI governance consultant earns the fee, and it is not a document exercise. It is deciding who is accountable, then building the evidence that shows they were.
03 · Pricing
How much does an AI consultant cost?
It is the question buyers ask most and the one agencies answer least. Here is the honest shape of the answer, and what moves it.
AI readiness assessment
Two weeks. What you already run, what it costs, what is worth automating and what is not. You get the working, never a single-number score.
Evaluation and assurance
Monthly. Output-quality evaluation, drift watch, model-retirement cover, and a cost-per-request line you can put in front of a finance director.
For context, UK day rates in this market sit somewhere around 950 to 1,500 pounds, and a fair amount of that is charged by people who cannot build the thing they are advising on. folkfox works to a fixed fee wherever the scope can be defined, and to a rate only where it genuinely cannot. Enterprise AI consulting for a larger programme is a conversation rather than a table, because the honest answer depends on what already exists. We would rather quote you properly than publish a number that turns out to be wrong for your situation.
Prices for our established services are published in full on our pricing page, including the row that says you do not need us yet.
How We Work
How Does an AI Engagement Work?#
Readiness, Honestly
The answer is sometimes that you do not need us yet.Two weeks looking at what you already run, what it costs, and which of your processes are actually shaped for automation. Buyer demand usually arrives brief-led, as a request to build a specific thing. We work back to the problem first, because a brief scoped to the wrong thing cannot be rescued later by good engineering.
Evaluation Before Build
If you cannot score it, you cannot improve it.We define what a good output looks like and build the test set that measures it, before anything is built. AI evaluation is the step 48 per cent of teams skip, and it is why so many AI projects cannot say whether they worked. It also gives you the artefact a regulator or an auditor asks for.
Build, Or Do Not
About thirty keyword rules beat a model, once.We build the smallest thing that passes the evaluation. Sometimes that is AI agent development. Sometimes it is a set of rules and a dropdown, which one practitioner found took accuracy from 92 to 99 per cent while removing the model entirely. We will tell you when the boring answer is the right one, and we will still charge less for it.
Handover, Then Watch
Model retirement notice has been as short as sixty days.Your team gets the evaluation harness, the cost instrumentation and the documentation to run it. Then we watch the things that change without asking: model deprecations, drift against the test set, and cost per request. Capability transfer is the point. Firms in the Lloyd’s market name skills and internal capability as their key AI challenge, not strategy, and they are right.
Sectors
Automation Does Not Mean the Same Thing Everywhere
The constraint that stops an AI project is almost always sector-specific, and it is almost never the model. Here is the one an outsider gets wrong in each of the six lanes we already work in.
Cybersecurity
A market that disbelieves vendor claims by default is a market where an unevaluated AI feature is a liability, not a differentiator.
FinTech
Under SCHUFA, the score itself is the automated decision. A supplier who calls the bank’s reviewer the human in the loop has it backwards.
Healthcare
The MHRA reads intended purpose from your promotional materials. Ad copy can make a tool a regulated medical device with no code change.
Music
Consent is layered: master owner, publisher, the artist’s voice, the session players’ union. Clearing the top layer clears nothing.
Web3
Tuning alert thresholds for precision, and adding a helpful onboarding assistant, are both the breach rather than the improvement.
iGaming
Automated player interaction sits inside the safer-gambling duty, so an experiment here is a regulated act rather than a growth test.
From the Desk
Working Notes#
AI Consultancy FAQ
Common Questions#
How much does an AI consultant cost?
UK day rates in this market currently sit somewhere around 950 to 1,500 pounds, and a fair amount of that is charged by people who cannot build the thing they are advising on. folkfox prices a readiness assessment as a fixed fee for two weeks, and evaluation and assurance monthly. We quote the number once we have seen what you already run, because a rate card written before that is a guess with a decimal point. Prices for our established services are published in full on our pricing page.
Is folkfox an AI automation agency or an AI consultancy?
Both words describe part of it, and so does AI implementation consulting. We do build, and we do advise, but the distinguishing work is what happens after: evaluating outputs, covering model retirements, and instrumenting cost. If you want somebody to hand over a system and leave, we are the wrong shape and there are cheaper options.
Do frontier models make AI consultancy obsolete?
The honest evidence points the other way, and it comes from the people who measure model capability rather than sell it. METR, whose task-length research underpins most claims about AI replacing knowledge work, says its time horizon is closer to what a low-context person can do, naming a new hire or a remote internet contractor as the comparison. It adds that most jobs are not composed of well-specified, algorithmic tasks, and involve success metrics that cannot be algorithmically scored. Model capability keeps rising. Knowing your data, your regulator and your customers is what it does not include.
Which model should we use?
It depends on the workload, and be careful with benchmark claims: each vendor publishes tables in which its own model wins, and the highest scorer is sometimes not purchasable at all. GPT-6 Astra and Claude Fable 5.1 both list at 10 dollars per million input tokens. The real cost difference comes from architecture, caching and context length rather than the headline rate, which is a decision worth getting right once.
Will you do our AI visibility and llms.txt?
We will do the visibility work, on our AI visibility page. We will not sell you an llms.txt package. Google’s own guidance says no AI-specific file or markup is needed to appear in its generative features, Ahrefs measured 137,210 domains and found almost nothing ever requests the file, and OpenAI’s crawler documentation names robots.txt as the control surface. Selling it anyway would be taking money for a file nobody reads.
Do you work with companies outside your six sectors?
Yes. The six lanes are where we already know the regulator and the vocabulary, so we start faster and charge less. Outside them we say so, and we price the learning curve into the first engagement rather than passing it off as expertise.
Receipts: how we measure what we claim
- The 89 and 52 per cent evaluation figures, the 7.2 per cent accountability figure and the FinOps Foundation skills-gap finding are all from 2026 practitioner surveys with published sample sizes. The EU adoption split (17 against 55 per cent) is Eurostat data extracted December 2025. Ask us for the working behind any of them.
- We deliberately do not quote the widely repeated claim that 95 per cent of AI pilots fail. The underlying report says something different, its sample is 52 interviews and 153 leaders, and its central claim has been publicly criticised as insufficiently supported. It is a good statistic for selling and a bad one for being right.
- Search demand for this page was checked before it was written: the pricing question is in the People Also Ask block on three of the five UK commercial searches we sampled, which is why it is a heading here and answered in plain terms rather than hidden behind a form.
- What we will not do: No llms.txt packages. No single-number AI maturity scores. No borrowed failure statistics. No engagement where the deliverable is a deck and your team cannot run what we built.
Built by hand in Malta · last human edit · no template survived contact with the argument
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AI consultancy for teams who would rather have a system that keeps working than a pilot that once demoed well.