The audit and the proof of concept, answered in full.
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60 questions on the audit and the proof of concept, answered by Tenhaw, a UK AI consultancy and AI delivery partner based in London. Nothing here is a summary: each answer is the exact text from the page that owns it, and every group links back to that page for the context around it.
AI Readiness Audit
Answered on AI Readiness Audit, and rendered here in the same words.
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What is an AI readiness audit?
An AI readiness audit helps an organisation decide where AI could create useful, measurable value and what would need to change to achieve it. It examines the work, the available data, the risks and the support people need.
Tenhaw's audit covers product, internal processes, operations and software delivery. Over four weeks, we build two or three working prototypes with your team and turn the findings into a sequenced, costed plan. The fixed fee is £44,000, excluding VAT.
What does the audit actually look at?
Four connected areas: the product your customers use, the internal processes that run the business, operations and software delivery. We follow real workflows with the people who know them, review the data and examine the tools already in use.
That might mean exploring how a customer finds an answer, how a team gathers information for a decision, or how engineers test a change. We compare opportunities within and across the four areas so your board can decide where to invest first.
How much does an AI readiness assessment cost in the UK?
Tenhaw's AI Readiness Audit costs £44,000 fixed for an agreed four-week scope, excluding VAT. We agree the business areas, access and two or three prototype workflows before work starts. Organisation size shapes where we focus the four weeks; it does not create a different price band.
Pre-agreed expenses are charged at cost, and model and platform use sits on your own accounts. The fee covers the agreed deliverables. If you request a scope change, we agree it and any fee or timeline changes in writing before the additional work starts. When comparing assessments, check the deliverables, engineering time and client involvement as well as the fee.
Should we start with the audit or a proof of concept?
Choose the audit when you need to decide where to invest across the organisation. It explores four areas, tests two or three candidates and gives your board a costed plan.
A proof of concept fits when you already have one workflow in mind and want to find out whether the approach works. It costs £20,000–£55,000 fixed over two to four weeks, excluding VAT. Your team can use either engagement to learn before committing to a production build.
Who from Tenhaw actually does the work?
James Rooney leads every audit personally, supported by a senior operator and a build engineer. The operator explores workflows with your teams; the engineer pairs with your engineers to build and test the prototypes.
The fee is based on five partner days, twenty operator days and nine engineer days across the four weeks. Associates come through work James knows at first hand or referrals from people he has delivered with. Everyone completes BS7858-standard screening before client access, with written confidentiality and data-handling terms. Your Statement of Work names the people and their responsibilities.
Should we hire a Head of AI or run an audit first?
It depends on the decision you need to make. If you need permanent leadership, the hire matters. An audit can help define that role by establishing the opportunities, constraints and investment priorities they would inherit.
If your Head of AI is already in post, we can work with them over the four weeks to test their priorities and develop the plan with your teams. The audit provides evidence and delivery support while responsibility for the permanent role remains with your organisation.
What is included in the £44,000 audit price?
The agreed four weeks of work: two or three working prototypes, a heat map across the four domains, a constraint register, a decision inventory, an assessment of people and adoption, and an investment case. You also receive estimated running costs and a plan in three-month increments, capped at twelve months, presented to your leadership.
Code is built in your repositories, and you own the deliverables on payment of the applicable fees. VAT, pre-agreed expenses at cost and model or platform use on your accounts are separate. The fee is fixed for the agreed scope; client-requested changes are agreed in writing before additional work begins.
Can the audit sort out the AI tools we have already bought?
It can help you decide what to keep, improve, consolidate or retire. We map the tools people use, including informal use, to the workflows they support. Your colleagues can explain why they chose them, what helps and where they still have to work around a limitation.
We examine overlap and running costs alongside the opportunities for new work. The plan records the recommended changes and their reasons. Tenhaw does not sell software licences.
What does an AI readiness audit deliver in four weeks?
Two or three working prototypes and the evidence to decide what to do next. Each prototype runs against your real data in your tenancy, with measured accuracy, an assessment of confidence in the results and an estimated run cost per unit of work.
The written readout covers opportunities, constraints, decisions, people and adoption, the investment case and candidates to leave out. A costed plan sets out the next steps in three-month increments, capped at twelve months. Preparing a prototype for production is a separate scope.
How do you assess whether a data estate is ready for agentic AI?
We trace the data a real workflow needs: where it lives, who can access it, how complete it is and whether an answer can be checked against its source. Your teams help us find the exceptions and dependencies.
The prototypes then test those conditions in practice. We examine retrieval quality, missing context, permissions and links back to the source, and record what would need to improve before relying on the workflow. Findings apply to the data and workflows examined, with wider questions recorded for follow-up.
How do you work out where AI will not deliver value?
We compare the possible benefit with the data, risk, effort and running costs involved. Some candidates have too little volume to justify a build. Others need better information, a different process or a decision that should remain with a person.
Your team's examples help us understand which constraint matters. We record candidates to defer or stop with a reason, so you can revisit them if circumstances change. A simpler process improvement may be the useful outcome.
Which stakeholders need to be involved in an AI readiness audit?
The people doing the work and engineers who can pair on the prototypes are central. Their examples, judgement and feedback help us choose and test the candidates. We also need an executive sponsor empowered to decide within the agreed scope, the platform or data owner, and someone from risk to agree the classification and controls before prototyping.
Finance helps examine the cost baseline and investment assumptions. We agree the people, access and time needed during scoping so each team can plan its contribution.
How do you baseline current operating costs so AI savings can be measured later?
We record volume, elapsed time, people involved and rework for the workflow as it runs today, then work with your team to express that baseline in currency. Finance can check the assumptions and the value assigned to people's time.
Prototype results and estimated model and platform costs help us explore potential improvements against that baseline. Time released is capacity; it becomes a cash saving only if expenditure changes. The audit estimates the opportunity, while realised savings need to be measured after adoption in live work.
What security constraints are examined before an AI build starts?
We establish where the data may go, who may access it and which actions the prototype is allowed to take. That includes identity and access controls, scoped permissions, approved locations for model inference, data-handling requirements and the evidence your risk team needs.
The prototypes run in your tenancy on your contracts, within the controls agreed with your platform and risk owners. Those colleagues help us identify what can be tested and what needs another decision before work proceeds.
Can an audit tell us whether our engineering team can build AI-native?
It can show how your engineers work with the approach on the selected workflows, and where further support would help. We review how software is delivered today and pair with your engineers while building the prototypes.
That gives us practical evidence about requirements, implementation, testing and review. Their feedback helps identify useful changes to tools and working practices. Four weeks provides a view of the work examined, which you can use to plan further learning and delivery.
How does this compare with an AI strategy engagement from a large consultancy?
Compare the scope you need with the people and deliverables in each proposal. Tenhaw's audit is a four-week engagement at £44,000 excluding VAT, with James Rooney, a senior operator and a build engineer contributing an agreed allocation of time. It includes prototypes built with your engineers and a costed investment plan.
A larger firm may suit a broader international programme or a need for several specialist disciplines. Ask each supplier what it will test, what your team receives, who does the work and what involvement it needs from you. Our pricing page provides the rate card and published framework comparisons for context.
How do you make sure an audit ends in engineering work rather than slides?
Prototyping is part of the agreed scope, with an engineer allocated to build it. During weeks two and three, our engineer pairs with yours on two or three workflows using your real data and repositories.
The tests and your team's feedback inform the plan presented in week four. You can inspect the code and results as they develop, and you own the deliverables on payment even if the audit is the only engagement you buy.
What is the return on £44,000 spent before committing to a build?
The audit helps you make a better investment decision. It can identify a promising workflow, expose a costly dependency or show why a proposed build should stop. The value of that decision depends on the work and spend under consideration; we do not promise a financial return from the audit.
You receive a cost baseline, prototype measurements, running-cost estimates and a plan with assumptions your finance team can examine. Together, those give you a way to judge the next investment before making it.
Can the audit be used as AI due diligence before an acquisition?
Yes, as an operational assessment scoped to the target or business unit, at the same £44,000 fixed fee over four weeks, excluding VAT. We examine the work, systems, evidence of value and dependencies within the agreed scope.
Access to the people doing the work, engineers and relevant data is needed for the prototypes. We check whether that involvement is practical within your transaction timetable before you commit. Legal, financial and regulatory due diligence remain separate specialist work.
Is an agent readiness audit the same as an AI readiness audit?
Tenhaw's service was originally called an Agent Readiness Audit. It now covers AI opportunities more broadly across product, internal processes, operations and software delivery. An agent is one possible approach to a workflow.
The agent-specific work remains in the decision inventory: what a system could act on, what a person should decide, and how consequences and reversibility shape that choice. The engagement runs four weeks at £44,000 fixed, excluding VAT, and tests two or three candidates as working prototypes.
Can you audit a programme our current AI supplier is already building?
Yes. We can examine the workflows, assumptions and proposed investment alongside your team and supplier. We agree access, responsibilities and scheduling before starting, including how to avoid disrupting ongoing work.
The audit tests two or three candidate workflows and compares the findings with expected value, feasibility and running costs. Your board receives a costed plan and recommendations about what to continue, change or stop. Tenhaw does not sell licences, and you can take the findings forward with your existing supplier.
What happens in the weeks after the audit readout?
The engagement ends after the agreed four weeks. Nothing renews automatically. You have the prototype code in your repositories, the written findings and a costed plan with review points. You own the deliverables on payment of the applicable fees.
Your team can take the plan forward, use another supplier or agree further work with Tenhaw. That could mean a focused proof of concept, operating-model design, a production build or programme support. Each is a separate scope, and a decision to stop is also a valid next step.
How many hours a week does the audit ask of our teams?
There is no single weekly allowance: it depends on the workflows, access arrangements and number of engineers pairing with us. We agree the expected involvement before you commit so your teams can make room for it.
Week one needs colleagues to walk through their work and help us understand the data. Weeks two and three need engineering time for pairing and colleagues to review prototype results. Week four needs the relevant leaders, with finance and risk input, to examine the findings and decide what follows.
Is the readout a document or a session with our board?
Both. You receive a written readout in seven sections and a session with your leadership in week four. We show the prototypes, explain the findings and work through the investment choices with you.
Bring the people who will own the decisions, alongside the finance and risk colleagues whose input the plan needs. They can examine the assumptions, ask about difficult cases and agree which questions still need answering.
Is the heat map a score out of five, or is there evidence behind it?
Each placement names its evidence. We rank the workflows examined by expected return and feasibility, using the workflow observations, available data, constraints and prototype results.
The two or three prototyped candidates have measured accuracy and an assessment of confidence in the results. Other candidates may have less direct evidence, which is made clear. Your team can see why a workflow sits where it does and which assumption or test could change its position.
Is four weeks long enough for an organisation our size?
Four weeks can answer a useful, bounded set of questions in a large organisation. Before starting, we agree which business areas and workflows to examine across the four domains and which two or three candidates to prototype.
It is not an exhaustive assessment of every operating company at once. We use the scoping conversation to establish whether the questions that matter can be answered within the time available. If they cannot, we say so before you commit and discuss a more focused starting point.
What if our board challenges the numbers in the investment case?
That is a useful part of the readout. Each value is stated in currency with the assumptions, confidence and arithmetic available for review. Your finance team can change the inputs and see how the case changes.
James Rooney leads the audit personally and can explain how the findings support the recommendation. The prototype results are there to examine too. A challenged assumption may change the order of investment or identify the next thing to test.
If the audit says do not proceed, do we still pay the £44,000?
Yes. The fee pays for the agreed assessment, prototypes and findings, including a recommendation to stop where the evidence supports it. You retain the written findings and own the deliverables on payment, whether or not you proceed.
A stop recommendation may apply to one workflow while others remain worth pursuing. The readout explains the reasons and the conditions that would justify revisiting the decision.
Does the costed plan go stale if we sit on it for six months?
Some assumptions may need refreshing. The plan marks review points within its three-month increments, capped at twelve months, so you can check what has changed before funding the next stage.
Model pricing, platform costs, data access, business volumes and team capacity can all affect the case. Your team can revisit those inputs alongside the baseline and constraints recorded during the audit. The age of the plan matters less than whether its assumptions still fit the work.
Do the prototypes cost us anything to run after the audit ends?
Model inference, compute and other platform use are charged on your own accounts during and after the audit. Those costs are separate from the £44,000 fee. You control the prototypes in your tenancy and can switch them off when you choose.
The audit includes an estimated run cost per unit of work for each candidate. Costs at production volume depend on the workload and the additional controls, monitoring and support needed for live use, so the prototype estimate is a starting point for that budget.
Can we put the audit prototypes straight into production?
No. They are built to test the selected workflows against your real data and provide evidence for an investment decision. A production system needs a separately agreed scope for hardening, assurance and operation.
Your engineers can build on the code in your repositories. The costed plan identifies the build work, dependencies and estimated costs involved in taking it forward, including the volumes and error tolerance the workflow needs to support.
What if our data access is not ready when week two starts?
We check access dependencies during scoping and address identity, permissions and risk classification early in week one. Your platform and data owners help us establish what can be reached and when, because the prototypes use your real data in your tenancy.
If access is delayed, we flag the effect on delivery in writing and work with your sponsor to agree how to proceed. We do not assume the original end date is achievable regardless of the delay. The fee remains fixed for the agreed scope; any requested scope change is agreed in writing before additional work starts.
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Talk it throughAgentic Proof of Concept
Answered on Agentic Proof of Concept, and rendered here in the same words.
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What is an agentic proof of concept?
A short fixed-price engagement, two to four weeks at Tenhaw, that takes one real workflow and builds a working agentic system against it, in your environment and against your data. The point is to replace an argument about feasibility with a working thing people can use. It is not a production deployment; productionising is scoped and costed separately.
How can a proof of concept take only two weeks?
By treating the requirements as the source code. Every requirement is converted into structured markdown, mapped for relationships, and interrogated for gaps and contradictions before any code is written; the build then runs against the whole requirement set at maximum model reasoning rather than file by file. The full method is published at tenhaw.com/the-tenhaw-way/building-with-ai.
Will our own engineers learn anything, or do you hand over a black box?
The build is pair-programmed with your engineers throughout, deliberately. On a recent engagement the client engineer who paired on a two-week build finished it saying they were 70% confident they could run the process unaided. Seventy per cent after a fortnight is the measured figure, and it is the difference between buying a proof of concept and starting to acquire a capability.
What does an agentic proof of concept cost?
Tenhaw prices agentic proofs of concept between £20,000 and £55,000 as a fixed fee for two to four weeks, depending on the complexity of the workflow and the state of the underlying data. The price is agreed before the work starts and does not move.
Can we contract your engineers by the day instead?
No. Tenhaw is not a staffing agency and does not place people by the day into someone else's plan, which is what lets us publish a rate card and stay accountable for the outcome. Senior people are supplied on an engagement with partner oversight behind them. If you want a single senior lead rather than a build, the closest thing on the ladder is programme and delivery management, where one lead runs delivery and governance without Tenhaw building any of it.
What happens if the proof of concept fails?
You get a documented answer to a question that would otherwise have cost far more to answer, plus the requirement corpus and gap analysis, which retain value regardless. A proof of concept that establishes a workflow is not viable has done its job, and we would rather tell you that in week three than in month nine.
What decides whether we pay £20k or £55k?
The complexity of the workflow, and the state of the data underneath it. Those set the two variables the price is built from, whether one or two Tenhaw engineers are on it and whether it runs two weeks or four, costed from the published senior practitioner rate of £1,250 a day. A tangled workflow with scattered data needs more of both and sits nearer £55,000; a well understood one with its data already in a single place sits nearer £20,000. Either way the number is fixed in writing before anyone starts, and the deliverable is fixed alongside it.
What do you need from us during a proof of concept?
Access, experts and engineers. The system is built in your environment against your real workflow, so we need that environment and the workflow's data from the first day. Your subject-matter experts are wanted around days four and five, once the gap-and-contradiction pass has surfaced what the written requirements contradict or leave out. And engineers of your own to pair with ours throughout, because your people finishing able to run the method is a measured deliverable rather than a hope. Data is the one hard prerequisite, and where it does not yet exist in any usable form, a proof of concept is the wrong place to start.
What happens week by week in a proof of concept?
Days one to three turn your existing requirements, the PDFs, diagrams and decks, into a structured markdown corpus, map the relationships and run the gap-and-contradiction pass, all before any code exists. Days four and five resolve those gaps with your subject-matter experts and record explicitly what we are proceeding without, and why. Week two is the build, paired with your engineers, with a security review roughly every fifth prompt, and it typically reaches around 80% correct by the end of it. Weeks three and four iterate toward roughly 95%, fold user-testing feedback back through the same corpus, and scope what production readiness would require.
Does a proof of concept commit us to anything afterwards?
No. It ends on a date agreed at the start with a fixed-price deliverable, nothing rolls on, and there is no retainer waiting on the other side. You keep the working system, the full requirement corpus as structured markdown, and a costed scope for what productionising it would take, all of it yours to extend or to hand to somebody else. Whether to build for production is a separate decision, and it is a better decision for being made with a working thing and a real number in front of you rather than bought in advance.
When is an agentic proof of concept the wrong thing to buy?
In three situations, all of them cheaper to spot now. An agentic proof of concept is the wrong buy when you do not yet know which workflow to attack, and the audit is the better answer there at £44,000 fixed over four weeks. It is wrong when what you actually need is a production deployment, because this ends in a proof of concept and hardening one for production is a longer, separately scoped job. And it is wrong where the data underneath the workflow does not yet exist in any usable form, because the fortnight then goes on building the source rather than the system.
Can a proof of concept cover more than one workflow?
No, and the narrowness is the point. One real workflow, in your environment and against your data, is what makes a fixed price over two to four weeks honest rather than a guess, and it is what leaves you with a measured result instead of two half-built things. A second workflow is a second engagement, scoped and priced on its own inside the £20,000 to £55,000 band. If choosing between candidates is the real problem, take the one whose result would settle the argument in the room, because that is where a working system earns the most.
Our requirements are out of date. Can we still start?
Yes, and that is the normal starting point. Nothing gets built before the requirements are dealt with. Whatever exists, the PDFs, diagrams and decks, is turned into a structured markdown corpus with the relationships mapped, then interrogated for gaps and contradictions. What that surfaces becomes the agenda for the sessions with your subject-matter experts, and anything still unresolved is recorded as something we are proceeding without, and why. So there is no tidying exercise to run before we start. The corpus is the tidying, and it is yours to keep and extend whatever you decide about the build.
What does a forward-deployed AI engineer do on a proof of concept?
They build, in your environment, next to your people. One or two of them are the whole team on this rung, at the published senior practitioner rate of £1,250 a day, each one someone James Rooney has already delivered alongside. The day-to-day work is turning the requirement corpus into a working system against your real data, pairing with your engineers from the first day so the method stays behind, and running a security review roughly every fifth prompt. If what you want instead is a senior person sitting in your stand-up for six months, that is the build team rather than this.
Do real users test the system before the proof of concept ends?
Yes, in weeks three and four. Week two produces the first working build, paired with your engineers, and the fortnight after it folds user-testing feedback back through the same requirement corpus rather than patching the code around it, iterating toward roughly 95% correct. That is also why the engagement ends with something your executives can use rather than a deck about one. It remains a proof of concept, so the testing answers whether the workflow works, and what a production rollout would take is scoped and costed as its own decision.
What do we show the board at the end of a proof of concept?
Four things: a working system your executives can use rather than a deck about one, a measured read on how much of the method your own people absorbed, a costed scope for productionisation as a separate decision, and evidence of whether this workflow is worth pursuing at all. Boards tend to underrate the last one, because evidence that a workflow is not worth pursuing is far more useful before a build is budgeted than after. And if the difficulty is that a plan will not persuade the sceptics in the room, a working system usually does.
Who builds the production version after the proof of concept?
Whoever you choose. You finish holding the working system, the requirement corpus and a costed scope for production, so the options are real ones: your own engineers, a different supplier entirely, or a Tenhaw agentic build team at £70,000 to £85,000 a month. Weeks three and four exist partly to produce that scope and that number, so the production question gets answered with a working thing and a real cost on the table. Your engineers having paired with ours throughout is what makes the first option a genuine one rather than a courtesy.
Who pays if a fixed-price proof of concept overruns?
We do. The number is agreed in writing before anyone starts and it does not move, and the deliverable is fixed alongside it, so an overrun is our problem rather than a change request pointed at you. That is a sane promise rather than a gamble because of where the unknowns surface. The requirements are interrogated for gaps and contradictions in week one, before any code exists, and whatever cannot be resolved is written down at the time. Fixed-price work goes wrong when that discovery lands in week three, and this sequence is built to stop it.
A software vendor offered us a free proof of concept. Why pay for yours?
Because a free vendor pilot is scoped to prove that product, and Tenhaw has no model, platform or licence to resell or take a margin on. What the fixed £20,000 to £55,000 buys is a working system in your own environment against your own data, one or two engineers pairing with yours while it is built, and the requirement corpus that produced it. If you were always going to buy that product anyway, let the vendor prove it and keep your money. What neither exercise can settle from outside is whether the workflow is worth automating at all, and that turns on volumes and the cost of an error, which only your operation knows.
Will a proof of concept still work at our real volumes?
Not on its own, and Tenhaw scopes that gap rather than glossing it. A proof of concept is built to answer one question, whether this workflow can be done at all, in your environment, against your data, inside two to four weeks. Throughput, error handling and identity carry deliberate shortcuts at that stage, which is why weeks three and four end with a costed assessment of what productionising would take rather than a claim that you are finished. The £20,000 to £55,000 buys the first answer cheaply. What sets the second is your peak volume and how unevenly it arrives, which your operations people already know and no fortnight can discover.
Can a proof of concept run on masked or synthetic data?
Masked data usually works, synthetic data usually does not, and since Tenhaw builds inside your environment under your own policies, with UK data residency by default and EU available, the choice is yours to make. The test is whether the mask preserves the features the decisions actually turn on. Replace a customer name and nothing changes; flatten the messy free text and the result flatters itself. Synthetic records fail that test because they are generated from the rules you already know, so the exceptions quietly vanish. The one hard prerequisite is data that exists in usable form, and whether your masked copy still carries the awkward cases is a question for your data owners.
How do we agree what counts as working before we sign?
In writing, before the fee is fixed. Tenhaw prices a proof of concept at £20,000 to £55,000 against a fixed deliverable, so what counts as working has to be settled first, and the reference it is settled against is the requirement corpus. Your existing documents are turned into structured markdown, interrogated for gaps and contradictions, with anything your subject-matter experts cannot resolve recorded explicitly as something the build proceeds without. Acceptance is then measured against that, rather than against somebody's memory of a meeting. What the corpus cannot decide for you is which specific cases must be right rather than what percentage, because that is a judgement about consequence your process owner owns.
How long does it take to get a proof of concept into production?
On Tenhaw's own live engagement, a proof of concept built in two weeks is being productionised over four to six weeks with a dedicated team. Treat that as the shape rather than a quote for yours. Weeks three and four of your own engagement exist partly to produce the number for the specific thing you have just watched work, which is why the costed assessment is a deliverable of the fixed fee rather than a follow-on proposal. Three things move it: the integration surface, the non-functional requirements your estate imposes, and how accurate the workflow must be before it runs unchecked. The last is a risk decision rather than an engineering one.
If the system breaks a month after you leave, who fixes it?
Your own engineers, and Tenhaw shapes the two to four weeks so that is realistic rather than a hope. They pair on the build from the first day, the code sits in your repositories as it is written, and the requirement corpus behind it is structured markdown they can read and extend, so a fix is a change to something they already know rather than a call to us. Be clear-eyed about what you are running, though. It was built to answer a question quickly, so it is a thing to learn from while you decide rather than one to leave unattended in front of customers. How much attention it needs meanwhile depends on who is using it, and how often.
Our engineers could try this themselves. Why pay for two weeks of yours?
If you have engineers who have already shipped an agentic system and can be freed for a fortnight, run it yourselves, because Tenhaw publishes the method free, failure modes included. What £20,000 to £55,000 buys is that the fortnight actually happens at a fixed price, with one or two engineers at the published senior practitioner rate of £1,250 a day whose only job for two to four weeks is this one, and a gap-and-contradiction pass run by somebody with no stake in which answer it produces. Internal attempts stall on the first of those far more often than the second. Whether your people can genuinely come off their current commitments is the thing to test before you decide.
Whose AI model licences does the build run on?
Yours, wherever you have an approved enterprise tenancy. Tenhaw does not resell or mark up models, platforms or licences, so the build runs inside your infrastructure on your own contracts, and nothing you specify becomes revenue for us. Where there is no approved stack, the default is named up front as Claude Code with OpenAI models and Gemini, best tool for the case, swapped for your preferred stack on request. The £20,000 to £55,000 is the fee for the work, costed from the published £1,250 senior practitioner day rate, with no licence margin underneath it. Whether your existing agreements cover the models this workflow needs is worth checking early, since procuring a new one can outlast a two-week build.
Does the fee come off the price if we go on to a build?
No, and the reason is worth knowing. Tenhaw prices the proof of concept standalone at £20,000 to £55,000, fixed, ending on the date agreed at kickoff. A fee credited against a later build would quietly put a price on the recommendation to stop, and a proof of concept that establishes a workflow is not viable has done its job. What you carry into the production decision instead is a working system, the requirement corpus and a costed scope, so the next number is a real one whoever ends up spending it. Which route that turns out to be depends on engineering capacity you have and we cannot see from here.
Should we pick our biggest workflow or our simplest one?
Neither, quite. Tenhaw's test is three conditions: the workflow's data already exists in usable form, its requirements exist in writing even if they are years out of date, and its subject-matter expert can be in the room on days four and five. Those are what let a fixed price hold over two to four weeks. Add one more test of your own, that your people can check the output quickly, because a result nobody can verify inside a day cannot be user-tested in weeks three and four. The biggest workflow in the business usually fails the first condition, and the simplest one rarely settles the argument you are running the exercise to settle.
All five engagements, priced side by side→
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Talk it through1427 questions, grouped by subject
Every question answered anywhere on tenhaw.com sits in one of 51 groups. This is one of them.
- Choosing between the five engagements22
- The design pair and the build team57
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Talk it throughStill have a question?
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