Tenhaw vs Big Four

Choose a global consultancy when you need hundreds of people across multiple countries, deep multi-domain regulatory expertise, or when board expectation requires the brand. Choose a small forward-deployed firm like Tenhaw when you need senior operators building working systems inside your teams, a contractual exit, and pricing you can see before you engage. The determining question is usually whether you need scale or seniority.

Tenhaw's AI Readiness Audit is £44,000 fixed, and it ends in working prototypes rather than only a document, against an estimated £150,000–£500,000 for an equivalent large-firm assessment. The gap is the shape of the team rather than the day rate, because fewer, more senior people over four weeks leave no pyramid to fund. Our rate card is published so you can check the arithmetic, and the pricing page sets it beside the large firms' own G-Cloud framework rates. The Big Four cards we could locate run 1.7 to 1.8 times ours at the top grade, not the four times often claimed, and across every large firm on the framework the range is 1.3 to 2.3, with several cheaper than us at mid grades. A global firm's overhead is real and its scale requires it. You are not buying scale here, you are buying far fewer people-days to reach the same answer.

Yes, and it is a common arrangement. The arrangement we are built for is Tenhaw running the agentic operating model and embedded delivery while a larger firm handles adjacent regulatory or systems-integration workstreams. We are explicit about the boundary and will say when the other supplier is better placed to own something.

When the programme is wider than the build. A global firm mobilises hundreds of people across countries inside a quarter, carries nine-figure indemnity, and puts tax, legal, audit and regulatory remediation under one contract, so a multi-country roll-out, or an agentic programme entangled with a remediation, is their buy and we will say so on the call. Tenhaw is the choice when the operating model, the engineering and the adoption have to move together inside your teams. Our founder co-designed HSBC Global Payment Solutions' target operating model for 500 teams against a $450 million budget, and our day rates are published so you can do the arithmetic before you engage.

On evidence and accountability. Named clients with checkable outcomes, published prices, monthly value delivered and reported against, and a contractual exit date with permanent-team recruitment in scope. The AI Readiness Audit exists partly as a low-risk way to test the working relationship before committing to a larger programme.

What we can put in front of you is live work. In the London specialty insurance market, confidential at the client's request, a two-week proof of concept turned PDFs into business intelligence on Azure over ground the business had circled for roughly a year, and month three is productionising it against the client's security standards. Behind that sits Velocity84, Tenhaw's build lab, and more than twenty agentic products across voice, video, document reading, mobile and go-to-market. No client is yet running one of ours in production. The engineer who paired with us through that entire fortnight finished it 70% confident they could run the process without us. If a supplier answers 100%, ask them the same question about a system they built two years ago.

Splitting them is the usual arrangement with a large consultancy, and it is where agentic programmes stall. The strategy firm hands over a target operating model and a roadmap, a systems integrator builds against it, and when adoption fails the two suppliers point at each other. Tenhaw is built the other way, with one forward-deployed squad of three, an Agentic Lead, an engineer and an adoption lead, owning the operating model and the engineering together, so the architecture and the build path are designed alongside each other. Where a large firm's breadth genuinely wins is a programme entangled with a regulatory remediation or a carve-out, reaching well past operating model and delivery into tax, legal or M&A integration.

Typically a comprehensive target operating model, an implementation roadmap and change materials, often with a proposal for the next phase attached. Some engagements do land production systems, and many produce excellent analysis the client then struggles to execute alone. A Tenhaw engagement is shaped to end in a different state: agentic workflows with named internal owners inside your own estate, a permanent team recruited and in post, and documentation. The exit date is agreed at kickoff rather than negotiated at the end, the final sixty days run as a taper, and you own the code, the documentation and the work product on the day it closes.

Usually, with one honest exception. If your procurement floor requires nine-figure indemnity cover, a global firm clears it and we do not, so that settles the choice. Large firms hold established procurement, insurance and indemnity positions that pass enterprise legal easily. What a boutique brings to the same review is checkable detail: published day rates and engagement prices, insurance figures stated openly with limits that can be increased for a specific engagement at request and priced in, BS7858 screening before any client access, UK data residency by default with EU available, and 24-hour personal-data-breach notification as a term of the DPA.

Not necessarily, though two cases point that way. If your board or regulator specifically expects a Big Four name on the work, that settles it and we will not argue with it. If the agentic programme is entangled with a regulatory remediation or a carve-out, their multi-domain regulatory and audit depth is real and a specialist cannot match it. Tenhaw's depth is narrower, running to delivery and governance, and the page says so. Behind that sits the founder co-leading the design of HSBC Global Payment Solutions' target operating model for 500 teams, and a live engagement in London specialty insurance, confidential at the client's request, where a proof of concept is being productionised now.

In most large-firm engagements a partner sells the work, a senior manager oversees it, and delivery is staffed by consultants typically two to eight years into their career. The expertise that won the pitch is rarely the expertise in your rooms afterwards. That pyramid is not a flaw, it is what funds global scale, and it is exactly how a firm puts 200 people across twelve countries next quarter. Tenhaw makes the opposite trade and fields a forward-deployed squad of three, an Agentic Lead, an engineer and an adoption lead, every one of them senior, with James Rooney personally accountable for the engagement. Scale against seniority per pound is the whole choice.

No. The Big Four are the audit firms: Deloitte, EY, KPMG and PwC. Accenture sits outside that group, as do McKinsey, PA Consulting and TCS, and our pricing page keeps them separate for exactly that reason. On an AI shortlist the label rarely decides anything, because all of them sell the same delivery model: a partner-led pyramid, global reach, and depth across regulation, tax and technology under one contract. That is the model this page sets against a forward-deployed squad of three senior people. Accenture, Deloitte, KPMG and EY all publish day rates on the G-Cloud framework, each card linked at the foot of this page, so you can put their numbers beside ours.

The adoption lead, and they sit inside the squad of three rather than arriving as a separate change workstream once the build is done. A Tenhaw squad is an Agentic Lead, an engineer and an adoption lead, so the person accountable for whether anyone uses the thing is in the room while it is being designed. A large-firm engagement more often hands over change materials alongside the operating model, which is how so much genuinely good analysis ends up unexecuted. Agentic workflows need named internal owners, and those have to be your people, so the honest limit sits on your side. If the organisation will not free them up, no supplier fixes that.

Because the engagement is structured to end, and writing that into the scope is the only way to prove it. A large firm's model is time-and-materials or milestone-based with account growth as an explicit commercial objective. Good firms manage that tension professionally, but it does reward extended tenure in a way a small firm's model cannot. Tenhaw sells a fixed-price audit and then monthly retainers, with the exit date agreed at kickoff, permanent-team recruitment as a stated deliverable and a final sixty days that run as a taper. Recruiting your team is rarely in scope for a large consultancy. Here it is one of the things you are buying.

Because a quarter is a long time to wait to find out whether an agent can actually do the job. Agentic work turns on questions you cannot settle on paper: whether the data supports the task, whether accuracy holds on your own exceptions, whether people accept the handover. A milestone plan defers those answers to the gate. Tenhaw commits to a monthly increment instead, reported against, and a month that delivers no measurable value is reported as a failed month rather than absorbed into the plan. The problem is not the gate itself but the gap. If your governance requires one, make the monthly increment the evidence you carry into it.

It varies by engagement, which is the honest answer and also the reason to ask it early and specifically. Some large-firm engagements do land working systems, and plenty end at analysis the client is then left to execute alone. With any supplier, the checkable version of the question is which repository the work lands in, who holds commit access, and whose infrastructure it runs on. On a Tenhaw engagement one of the three seats is an engineer, so code is written from the first weeks, inside your estate and under your policies, and you own it as it is written rather than receiving it at handover. Ask both suppliers to show you the repository.

Yes, and that is a legitimate way to buy it. The AI Readiness Audit is £44,000 fixed over four weeks, standalone, with no obligation to continue. It produces the material a tender is usually missing: which workflows are worth doing, what your data and controls will actually support, and working prototypes instead of a hypothesis. Take that into a procurement process and you are specifying a defined scope rather than paying a discovery phase to produce one, which also makes the bids comparable. A recommendation to stop is a valid outcome here too, and four weeks is a cheap place to learn it.

Yes, and we would not start by redoing the strategy. The four-week audit tests the model against what agents can actually do inside your estate: your data, your access controls, and the exceptions that decide whether a workflow survives contact with real volume. Where it holds up you have a build path and an engineer in the squad to start on it. Where a workflow does not survive that test, you have it in writing for £44,000 in four weeks rather than halfway through a build. If what you need next is the scale to roll the model out across many countries rather than engineering judgement about it, the firm that wrote it can staff that and we cannot.

There is no published evidence that they do. What the data does show is that longer programmes overrun more, larger teams carry more risk, and engagements priced on inputs do not reward finishing early. Those are properties of the delivery model rather than anyone's intent, and they apply to any supplier who sells a large, long, day-rate programme. The National Audit Office, looking at consultancy engagements that ran past their scoped length, put the extensions down to the departments buying them rather than the firms selling them.

Not always, and the finding has a limit. On software builds the evidence is fairly direct. A comparison of 390 applications found teams of nine or more cutting the schedule by about 30% against teams of under four, while cost rose 350% and defects rose 500%. Across whole programmes the finding is about risk rather than raw speed, because underperformance rises sharply past eighteen months and past a team of twenty. A small team is not automatically faster. It is exposed to less of what makes programmes fail.