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2 min read

How much does conversational AI cost?

Silviu Major·Founder, Fiveleaf·

Nobody can give you a real number without seeing your systems, and anyone who does is guessing. What I can give you is the benchmark that actually helps.

A capable in-house AI engineer in the UK runs around £90,000 a year fully loaded, so call it £8,000 to £10,000 a month. Most businesses that go the in-house route end up needing a second one, because an agent nobody maintains freezes in place and starts underperforming within months.

That is the number to hold everything else against.

The four routes, roughly priced

Off-the-shelf platforms. Low setup, predictable monthly fee, usually with a per-resolution or per-message component that can move around more than you would like. Right call if you are already on that platform's stack and your needs are generic.

Build it in-house. No vendor fee, full control, and the full engineering cost sits with you. Plus the ongoing operating burden, which is the part that gets underestimated.

A specialist partner. Structured build fee plus a managed monthly retainer. The honest benchmark is that this tends to land at less than the cost of one to two in-house engineers, with the ongoing tuning included.

Big consultancy. Six figures across a multi-phase programme. Correct answer if you are a FTSE 250 with formal procurement. Heavy for a mid-market operator who needs something working next quarter.

What actually drives the number

Not the model. Model cost is a rounding error next to the rest.

It is how accessible your systems are. Connecting to a platform with a clean, documented API is quick. Connecting to a legacy billing system where one internal developer controls every endpoint and is busy until March is where the money and the timeline go.

In our own builds, the slowest part has never been the AI. It has been waiting on access to a client-side system that one person owns. The conversational logic is usually ready in days.

That is why the first question a serious partner asks is about your stack rather than about your use case.

The number people forget

Ongoing tuning. Prices change, policies change, real customers find corners no test anticipated. An agent built on a knowledge base that was accurate at launch and never touched again will be confidently wrong within a few months.

If a quote does not include that, you are being quoted for a project rather than a service, and you should budget internal time to cover the gap.

How to make a quote comparable

Ask for three things in writing: what is in the setup fee, what is in the monthly fee, and what triggers the monthly fee going up. More agents, more channels, more volume, all reasonable, all worth knowing before you sign.

Then ask what leaving costs. A partner who answers that without flinching is relying on results rather than lock-in.

If a vendor cannot answer those crisply, the pricing is not going to get clearer after you have signed.

Frequently asked

Why will nobody publish a price list?
Because the number depends almost entirely on how accessible your systems are, and that is invisible until someone looks. Connecting to a modern platform with a clean API is fast. Connecting to a legacy billing system that one person owns is where timelines and budgets move. A published price would be a guess dressed up as a quote.
What ongoing costs should I expect after the build?
Hosting, model usage, and the tuning that keeps the agent accurate as your prices and policies change. That last one is the cost people forget, and it is why agents that were excellent at launch are confidently wrong six months later.
Is it cheaper than hiring?
Usually, but that is the wrong comparison on its own. A hire gives you judgment and can handle the complex conversations an agent should escalate. The fair comparison is against hiring for the repetitive contact specifically, which is where the economics are clearly favourable.

If you want help building this

Building AI agents into a mid-market business is what Fiveleaf does.

Bespoke build, fully integrated, continuously optimised. A 30-minute discovery call is enough to tell you honestly whether AI agents fit your team right now, or whether you’re better off waiting six months. No pitch.

About the author

Silviu Major, Founder, Fiveleaf

Silviu Major

Founder, Fiveleaf

10+ years building automation systems inside enterprise SaaS, now applying that same operational rigour to AI implementation for mid-market businesses. Writes about what works (and what doesn’t) from inside live deployments, not from the outside looking in.

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