How long does a chatbot project take?

A focused assistant over material you already have is typically weeks. What extends it is content: discovering that the policies it needs to quote are inconsistent, or exist only in someone's head. That work has to happen anyway — the chatbot just makes it unavoidable.

Will it handle Arabic properly?

Only if it is built and tested for it. Arabic capability is not a checkbox — it depends on model choice, on how your source material is prepared, and on testing against genuine customer messages including dialect and mixed Arabic-English. I test both languages against your own historical conversations, and someone who reads Arabic reviews the output before launch.

Can it connect to our systems, or only answer questions?

Both, and they are different levels of risk. Reading from a system — order status, availability, account balance — is straightforward. Writing to one is where confirmation steps, validation and audit logging become essential. I would generally launch a read-only version first and add actions once the assistant has earned some trust.

What does it cost to run?

There is a per-conversation cost that does not go away, so it should be modelled at realistic volume rather than pilot volume. It is usually modest against the alternative, but it is a line item that will be questioned at some point, and it is better to have the number ready than to be surprised by it.

What if it gives a customer wrong information?

You reduce the chance by grounding it strictly in approved material and testing it on the questions it should refuse. You manage the remainder by design: keep it away from commitments it cannot make, log every conversation, make handover easy, and be clear to the customer that they are talking to an assistant. Anything with legal or financial consequence should be prepared by the assistant and confirmed by a person.

How it should be measured

The industry's favourite metric is the proportion of conversations handled without a human. Taken alone it is actively misleading: a bot that frustrates people into giving up scores beautifully on it. Measure it alongside the things that catch that failure. Conversations resolved without a human — but only counted where the customer's question was actually answeredAbandonment: people who leave mid-conversation and never come back through any channelRepeat contacts on the same issue within a few days, which is the honest signal that a resolution was not oneTime to first useful response, in and outside working hoursHandover rate, and how long the handover takes once requestedQuestions asked that the assistant had no material for — the most valuable output of the whole system That last one deserves more attention than it gets. A chat assistant is the most direct record you will ever have of

What I will tell you not to build

An assistant on top of information that is wrong or out of date. This is the most common request I decline. If your product details differ across three systems, a chatbot does not fix that — it publishes the inconsistency to customers faster and more confidently than your website ever could. Fix the source, then build. An assistant that exists because a competitor has one. If you cannot name the five questions it will spend most of its time answering, it is not ready to be scoped, and the honest first step is to go and read a month of your own enquiries. And an assistant standing in for a process that should be automated instead. If customers are chatting to ask where their order is, the answer may be a status page and a notification rather than a conversation — that is workflow automation, and it is cheaper to run and impossible to get wrong in an interesting way.

We start with your real conversations — a month of enquiries, support tickets or messages — and group them. That produces the actual scope, which is almost always narrower and more boring than the one people imagine, and far more valuable. It also identifies the questions that must never be answered automatically. Then the boundaries: what it may access, what it must refuse, how it escalates, what it logs, and what it says when it is unsure. Then the build, then testing against those same real messages in both languages, then a limited launch — one channel, or one customer segment, or staff only — before it goes wide. After launch it needs an owner. Reviewing what it could not answer, adding the missing material, and keeping the sources current is a small recurring job that decides whether the assistant improves or quietly decays. I set that routine up and hand it over, with training for

Book: Custom AI assistant build

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Custom AI assistant build — KD 1,250.000, paid today. The assistant answering from your own documents and price list, on WhatsApp or your site, with the handover rules that decide when a person takes over, and training for whoever maintains it.

Running — KD 145 a month. Hosting, model usage, monitoring, answer corrections, from go-live, billed separately.