KweekTechServices
AI agents and automation
Useful AI is not the kind that impresses in a demo. It is the kind that removes a task from your week.
The word "AI" now covers almost everything, which makes it useless for deciding anything. The narrower question is the one that pays: which task, repeated every day in your company, consists of reading something, understanding it, and then acting? That is exactly where an agent earns its cost, and nowhere else.
Three families keep coming up. Answering — customer questions on WhatsApp, on the site, by email, at any hour and in the customer’s language. Extracting — pulling data out of an invoice, a delivery note, an ID document, with no retyping. Classifying and routing — qualifying inbound requests and sending them to the right person at the right urgency.
An agent has to know its limits. One that invents an answer rather than stay silent will cost you more than having no agent at all. It must be able to say "I am handing this to a human", and that handover has to genuinely work. We build that first, before anything goes live.
What is included
Customer-facing agent
On WhatsApp, your website or email. It answers on your products, pricing, hours and terms — from your documents, not from general knowledge — and hands over the moment it leaves its scope.
Document understanding
Supplier invoices, delivery notes, quotes, identity documents: data extracted and pushed straight into your management system. Retyping disappears, and typos with it.
Triage and routing
Inbound requests qualified, tagged and directed to the right person. An urgent case no longer spends the night in a shared inbox.
Workflow automation
Overdue invoice chasing, booking confirmations, appointment reminders, the report that goes out every Monday. Simple tasks that never happen on time when they depend on a person remembering.
Retrieval over your documents
A system that answers by quoting your own contracts, procedures and specifications, with the source attached. Valuable as soon as company knowledge lives in two people’s heads.
Guardrails and measurement
Explicit limits, human handover, a log of every conversation, and tracking of what the agent actually resolved. Without measurement nobody can say whether it is working.
Who it is for
- Businesses answering the same questions on WhatsApp every day
- Companies retyping invoices or delivery notes by hand
- Support teams that saturate in peak season
- Organisations whose procedures are written down nowhere
What drives the price
- How many channels are connected: one agent on WhatsApp costs less than one present on four channels with shared history.
- The quality and volume of documentation to give it. If nothing is written down, it has to be written first.
- Connections to your systems: checking stock or creating a booking needs an integration; answering a question does not.
- Monthly message or document volume, which drives running cost — models are billed by usage.
- The level of control required: human approval before sending, full audit trail, data retention rules.
Frequently asked questions
Can an AI agent replace our support team?
No, and it should not be sold that way. It absorbs the repetitive questions — hours, availability, pricing, order status — which are usually most of the volume, and frees your people for the requests that genuinely need a human. An agent that claims to handle everything ends up driving customers away.
Which languages does it handle?
Arabic, French and English, including Tunisian dialect. This matters more than it sounds: a single day in a Tunisian business mixes all three. The agent replies in the language of the incoming message without the customer choosing.
Where does our data go?
A decision to make before building, not after. Depending on sensitivity we either use a hosted model from a provider with a contractual no-training commitment, or an open model running on infrastructure you control. The second costs more to run; for health or legal data it is justified.
How do you stop it inventing answers?
By constraining it to answer only from your documents, making it cite its source, and giving it an explicit exit when it finds nothing. This is a matter of construction, not of model: an excellent model poorly constrained will hallucinate, a modest one properly constrained will not.
Where should we start?
One task, measured. Take the question you receive most often, put an agent on it, and after a month look at how many messages it genuinely handled without intervention. If the number is good, widen. If not, you have spent a month rather than a budget.
Related services
Further reading
- AI agents in business: where they pay, and where they do not
AI agents for business: which tasks genuinely pay, how to prevent hallucinated answers and how to measure real results.
- Offshore and nearshore software development in Tunisia
Offshore and nearshore software development in Tunisia: time zone, languages, engineering supply and what to check before signing.
- Why site speed matters more in emerging markets
Why website speed matters more in emerging markets: metered mobile data, older devices and the real cost of unoptimised images.
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