AI assistants & conversational interfaces

Area: AI & Automation · Usual shape: conversation interface + knowledge source + review · Languages: Arabic and English

A useful assistant is not the one that knows everything; it is the one that knows its limits. We build assistants that answer from your own material — your documents, your policies, your catalogue — say "I don’t know" when they do not, and hand over to a person when they should. And we treat answer quality as something measured and reviewed after launch, rather than assumed before it.

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What this solves

Support answers the same twenty questions all day.
Questions arrive outside working hours and wait until morning.
The policies exist, and nobody finds them when they need them.
Customers ask about availability in separate messages, each answered by hand.

What we build

Scope first: what the assistant answers, and what it explicitly declines to answer.
A connection to your knowledge source: documents, a site, a catalogue, or a system.
A conversation interface in Arabic and English that works on a phone first.
Handover to a person by a clear route, carrying the conversation’s context.
Guard rails: what must not be said, what must not be shown, what must cite its source.
A log of what was asked and answered — the first month is what reveals the real questions.
A review loop: periodic measurement, correcting the source rather than patching the reply.

Where it is used

Customer support where a limited set of questions arrives in many phrasings.
An internal assistant for staff on policies, procedures and forms.
A question interface over a catalogue, ahead of talking to a person.
First-line triage that collects what your team needs before the real conversation.

What this does not include

We do not guarantee accuracy. We scope, measure and correct — and design on the basis that error is possible.
We do not build assistants that make a consequential decision on a person’s behalf.
We do not provide medical, legal or financial advice through an assistant, and do not build ones that do.
We do not train or fine-tune custom models.
We do not undertake that any external model provider stays available.

How the work goes

We start from the real questions: what actually arrived over recent months, not what might.
We define scope and refusal before the interface, because an assistant with no limits fails in a way that is hard to repair.
We launch to a limited audience first, read the log, then widen.
We agree who reviews answers and when, because an unattended assistant degrades quietly.

Document & text processing
when the need is reading many files, not answering questions.
Workflow automation
when the need is executing steps, not a conversation.
Customer & partner portals
when the customer needs their own records, not a general answer.
System & service integrations
when the assistant has to read from a system you already run.

Questions about this service

Where does the assistant get its answers?

From your material only, within the agreed scope. If a question falls outside it, the designed behaviour is to say so and hand over — not to compose an answer.

What if it gets something wrong?

It sometimes will, and we design on that basis: explicit limits, sources shown where they help, easy handover to a person, and a log that gets read. Anyone promising complete accuracy is promising something they do not have.

Does our data leave our systems?

We write it explicitly into the scope before starting: what is sent, where, and what is never sent. If some data must not leave, that is a design constraint from day one rather than an exception handled later.

Does it actually work in Arabic?

Arabic is not an add-on here. We test in Arabic as we test in English, using questions phrased the way they actually arrive rather than in ideal formal prose, because that is what the assistant will meet.

Can it be connected to a messaging channel?

We discuss channels within scope and verify what is genuinely available before promising it. We do not assume an external channel will permit what we want until we have checked.

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