Will it replace our agents?

No. It removes the repetitive contacts and shortens the rest. The teams that get the most value move agents onto the complex, revenue-affecting work the queue never left time for.

How does it handle Arabic dialects?

Recognition is tuned on your own call recordings so it hears your customers, not a generic corpus. Responses are written in the register your brand uses, which in most Gulf enterprises is clear modern standard Arabic rather than dialect.

What stops it inventing an answer?

Retrieval from approved sources only, a refusal path when confidence is low, and an evaluation set that runs on every change. Unanswerable contacts go to a human rather than to a guess.

Healthcare & Life Sciences · Contact centre automation

Patient contact automation

Resolve routine contacts end to end, and give agents a copilot for the rest.

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First-contact resolutionAverage handle timeContainment rateTransfer and repeat-contact rate

The problem

What this fixes

Appointment booking, rescheduling, results enquiries and insurance approval questions overwhelm the call centre, and the missed calls become missed appointments and empty clinic slots.

An automation layer across voice, chat, WhatsApp and email that answers the repetitive contacts on its own and assists a human on the complex ones. It reads the same systems your agents read, so an answer is grounded in the customer's actual record rather than a generic script. Arabic and English are handled natively, including dialect on the inbound side.

Healthcare & Life Sciences

Booking and rescheduling

Slots offered against real clinic capacity and confirmed in the HIS during the call.

Healthcare & Life Sciences

No-show recovery

Reminders and automatic re-offer of released slots to the waiting list.

Healthcare & Life Sciences

Pre-visit preparation

Fasting, medication and document instructions delivered in the patient's language.

Healthcare & Life Sciences

Clinical escalation is immediate

Symptom or distress signals hand straight to a clinician; the agent never gives clinical advice.

In this sector

Where it earns its place

Delivery

How we build it

Foundation check

Before any build

We inspect the systems, the data behind them and the quality of the records this capability will depend on, then write down what has to be fixed before anything is built.

Narrow first release

First release

One workflow, one team, real traffic, measured against the baseline we captured before we started.

Controls and evaluation

Runs in parallel

Guardrails, approval gates, evaluation sets, logging and the evidence pack your auditor and your regulator will ask for.

Scale and hand over

After sign-off

Additional workflows, sites or languages, then runbooks and training so your team can operate it without us.

Data foundation

What has to be right first

A single customer identity across channels, or the bot answers the wrong person's question.
Knowledge that is current and owned, an out-of-date policy page becomes a confidently wrong answer.
Write access to the systems of record, otherwise the customer is told to call back.
Call and transcript history for evaluation baselines.

Controls

Guardrails and KPIs

A human owns every consequential decision

Agents draft, route and execute reversible steps. Anything that moves money, changes a record of consequence or affects a person's rights stops at a named human approver with the reasoning attached.

Every action is logged and replayable

Inputs, retrieved context, model version, output and the human decision are written to an immutable log, so an auditor can reconstruct any single interaction months later.

Data stays where your regulator requires

In-country, in-region or on-premise deployment, with the model portfolio right-sized to the workload instead of routing everything to a frontier endpoint abroad.