Case studies
A grounded assistant answering order, delivery and returns questions in Arabic and English, with a designed handover to a human.
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Illustrative example. Not a real client engagement — results are described qualitatively because no measured client figures have been cleared for publication.
01Challenge
A three-person support team answering the same order-status, delivery and returns questions hundreds of times a week, in Arabic and English, across WhatsApp and Instagram — with nothing outside working hours and no record a manager could search.
02Approach
Started from 600 real historical conversations to find what customers actually ask, rather than what the FAQ page assumes.
Grounded every answer in the order record or the published policy, with the assistant explicitly unable to state a price or date it has not retrieved.
Built an evaluation set including Gulf-dialect and code-switched messages, and gated launch on accuracy against it.
Made escalation a first-class path: the human receives the transcript, the retrieved sources and the assistant's uncertainty.
03Solution
A retrieval-grounded assistant connected to the order system and the returns policy, able to answer in Arabic, English or a mix of both, and to escalate anything outside its scope with the full conversation context attached.
04Features
Every response is retrieved from the order record or the published policy, and carries a source the support team can check.
Handles Gulf-dialect phrasing and messages that switch language mid-sentence, which is how customers actually write.
Out-of-scope questions route to a human with the transcript, the sources consulted and the assistant's confidence — not a dead end.
The assistant cannot state a price, date or policy it has not retrieved. Refusing is a valid answer; inventing one is not.
A fixed set of real historical questions, including adversarial ones, run before every prompt or model change.
Every conversation is stored and reviewable, so quality is something the business inspects rather than hopes for.
05Technology architecture
How the pieces fit together.
Frontend
Backend
AI
Database
Infrastructure
Integrations
06Results
Outcomes are described qualitatively. No measured figures are claimed for illustrative work — real metrics appear here only when a client has approved publishing them.
07Gallery
Product screenshots are added once a client has approved publication. Nothing here is a mock-up of an interface that does not exist.
One inventory record, automatic lead routing and a commission ledger drawn from the same data as the sales pipeline.
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A multi-tenant scheduling and job-management product with an offline-first technician app, so work is captured where it happens.
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Online booking against real practitioner and room availability, with automated multilingual reminders and no-show reporting by branch.
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