Solutions / Bilingual support
Your chatbot works in English and falls apart in Arabic.
Soluvide builds bilingual AI support agents for UAE businesses that genuinely handle Arabic and English — including Gulf dialect, Arabizi, and messages that switch script mid-sentence. Answers are grounded in your own knowledge base, kept on-topic by guardrails, and escalated to a human on low confidence. Every agent passes a dedicated Arabic and mixed-script validation layer before it ships.
01 / The problem
What breaks the moment a customer types in Arabic.
A customer messages your support line in Arabic. Not the textbook Modern Standard Arabic from a course — real Gulf dialect, half of it typed in Latin letters and numbers because that is how people actually text. One sentence is Arabic, the next is English, and a product name sits in the middle in a third register. Your chatbot, demoed and signed off entirely in clean English, has never really seen anything like it.
So it does the worst possible thing: it answers confidently and wrongly. It misreads the intent, retrieves the wrong article, or replies in stiff, literal Arabic that any native speaker can tell was written by a machine. In English the same bot looks polished. The failure is invisible to the people who approved it, because they tested in the one language it happens to be good at.
Underneath, several things break at once. Gulf Arabic differs from the Arabic most models see most of. Code-switching — Arabizi and mixed Arabic/English inside a single message — confuses systems built to assume one language per turn. Right-to-left text renders incorrectly when Arabic, English, numbers, and punctuation share a line. And dialect variation across the Gulf means the same question arrives in dozens of shapes.
The result is a support experience that quietly collapses for a large share of your customers while your English metrics stay green. People stop trusting the bot, escalate everything to already-stretched human agents, or simply leave. It is not a dramatic outage — it is a slow erosion of service that nobody's dashboard is measuring.
02 / Why the obvious fixes fail
You've probably already tried these.
The Google-Translate layer
Bolting a translation API onto an English bot translates words, not meaning. Gulf expressions come out literal and culturally wrong, politeness registers get flattened, and idioms turn into nonsense. The customer reads a reply that is technically Arabic and obviously not written for them.
English-first LLM tooling
Many models and pipelines are tuned for English first. They mis-tokenise Arabic, mishandle right-to-left rendering, and truncate or garble mixed-script input before the reasoning even starts. The agent isn't answering your customer's question — it's answering a mangled copy of it.
Template and keyword bots
Rule-based bots match keywords and canned intents. Real dialect has too much variety for that: the same request arrives spelled ten ways, half in Latin letters, so the bot falls through to "I didn't understand" and dumps the customer into a queue. It scales your fallback rate, not your resolution rate.
03 / How the system works
A grounded bilingual agent, tested in Arabic.
Knowledge base grounding
We ingest your own content — help-centre articles, product docs, policies, past tickets — into a retrieval layer. Every answer the agent gives is pulled from and matched against your material, so it speaks with your facts and your policies rather than whatever a general model happens to have absorbed.
Bilingual understanding
The agent is built on an LLM that handles Arabic and English together, including Gulf dialect, Arabizi, and messages that switch script mid-sentence. It reads what the customer actually typed — mixed, informal, right-to-left — instead of forcing it through a one-language-per-turn assumption.
Grounded answering with guardrails
Retrieval-augmented generation keeps replies anchored to your knowledge base. Guardrails keep the agent on-topic and inside your policies — it answers what it is meant to, declines what it shouldn't, and doesn't wander into promises you never made or facts you never gave it.
Arabic & mixed-script validation
This is the real engineering. Before anything ships, the agent runs through a validation layer built specifically for Arabic and mixed-script failure modes — dialect variation, Arabizi, code-switching, right-to-left rendering, and tokenisation edge cases. We test the language most tools only test in English, and treat Arabic reliability as a measurable capability, not a hope.
Escalation & human handoff
When confidence is low, the question is ambiguous, or the customer asks for a person, the agent hands off to a human with the full conversation in context — no restarting, no lost thread. Human handoff is always available. The agent absorbs volume; your team keeps the hard and the sensitive.
Multi-channel deployment
The same agent deploys across the channels your customers already use — WhatsApp, your web chat widget, Instagram — and syncs into your CRM. One grounded, validated, bilingual brain, consistent everywhere, instead of a different half-built bot on every platform.
04 / What's in scope — and what isn't
Clear lines, agreed up front.
In scope
- A bilingual agent that handles Arabic, English, and mixed script
- Retrieval-augmented answering grounded in your own knowledge base
- Guardrails that keep answers on-topic and inside your policies
- A validation layer for Arabic and mixed-script failure modes
- Escalation to a human on low confidence — always available
- Deployment across WhatsApp, web chat, and Instagram with CRM sync
Out of scope
- Replacing your human agents entirely
- Making promises or commitments outside your policies
- Answering from the open internet instead of your content
- Removing the human handoff path
05 / Integration surface
Named channels, not “works everywhere.”
We confirm exactly which channels and systems the agent connects to during scoping. The deployment commonly touches:
Timeline & scope
Live in weeks, quoted before we start.
Most bilingual support agents go live in about three to six weeks. What moves it inside that range is the size of your knowledge base, how many channels you deploy to, and the depth of Arabic validation your use case needs. We map the work in a short discovery call and send a fixed-fee proposal — scope, timeline, and deliverables — before any build begins. No hourly billing, no surprises.
06 / Questions buyers ask
Straight answers.
Does it really handle Gulf dialect and Arabizi?
Yes — that is the point of the build. The agent is designed for real Gulf Arabic and for Arabizi, where Arabic is typed in Latin letters and numbers. It is also built for code-switching, where a customer moves between Arabic and English inside a single message. We validate exactly these cases before launch instead of assuming they work because an English demo looked clean.
How do you test that the Arabic is actually good?
Before anything ships, the agent runs through a validation layer built specifically for Arabic and mixed-script failure modes — dialect variation, Arabizi, right-to-left rendering, and code-switching. We treat Arabic reliability as something to measure and check, not something to hope for because the English version passed. It is the part of the work most tools skip, and it is where support quality is actually won or lost.
Does it make things up?
It is constrained to answer from your own knowledge base using retrieval-augmented generation, and guardrails keep it on-topic and inside your policies. When it does not have a grounded answer, it says so and escalates rather than inventing one. It is built to speak from your content, not the open internet.
When does it hand off to a human?
On low confidence, on ambiguous or sensitive requests, or whenever the customer asks for a person. The handoff carries the full conversation so nobody has to start over. Human handoff is always available — the agent is there to absorb volume, not to replace your team.
Which channels can it run on?
It deploys across WhatsApp via the WhatsApp Cloud API, a web chat widget on your site, and Instagram, and it can sync conversations into your CRM. It is one bilingual agent behind every channel, not a separate half-built bot per platform.
How long does it take to go live?
Most builds go live in about three to six weeks, depending on the size of your knowledge base, the number of channels, and how much Arabic validation your case needs. We scope the work first and send a fixed-fee proposal before starting.
Who owns the system once it's built?
You do. It runs on your infrastructure and accounts, it is grounded in your content, it is documented, and it is handed to your team — no black box and no dependency on us to keep it running.
Start
Give your Arabic-speaking customers a real answer.
Tell us how support reaches you today and what your customers actually type. We'll map the bilingual agent and send a fixed-fee proposal within 24 hours.