The 30-Minute Setup: How to Add AI Customer Support to Any Arabic Website

If you run a business in the MENA region, you have probably tried at least one chatbot tool and felt the same frustration:

• The interface feels like it was designed for another market.
• Arabic looks broken or misaligned.
• The bot answers in English, even when the customer writes in Arabic.

Most chatbot platforms were built for English‑only teams and then “extended” to Arabic as an afterthought. That shows up in:

• Poor Arabic language models.
• No RTL (right‑to‑left) support.
• Confusing behavior when you mix Arabic, English, and French.

In this guide, we will walk through how to set up AI customer support on an Arabic website in about 30 minutes, using Sanad as the example. The steps are general enough that you will learn what matters even if you use another tool—but we will highlight where an Arabic‑first platform makes a real difference.

Why most chatbots fail for Arabic businesses

Before we jump into the how‑to, it helps to understand why many tools do not perform well in Arabic.

1. No real RTL support

A lot of interfaces:

• Flip the text direction incorrectly.
• Mix LTR and RTL in a way that feels broken.
• Misalign message bubbles and UI elements.

For customers, this feels unprofessional. For your brand, it erodes trust.

2. Weak Arabic language understanding

Some tools:

• Rely on English‑trained models and simply translate in and out of Arabic.
• Struggle with dialects and mixed Arabic–English messages (very common in MENA).
• Misinterpret simple questions and answer with generic replies.

The result is more confusion, not less.

3. English‑only training content

Even when tools support Arabic on paper, the recommended setup often assumes:

• English FAQs.
• English help center.
• English system messages.

If your real customers write and read primarily in Arabic, the model is learning from the wrong examples.

Sanad takes the opposite approach: Arabic, English, and French are first‑class citizens. You can upload content in those languages, customize tone in each, and run the same assistant across them.

Now let us see how to go from zero to live assistant.

Step 1: Gather your Arabic FAQs and documentation

The most common mistake teams make is treating “AI” as magic that will figure everything out on its own. In reality, AI performs best when it has clear, high‑quality training data.

For an Arabic‑first assistant, that means:

• Exporting or writing your core FAQs in Arabic:
  • Shipping and delivery.
  • Returns and exchanges.
  • Payment methods (including local options).
  • Opening hours and contact methods.
• Collecting key product or service descriptions in Arabic.
• Including any important policies or terms your team uses in support.

You do not need to rewrite your entire help center. Start with the questions you see most often.

Good training data:

• Uses the same phrasing your customers use.
• Includes both formal Arabic and the style your brand prefers.
• Is kept up to date as policies change.

Sanad lets you upload documents and files directly into a knowledge base that the assistant uses as its main reference.

Step 2: Upload your content to the knowledge base

Once you have your core Arabic content, the next step is to make it available to the AI.

In a Sanad‑style dashboard, that looks like:

1. Go to the Knowledge Base or Files section.
2. Upload your FAQs, policy documents, and product descriptions (in Arabic, plus any English/French versions you have).
3. Organize them into folders or categories if needed (e.g. “Shipping”, “Pricing”, “Account”).

Behind the scenes, the assistant:

• Indexes this content.
• Learns which paragraphs answer which kinds of questions.
• Uses your own wording when responding.

This matters a lot for Arabic, because you want answers to:

• Use the right script and diacritics (when relevant).
• Match your brand voice (formal vs conversational).
• Stay aligned with your official policies.

If you add or update documents later, the assistant learns from those versions automatically.

Step 3: Customize tone and greetings in Arabic

The next step is to decide how the assistant should introduce itself and speak to customers.

Things to think about:

• Do you want a formal tone or something more casual?
• Do you want to call it a “مساعد ذكي” (smart assistant), “روبوت دردشة”, or give it a human‑like name?
• How should it handle switching between Arabic, English, and French?

In Sanad, you can:

• Set greetings and default prompts in each language.
• Define instructions like:
  • “Prefer Arabic when the user writes in Arabic.”
  • “Answer briefly unless the user asks for more detail.”
• Write example conversations that show the style you want.

For example, a simple Arabic greeting might be:

“أهلاً 👋 أنا مساعد الدعم الخاص بسناد. اسألني عن الشحن، الدفع، أو أي شيء قبل الشراء.”

You can also define suggested questions that appear when the widget opens, such as:

• “ما هي خيارات الدفع المتاحة؟”
• “هل تشحنون إلى دولتي؟”
• “كيف أسترجع طلبي؟”

These give customers a starting point and help the AI stay in the topics you are ready to support.

Step 4: Test conversations in Arabic, English, and French

Before you install the widget on your production site, you should test how it behaves in real conversations.

Create a small internal checklist:

• Ask common Arabic questions you see in support tickets.
• Mix Arabic and English in the same sentence, like many customers do.
• Try French if you serve North African markets or bilingual audiences.

For each answer, check:

• Is the language natural and aligned with your brand?
• Is the answer accurate based on your policies and docs?
• Does it admit uncertainty instead of inventing an answer when content is missing?

When you find gaps, fix the underlying content:

• Add a missing FAQ.
• Clarify a policy document.
• Adjust the instructions for tone or level of detail.

Because Sanad works from your knowledge base, each improvement makes future answers better without manual re‑training.

Step 5: Embed the assistant on your website

Once you are happy with your assistant in the dashboard, it is time to go live.

There are several ways to embed the widget on an Arabic website:

Option 1: Floating chat bubble (most common)

• Add the script tag provided by your Sanad workspace before the closing </body> tag.
• Choose the position (e.g. bottom‑right or bottom‑left) that works best with your layout and RTL design.
• Customize colors so the bubble matches your brand.

This option:

• Works on virtually any site (custom code, WordPress, Shopify, etc.).
• Keeps the rest of your layout unchanged.
• Gives visitors a familiar chat experience.

Option 2: Embedded chat area (iframe)

If you want a dedicated support or “Help” page:

• Use the iframe or component snippet provided.
• Embed it inside your page content, respecting RTL layout.
• Use this for:
  • Help center pages.
  • Account dashboards.
  • Customer portals.

This is useful when:

• You want a bigger chat area than the bubble popup.
• You want to link directly to “support.yourdomain.com” or a similar page.

Option 3: Mobile webview

If you have a mobile app or a PWA:

• You can load the widget inside an in‑app browser or webview.
• Use the same configuration and content as your main site.

This keeps the experience consistent across:

• Desktop site.
• Mobile site.
• Mobile app.

Regardless of which option you choose, the logic stays the same:

• One assistant configuration in the dashboard.
• Multiple presentation options (bubble, iframe, webview).

Common mistakes to avoid

Even with a strong Arabic‑first platform, it is easy to make mistakes that reduce the impact of your assistant.

Here are some to watch for:

1. Generic English responses

If you only upload English content or leave system messages in English:

• The assistant may default to English, even for Arabic‑speaking visitors.
• Customers may assume the bot “does not support Arabic” and abandon it.

Fix: make sure your core FAQs and greetings exist in Arabic, and instruct the AI to prefer Arabic when the user does.

2. No escalation path

If you let the AI handle everything with no way to reach a human:

• Frustrated customers will feel stuck.
• Sensitive issues may be mishandled.

Fix: define clear handoff rules, such as:

• Certain keywords or topics always go to human agents.
• A “talk to a human” button that appears after a few AI messages.
• Office‑hour rules: AI always available, humans join when online.

3. Untrained or outdated content

If your policies change but your knowledge base does not:

• AI will keep answering with old information.
• Support agents will have to correct it manually, creating friction.

Fix: treat your knowledge base as a living system. When a policy or pricing tier changes, update the document in Sanad at the same time you update your website.

4. No measurement

Without tracking, you cannot tell if your assistant is successful. You may underestimate it or overestimate it.

Fix: use analytics to monitor:

• How many conversations the assistant handles.
• How many are fully resolved by AI.
• How often humans need to step in.

We will cover measurement next.

How to measure success

Launching an AI assistant is the beginning, not the end. To know if it is working, define a few simple metrics:

1. Resolution rate

• What percentage of conversations are fully answered by the assistant?
• How does that split by topic (shipping, returns, product info, etc.)?

This tells you where your content is strong and where you still rely heavily on humans.

2. Customer satisfaction

• Ask for quick feedback after conversations:
  • “Was this answer helpful?” 👍 / 👎
• Track satisfaction separately for AI‑only conversations vs human‑assisted ones.

If customers are happier when humans join, look for patterns in the topics or phrasing that trigger those handoffs.

3. Time to first response

• Compare response times before and after launching the assistant.
• Especially outside working hours.

If your average time to first response drops from hours to seconds for basic questions, that is a clear win.

4. Deflection and cost savings

• How many tickets would have gone to your support team without the assistant?
• How many of those are now handled automatically?

Tie this back to:

• Agent headcount.
• Overtime.
• The ability to reassign people to higher‑value tasks.

Bringing it all together with Sanad

Sanad is designed from the ground up for businesses that operate in Arabic, English, and French, with customers across the MENA region.

In practice, that means you can:

• Upload knowledge in Arabic without workarounds.
• Run one assistant that understands and responds appropriately across languages.
• Use a shared inbox so human agents see every conversation and can step in instantly.
• Customize the widget so it looks natural on RTL websites, not like a foreign object.

The 30‑minute setup looks like this:

1. Create your Sanad workspace and connect your organization.
2. Upload your core FAQs and policies in Arabic (and other languages you support).
3. Configure tone, greetings, and handoff rules.
4. Test conversations internally.
5. Embed the widget on your site using the script or iframe snippet.
6. Monitor analytics and iterate on your content.

From there, you can expand:

• Connect WhatsApp, Instagram, or other channels.
• Add more training data as new questions appear.
• Use analytics to refine both your content and your website.

If you want to see how an Arabic‑first AI assistant would behave with your real FAQs and traffic, you do not need a long implementation project.

Get started for free and we will walk you through the setup, step by step, using your own use cases as examples.