Real Work, Real Results

Agentic AI
Multi-Channel Automation

CodeLabs BOT

CodeLabs' own in-house multi-channel AI agent, live on codelabs.ae today — handling real conversations across WhatsApp, web chat and API, qualifying leads in multiple languages before routing them to sales.

What Agentic AI Looks Like In Practice

AI Chatbot Or AI Agent — Which Do You Actually Need?

Most people arrive at this looking for a chatbot. It is worth being clear about what the difference actually is, because it decides what you should buy.

What a chatbot does

A chatbot follows a script. You map out the questions customers ask, write the answers, and connect them with buttons or keyword matching. Ask it something the script does not cover and it either guesses badly or hands you to a human. For a narrow job — opening hours, order status, a simple FAQ — that is often genuinely all you need, and it is cheaper to build.

What an AI agent does differently

An agent is not working from a script. It understands what was asked in open language, retrieves the answer from your actual knowledge base, and can call your systems to complete the task — check the stock level, book the slot, raise the ticket, send the payment link. The test is simple: a chatbot can tell a customer your returns policy; an agent can start the return.

Which one you actually need

If your questions are few, fixed and rarely change, a chatbot is the honest answer and we will tell you so. An agent earns its cost when the questions are open-ended, when the answer lives in a system rather than a document, or when your team is manually doing something after every conversation. That last one is usually the tell.

WhatsApp, web chat, or both

In the UAE and Pakistan, most of this traffic is WhatsApp, not web chat — which is why we build on the WhatsApp Business API rather than treating it as an afterthought. One agent definition deploys to WhatsApp, your website and your own systems over API, so you are not maintaining three separate bots that drift apart.

What it costs to run, not just to build

Every reply, tool call and token is metered against a live dashboard. The build is a one-off; the running cost scales with adoption, and you should be able to see it before it surprises you. We would rather show you that number early than have the conversation after the first invoice.

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Agentic AI FAQs

Common questions about building and deploying AI agents.

  • Do you actually run agentic AI yourselves, or just build it for clients?

  • Which channels can an agent be deployed to?

    WhatsApp, web chat and API from a single agent definition — you're not maintaining separate bots for each channel.

  • How is AI spend controlled?

    Every reply, tool call and token is metered against a live dashboard, so you can see exactly what usage is costing as adoption scales — not a surprise bill at the end of the month.

  • Can the agent connect to our existing tools and data?

    Yes. Agents are built to call your real APIs and reference your actual knowledge base, so they can complete tasks and answer questions grounded in your business, not generic training data.

  • What happens when the agent does not know the answer?

    It says so and hands over, rather than inventing something. You decide where that hand-off goes — a human on WhatsApp, a ticket in your helpdesk, or a callback request — and the conversation history goes with it, so nobody has to start again.

  • Who owns the conversation data, and where is it stored?

    You own it. Conversations, customer records and the knowledge base you supply remain yours, and we will tell you exactly which region they are stored in and which model providers see what. If you need them held in a specific jurisdiction, say so at the start — it shapes the architecture rather than being bolted on later.

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