AI Chatbots for Business and Customer Service

A useful business chatbot is not a general model with your logo on it. It answers from your own content, knows when it does not know, can look up an order or a booking when that is what the customer needs, and hands the conversation to a person cleanly when it should.

What I build

• Customer service assistants that answer from your help content, policies and product data, with sources.
• Workflow-connected assistants that can check an order, open a ticket or book an appointment through your systems.
• Internal assistants for staff, answering from documentation and past cases.

Basic chatbot, RAG assistant or agent?

• A scripted chatbot follows decision trees. Cheap, predictable, limited.
• A RAG assistant retrieves from your documents before answering, so answers stay grounded in what you have published.
• An agent can also take actions across tools — see AI agents.

Most customer-service projects are best served by a RAG assistant with a few carefully chosen actions. New to the topic? Start with the AI chatbot guide.

How I work

1. Collect and clean the content the assistant should answer from.
2. Design the conversation limits, escalation rules and the actions it may take.
3. Build retrieval, integrations and the chat surface — web, app or WhatsApp.
4. Test against real questions before launch, and review conversations after it.

FAQ

Will the chatbot give wrong answers?

Any model can. The risk is reduced by answering only from retrieved sources, declining when nothing relevant is found, testing against real questions, and escalating to a person instead of guessing.

Can it speak Arabic and English?

Yes. Both languages are designed and tested separately, including how the assistant handles mixed-language messages.

Can it connect to our CRM or booking system?

Yes, through their APIs, limited to the specific actions you approve.