At LEAP 2026, the Saudi company is building its customer experience strategy around AI agents that can take action while keeping people involved when human judgment is needed. 

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A customer asking a company for help is rarely looking for a conversation. They want the problem fixed, the payment sorted out or the right product found. Much of the AI used in customer service today is still built around producing a better answer. The harder part comes after that answer, when someone has to check an account, make a change in another system or pass information to another team. That gap sits at the center of Unifonic's showing at LEAP 2026 in Riyadh. The Saudi customer engagement company is demonstrating AI agents that can understand a customer's intent, work across connected business processes and take action during an interaction rather than simply respond to it. Human handover remains part of the approach, reflecting the reality that enterprises still need people involved when a request falls outside an agent's authority or requires a decision that cannot be safely automated. 

Founded in Saudi Arabia in 2006, Unifonic built its business around communications and enterprise messaging before moving into customer engagement software. Its platform now brings voice, SMS, WhatsApp, web and in-app conversations together with customer data and AI capabilities, giving the company a communications layer that many newer AI products have to connect to after the fact. 

“Customer experience is entering a new era where AI is moving beyond assistance to action. The opportunity for enterprises is not simply to automate more interactions, but to connect intelligence with execution across the customer journey. LEAP 2026 serves as a critical platform to demonstrate how organisations can embrace this shift while retaining human control,” said Ahmed Hamdan, Chief Executive Officer of Unifonic. 

The recent acquisition of Segmentify adds another piece to that strategy. Its technology covers personalization, personalized search, recommendations and behavioral data, giving the customer engagement platform more information to work with when determining what a person may want or need. Unifonic said the deal would support its development of agentic marketing, where AI can help move a campaign from planning through execution. Personalization only becomes useful when it can influence what happens next. A customer who has browsed a particular product, contacted support about it and then returned to the site presents a different set of signals from someone visiting for the first time. An AI system with access to those signals can make a more relevant recommendation or tailor an interaction to the customer's behavior instead of relying only on the latest message. 

Customer service brings the same principle into a more sensitive area, particularly once an AI agent is allowed to act. Access to customer records, account changes, payments or internal workflows cannot simply be handed to a system without boundaries. Someone has to determine what the agent is permitted to do and when a person should take over. Human handoff is therefore more than a fallback feature in this model. The platform is designed to carry customer context with an interaction when it moves from AI to a human agent, so the customer does not have to start the explanation again. Unifonic's experience building communications technology for businesses across MENA also gives this approach a regional dimension, particularly in markets where language, customer behavior and regulatory requirements shape how companies engage with customers. 

“Enterprises are increasingly moving towards unified platforms capable of orchestrating customer experiences across the entire lifecycle. Through our agentic solutions, we are demonstrating how organisations can connect intelligence with execution, turning fragmented interactions into coordinated journeys that drive measurable outcomes,” said Mohammed Sleeq, Chief Operating Officer of Unifonic. 

Enterprise buyers will eventually judge these systems on what happens outside a product demonstration. An agent needs to work within the systems it has been given access to and recognize when a request needs human attention. Passing that case to a person also needs to happen without losing the context gathered during the interaction. Those practical details will determine whether agents become genuinely useful in customer operations. 

A customer should not have to know which AI system handled a request or which internal process completed it. What matters is whether the issue is resolved without the customer having to repeat themselves or chase the company for an answer. If AI agents can take that responsibility while knowing when a person needs to step in, their value in customer experience becomes much easier to measure. The conversation is only the beginning. What happens after it is where the technology has to prove itself. 

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