A night out can start with a simple question: “What should we do tonight?” That is where traditional search can struggle. It works best when users already know the event, date, or location they want. Booking platforms are now using artificial intelligence to tackle the opposite problem: first understanding vague intent, then turning it into options that can actually be booked. Nadeem Bakhsh, chief executive and co-founder of webook.com, says the platform’s AI booking agent was not built because existing search tools were failing. It was designed to add another layer of discovery for users who do not yet know exactly what they want. Speaking to Asharq Al-Awsat, Bakhsh said search and filters remain effective when users have a clear target. Open-ended questions, however, require the system to understand context before it can surface the right option. From keywords to intent In its first version, the agent uses natural language processing in Arabic and English and can handle informal requests that include location, preferences, group type or booking criteria. Users do not need to know an event’s name or phrase their request like a search query, Bakhsh said. They can simply ask for a family activity, a nearby experience or something available in the evening. The system then interprets the request, identifies the relevant details and matches them with options in the platform’s live catalog. If key information is missing, the agent is designed to ask for clarification rather than produce a generic list that may not fit the user’s needs. That makes accuracy central to the experience. The more discovery shifts from explicit search to conversation, the greater the risk that a question will be misunderstood or misinterpreted. When the agent gets it wrong Bakhsh acknowledges that mistakes are part of using AI systems. The agent, he said, “should not pretend to know.” If a request is unclear or incomplete, it should ask for more information rather than force an unreliable recommendation. The official booking page remains the final authority on availability, prices, fees and event terms. If information changes or tickets sell out before a purchase is completed, the details shown in the official booking flow take precedence over anything said earlier in the conversation. When the agent cannot verify information, Bakhsh said, it should direct the user to official event details or human support. A correction from the user may also help improve the next response, but Bakhsh does not present that as a guarantee that the same mistake will not happen again. Recommendation or advertising? Trust becomes a commercial issue when the agent is not only finding events, but ranking and recommending them. Bakhsh said the system is meant to match user intent with options that are genuinely available to book, not present paid advertising as personal advice. Recommendations are based on criteria supplied by the user, including location, timing, group type and activity preference, as well as live availability. Any paid or sponsored placement, he said, should be clearly labeled so users can distinguish an organic recommendation from commercial content. “Trust depends on making that distinction clear,” Bakhsh said. One journey, several channels The experience becomes more complicated when the conversation starts outside the booking platform itself, on services such as X, Instagram or WhatsApp. Bakhsh said the agent uses information users choose to provide, such as location, timing, group type, interests and booking criteria, to make suggestions more relevant. Public interactions remain limited to discovery. Once greater privacy is required, the conversation moves to a private channel and then into webook.com’s secure booking environment. Card details and other sensitive personal information should not be requested through public posts, comments or direct messages on social media, he said. Personal data remains subject to the platform’s privacy policy and to legal and regulatory retention requirements. Bakhsh also said data is not treated as freely transferable from one channel to another. Any personalization depends on the permissions granted by the user and the purpose for which the data was collected. What webook.com builds — and what it does not The agent is not built entirely with in-house technology. Bakhsh said webook.com develops and operates the core product layer and orchestration system. That includes understanding booking intent, linking it to the catalog, applying product logic, generating recommendations and directing users into the secure booking flow. External infrastructure is used when needed for language-model processing, cloud services and access to channels such as X, Instagram and WhatsApp. Those providers supply infrastructure or distribution channels, Bakhsh said, but they do not own the event inventory, booking logic or customer journey. The company does not disclose vendor architecture or security-sensitive implementation details. Bakhsh also stressed that the agent remains in beta and can make mistakes. Users should verify event details and final booking information on the official page before completing a transaction. Discovery ends where the transaction begins One of the main safeguards in the system is the separation between conversation and payment. The agent may respond to a general request in a public space, but when privacy becomes necessary, it moves the interaction into a private channel and then directs the user to an official, identity-linked booking flow. It does not request card details or sensitive information through social media posts, comments, or direct messages. Bakhsh said this structure helps limit the impact of prompt manipulation, impersonation, fraudulent accounts, and fake booking links. The conversational layer can help users find an event, but it cannot bypass the inventory, account, pricing, or payment controls on the official platform. The agent does not set the price Once a user moves from discovery to purchase, the agent’s role stops at a clear boundary. Options come from the live catalog, but the official booking page remains the authoritative transaction interface. Before confirming, users see current availability, the final price, booking fees and event-specific terms, including cancellation and refund policies. The agent cannot change those terms or guarantee that a ticket will still be available while a user waits. Age restrictions and accessibility requirements are shown only when they appear in the official event details. If the information is unclear, the system is not supposed to guess. AI, in other words, changes how users reach an option. It does not change the contractual terms or controls governing the purchase. Bakhsh also links the agent to a broader framework called TruFan, while drawing a distinction between the two. The AI agent operates at the start of the journey, turning natural-language requests into bookable options. TruFan addresses a different stage: integrity and access to high-demand events, by helping identify genuine, verified fans and giving them priority.
