Powered by LLM-based intent recognition that maps conversational queries to structured inventory. It is built around natural human interaction - the kind you’d have when asking a friend or a travel expert for advice.
“Where can I see the northern lights?”
Imagine a traveler wanting to, but unsure where to begin. With EsteAI on your app/website, your site answers with not just ideal destinations. It delivers a full journey: weather, local experiences, stay options, all curated instantly.
Now you’re not selling a product. You’re selling an experience.
EsteAI engages users through human-like dialogue, fueling curiosity, conversation, and serendipitous discovery.
When the journey feels personal, users don’t just browse - they book.
Whether you’re running a white-label OTA, a high-volume group travel desk, or a dynamic packaging engine, Estea integrates seamlessly via RESTful APIs to your content and suppliers.
EsteAI delivers personalised highly relevant results by leveraging a logged-in users booking history, search patterns, and preferences sourced through a privacy-first (anonymized) approach.
But the choice to book? Always with the user.
Estea architecture ensures privacy and data security. The AI operates without direct access to customer data, and multiple security layers ensure that all sensitive information remains protected at all times.
EsteAI is designed as an AI-first booking engine, but it does not force AI on every user or every journey.
The platform fully supports traditional booking flows, including filter-based search, structured results, and standard booking paths. Travel companies can choose where and how AI is introduced, from assisted discovery to fully conversational search, or operate with a classic booking experience where required.
This ensures flexibility across customer segments, geographies, and use cases, while keeping a single, unified booking engine underneath.
Both AI-driven and traditional booking flows operate on the same inventory, pricing logic, and booking infrastructure.
What is an AI booking engine?
An AI booking engine understands natural-language travel intent and converts it into relevant, bookable results. Instead of relying only on rigid filters, it interprets what travelers are asking for and dynamically recommends destinations, itineraries, and inventory across flights, hotels, and packages.
How is an AI booking engine different from a traditional booking engine?
Traditional booking engines rely on static filters and predefined search rules. An AI booking engine uses conversational input, context, and intent to refine results in real time, helping users discover suitable options faster and reducing friction between search and booking.
EsteAI also supports classic filter-based search and standard booking flows on the same underlying booking infrastructure.
Does EsteAI replace my existing booking engine or inventory systems?
No. EsteAI works on top of your existing booking engine, APIs, and supplier integrations. It enhances discovery and conversion while keeping your current inventory, pricing logic, and booking workflows intact.
Who is the AI booking engine built for?
EsteAI is built for OTAs, TMCs, tour operators, and travel platforms that handle complex inventory or itineraries and want to improve engagement and conversion without rebuilding their core systems.
Can AI be introduced gradually, or does it have to replace the full booking flow?
AI can be introduced incrementally. Travel companies can use AI for assisted discovery while retaining traditional booking flows, or deploy conversational search more broadly as adoption grows. Both modes operate on the same booking engine foundation.
How does the AI handle user data and privacy?
EsteAI is designed with a privacy-first architecture. Personalization is driven through anonymized signals and controlled access layers, ensuring sensitive customer data remains protected and compliant with data security standards.
Does using AI slow down search or booking performance?
No. The AI booking engine is backed by a high-performance caching and distribution layer, enabling sub-second responses even during high-concurrency search traffic.












