Inside ixigo’s Agentic AI Travel Push

The travel app has barely changed in over a decade.

You search. You scroll endlessly through filters. You open five tabs to compare timings, baggage rules, cancellation policies and hotel reviews. Then comes the real anxiety: will the flight run on time? Do I need a transit visa? Is this hotel actually close to the city centre?

Travel apps solved booking. They never fully solved decision fatigue.

But listed OTA platform ixigo now believes AI can rewrite the travel experience. And at the centre of it all is TARA, the company’s AI-native travel assistant that it claims brings agentic experiences for customers.  

Instead of functioning like a chatbot layered on top of an existing app, the company has rebuilt the experience around what it calls an agentic AI layer capable of navigating the app, understanding intent, comparing options, surfacing contextual information. It can even complete actions on behalf of users.

For instance, instead of manually opening multiple menus to add filters while searching for flights or hotels, users can simply ask TARA for exactly what they want as they would talk to any agent. For instance, one could request a shorter layover, higher baggage allowance, public transport access for hotel bookings as well as other amenities. 

The assistant handles it in one go.

For ixigo cofounder, CEO and chairman Aloke Bajpai, TARA solves a fundamental issue with travel planning. It is often less about transactions and more about reducing uncertainty. And ixigo’s bet is that AI can compress decision-making, simplify discovery, and make travel platforms accessible to users who may otherwise struggle with cluttered interfaces and information overload.

“We don’t consider ourselves an OTA anymore. We consider ourselves being in the peace of mind business,” Bajpai told Inc42.

But behind that vision sits a far bigger reinvention underway inside the company itself.

From Travel Agents To AI Agents

For ixigo, the biggest problem with most AI integrations in consumer apps today is that they feel bolted on.

Bajpai said most companies are effectively placing a chatbot sticker on top of an existing interface, where the assistant operates separately from the actual product flow. ixigo wanted to redesign the interaction layer itself.

That meant building what the company calls an AI-native architecture. Under the hood, the system combines four distinct layers:

• LLMs and voice intelligence models
• User intent and behavioural data
• Supplier-side contextual and real-time travel information
• ixigo’s own proprietary travel intelligence stack

The company claims this lets TARA function less like a chatbot and more like a travel operator embedded inside the app.

For instance, if a user is booking an international itinerary with a transit stop, the assistant can proactively explain whether a transit visa is required, how terminal transfers work, and what passengers should know before boarding.

Similarly, users no longer need to manually open multiple menus to apply filters while planning trips.

TARA handles conversational, multi-context instructions instead of forcing users through multiple search layers. The broader thesis here is opening up accessibility for users.

Travel apps historically assumed users were comfortable navigating cluttered interfaces, comparing fine print and understanding travel jargon. ixigo believes AI can flatten that learning curve significantly, especially for users from smaller cities or first-time digital travellers.

But the bigger shift is that the assistant is not just answering questions. It is increasingly being designed to perform actions.

“Our long-term roadmap includes AI agents that can autonomously check users in for flights, send boarding passes, call hotels to reconfirm bookings or even speak to airlines on behalf of customers,” Bajpai said, indicating where TARA is headed. 

Inside ixigo’s AI Stack 

As a travel company — at least by the nature of its core business, regardless of what Bajpai may claim — ixigo is not betting on a single foundational AI model or LLM to build TARA. 

Bajpai said the company currently uses multiple models and infrastructure layers depending on cost, latency, accuracy and use case requirements. “The real IP we are building here is the layer that marries the four pillars: user context, supplier intelligence, proprietary travel data and LLM capabilities.”

This orchestration layer has become increasingly important because AI costs can spiral quickly at scale. According to Bajpai, ixigo selectively decides where to use smaller internal models versus expensive large language models so token costs remain manageable. But internally, the company appears willing to absorb those infrastructure costs for now because of what it believes is the bigger upside: speed.

“The engineering bandwidth is available on a tap now,” Bajpai said, and an AI-native mindset is beginning to reshape the organisation and its operational culture itself.

The company has already invested in and brought in AI-native talent like Europe-based startup SqaaS which ixigo sees as part of its broader strategy to combine internal execution with frontier AI expertise. 

Despite operating with a team of roughly 600 employees, ixigo is already running at close to a $2 Bn annual ticket sales run rate, according to Bajpai.

The company sees AI as a force multiplier that allows leaner teams to ship faster, automate workflows and scale operations without proportionately expanding headcount.

“The best people out there are either willing to come and build for you, or they are doing their own startup,” Bajpai said, adding that the company remains open to both acquisitions and strategic investments. 

Internally, that talent is now being integrated into ixigo’s larger effort to reinvent not just its product stack, but also how the organisation ships software and automates workflows using AI.

The company is already seeing the impact. During the December 2025 airline disruption crisis, when flight cancellations surged after operational disruptions at a leading airline, ixigo leaned heavily on AI systems to handle customer support at scale.

According to the company, AI handled more than 90% of customer calls during the disruption period, with over 150,000 calls processed end-to-end through AI systems.

The OTA also used AI-driven outbound calls to proactively inform travellers about cancellations, refunds and alternate travel options, while TARA assisted users with refund workflows and rebooking support.

For Bajpai, the value of AI in such situations goes beyond cost savings. Instead, he sees it as a mechanism to preserve customer trust during moments where travel companies are usually most vulnerable to user frustration.

That philosophy is increasingly shaping how ixigo defines itself.

“Selling tickets is just going to be one part of our existence,” Bajpai said. “What you end up becoming is the most reliable travel companion for travellers.”

Betting Big On AI As Growth And Retention Play

ixigo’s AI push also comes at a time when the company is seeing strong business momentum across categories. Revenue from operations rose 31% YoY to ₹317.56 Cr, while adjusted EBITDA climbed 27% YoY to ₹30.78 Cr.

Air ticketing revenue grew 49% YoY during the quarter to ₹102.39 Cr, while bus revenue rose 47% YoY to ₹75.57 Cr. The company is now directing a sizable portion of fresh capital toward AI-led expansion.

Following its preferential raise of ₹1,295.56 Cr, ixigo earmarked 25% of the capital for organic growth opportunities and another 25% for inorganic growth opportunities.

Management indicated that a meaningful part of this allocation will go toward AI investments, acquisitions and strategic partnerships, like the investment in Europe-based AI startup SqaaS. It will continue evaluating additional AI-native teams and products that align with ixigo’s long-term roadmap. 

Bajpai said ixigo does not calculate AI ROI differently from any other product innovation. Instead of focusing on monetisation immediately, the company first looks at whether AI meaningfully improves customer experience and creates delightful moments for users through better recommendations, faster support and lower travel anxiety.

According to him, stronger retention, higher engagement and long-term customer trust eventually become the real business outcomes, even if direct monetisation takes years to materialise. “The moment users perceive you as the most intelligent app in your space, that shift is kind of permanent,” he said.

The online travel booking experience is largely focused on incentives, discounts, packaged deals, and value. With ixigo’s AI shift, the narrative could turn towards an agentic travel booking experience without the clicks and dozens of filters usually deployed by users. Will this turn help turn travel from a booking and reservation model into the “peace of mind” experience that ixigo envisions? 

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