• India’s Aviation Ambitions Could Meet AI-Powered Route Planning
  • Connecting the Data, Mapping the Opportunity: DOB AI’s Aviation Play
  • From Data to Departures: DOB AI Targets Faster Route Decisions

By Anna Jordy

Frankfurt, Germany. 25 October 2026. Aircraft orders make headlines. Deciding where those aircraft should fly is where the commercial challenge begins. As India adds airports and expands connectivity, turning fragmented data into viable routes is becoming increasingly critical. Speaking to Anna Jordy for Aviation & Defence Universe (ADU) at Routes World 2026 in Frankfurt, Britany O’Bannon, Founder of DOB AI, and Jeremy O’Bannon, Co-founder, outlined how their platform aims to bring booking figures, schedules and market intelligence into one analytical view. Drawing on DOB Systems’ four decades of aviation experience, their proposition is clear: faster answers, more tailored analysis and human expertise at the centre of every decision.

India’s aviation sector is expanding faster than many of its planners can model. New airports are opening, regional routes are being stitched into the network, and carriers are placing aircraft orders at a scale that demands equally ambitious route planning. Against that backdrop, this conversation offered a glimpse of how analytics could speed up decisions.

DOB Systems has been in the business for roughly four decades. Founded in the 1980s in Houston, Texas, by the current leadership’s father, it began by processing booking data for Continental Airlines and grew into a provider of software and business intelligence for network planning, revenue management, and sales and marketing teams. DOB AI, developed over the past four years, applies modern AI to that accumulated expertise.

The pitch will sound familiar to any Indian airport or airline analyst. Booking data, schedule data and market intelligence usually arrive from separate providers, each with its own tool and its own logins. Reports are pulled separately, merged by hand and passed to a data science team before anyone can act. DOB AI positions itself as data-agnostic: it layers external sources, such as GDS booking data, schedules and ticketing statistics, together with an operator’s internal figures, so a single question can be asked across everything at once.

Speed is the headline claim. The on-boarding process for a new customer, which previously required 30 to 60 days or more, is now said to take approximately 48 hours, with the time-frame subject to the client’s ability to provide their own data in a timely manner. Immediately after data is loaded, answers are available. Otherwise, they are available within a day or two. Otherwise, they are available within a day or two.

India’s regulatory environment makes the real-time angle especially relevant. Entry rules, declaration requirements and documentation can change at short notice, and distribution systems do not always catch up. This reporter experienced that first-hand on a Munich-to-India journey, when a government declaration requirement took effect only hours before departure. DOB AI’s executives said that any rule published online, including by a news outlet, is picked up automatically and factored into analysis. It was made clear that the system does not receive data feeds relating to immigration. Instead, it uses other sources of information, such as visa policy, turnaround times and baggage rules, to determine whether a route is viable. If the route is deemed not viable, the obstacles are explained.

Human oversight remains central. When asked if AI output could ever be incorrect, the executives conceded that it could, and stated that the company had invested years in encoding expert-style checks derived from its four-decade history. Nevertheless, it is still recommended that every result be reviewed and signed off on by airline and airport professionals. Indian regulators and boards should be reassured by this position, since they are understandably cautious about delegating major commercial decisions to software.

The scope is broad. The platform can cover passenger networks and connectivity. It can also cover cargo. And sales and marketing. This depends on the data a customer holds. The company’s leaders said that they do not see other companies that provide information, like Cirium, OAG or IATA, as their competitors. These companies give the information that DOB AI helps customers understand better. Its real competition, they argued, is the big-vendor model of fixed tools and slower, costlier support, against which the family-run firm sells customisation and one-to-one service.

For India’s airports and airlines, the practical question is not whether such tools work in a demonstration but whether they fit local realities: fragmented data, tight route-development windows and fast-moving policy. DOB AI has said it will email brochures with further detail. Indian operators weighing new routes, particularly from smaller and newly opened airports, would be wise to ask for a pilot using their own data, and to test how quickly the promised 48 hours holds in practice, because speed claims matter only when they survive messy, real-world datasets. Scepticism is healthy, but the underlying idea deserves serious attention.

For India’s expanding aviation network, the next breakthrough could begin with a better question—and a faster, better-informed answer. DOB AI’s proposition brings together decades of industry knowledge and the analytical reach of artificial intelligence, but its value will ultimately be measured against real operational data and commercial outcomes. As the O’Bannons acknowledged, professional scrutiny remains essential. AI can help identify the opportunity; aviation professionals must decide whether it deserves a place on the departure board.