AI built into the network, not bolted on.
TDS uses machine learning where it pays off for carriers: building trips across the network, forecasting demand and setting fares. It runs on 15 years of structured network data, and carriers stay in control of the decisions.
Applied where carriers earn revenue and save time.
Routing engine
AI-optimized routings across 7.5M+ routes, including interline connections between carriers.
Demand forecasting
Ridership predicted by route and departure from booking history, seasonality and events.
Dynamic pricing
The MMC Fare Pricing Pipeline sets fares by market, capacity and time to travel, starting from your current fare structure.
Revenue management
Models weigh demand signals, channel performance and each trip's value to the whole network.
Network intelligence
Predictive models for ridership, pricing performance and route viability, from historical demand and competitive behavior.
Found in AI answers
Schedules, fares and stops published as structured data that AI assistants can quote correctly.
AI is only as good as its data.
Because TDS runs ticketing, inventory and distribution across the network, its models learn from signals a single carrier's system never sees, built up over 15 years.
- Cross-carrier demand patterns
- Channel-level performance shifts
- Market substitution effects
- Real passenger booking behavior
- Network-level pricing dynamics
Carriers stay in control.
AI at TDS supports the people who run the network. It doesn't replace their judgment.
- AI suggests fares and schedules, and your team decides what goes live
- Models work within your fare structure, rounding rules and override tiers
- Each forecast and suggestion shows the signals behind it
- Start small: move from static fares to AI-assisted pricing step by step
- Your data serves your network: insights are aggregated, and carrier data isn't sold
See TDS in action.
A demo with our team, focused on the products you need, with time for your questions.