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ML demand forecasting + dynamic, continuous pricing

Maximize revenue with forecasting that's actually accurate.

Yieldcraft maximizes airline revenue by pairing accurate ML demand forecasting with dynamic, continuous pricing — every fare on every seat repriced in real time as demand shifts, not just once a night.

0Engines: forecast,
price, defend
0Engine checks passing
in the pilot test pack
0Days of booking
horizon modelled
Explore the platform

One loop. Maximum revenue.

Scroll — or pick a stage — to walk the engine that maximizes revenue on every seat you fly.

signals · live feeds · illustrative data
Interactive · Live estimate

How much revenue is your network leaving on the runway?

Move the sliders to match your operation. The estimate applies an assumed uplift from demand forecasting and continuous pricing to your static-pricing baseline.

Your operation

Rough figures are fine — this is a directional estimate.

120
180
82%
$145
Projected annual revenue gain
$0
On an estimated baseline of $0/yr
Revenue uplift0%
Illustrative estimate: the calculator applies an assumed 4–9% uplift over static pricing. It is not a measured Yieldcraft result. Actual results depend on market structure, demand volatility, and competitive density.
The platform

Accurate forecasting. Continuous pricing. One revenue brain.

Maximize revenue by combining accurate ML demand forecasting with dynamic, continuous pricing — each module works alone and compounds together.

Foresight — accurate ML demand forecasting

A machine-learning forecast for every flight, cabin, and point of sale, tuned for accuracy against your actual bookings. It reads bookings, seasonality, events, and macro signals to predict demand weeks before your legacy system reacts.

  • Per-flight demand curves updated hourly
  • Event & disruption detection built in
  • Explainable, override-friendly outputs
foresight · LHR–JFK · demand · illustrative data
-56d-42d-28d-14d-7dDep

Optima — dynamic, continuous pricing

Optima turns accurate forecasts into revenue. It solves for the revenue-maximizing price of every seat continuously — not once a night — respecting your fences, floors, and brand rules, and pushes fares to your inventory in milliseconds.

  • Continuous, class-free pricing
  • Business-rules engine you control
  • Willingness-to-pay by segment
optima · fare heatmap · illustrative data
Low fareOptimalHigh fare

Radar — competitive tracking

Radar watches every competitor on every O&D you fly, in real time. See fare gaps the moment they open, get alerted before you're undercut, and let Optima respond automatically within your guardrails.

  • Real-time fare & availability scans
  • Undercut & fare-war alerts
  • Auto-response within your rules
radar · CDG–BCN · illustrative data
Why Yieldcraft

Powerful science, made pilot-simple.

We wrap serious revenue maximization in an interface your analysts actually enjoy using.

Runs on the systems you already have

Yieldcraft works from a ticketing extract out of your reservation system and the fare ladder you already file. You keep your fleet, your fare classes and your distribution.

Powerful because it's governed

Every recommendation shows its reasoning and runs inside your floors, fences, and rules. Trust it, tune it, or override it — you stay in command.

Your data stays yours

Your commercial data is used to forecast and price your own network. It never trains anyone else's model.

Always turned toward demand

Prices reorient in milliseconds as the market shifts — never committed to last night's view. No overnight runs, no stale recommendations at 8am.

Analyst-first UX

The clarity of a consumer app over the depth of an RM engine. Onboard a new analyst in a day, not a quarter.

Partners, not vendors

You work directly with the people who build the engines, and your feedback decides what gets built next.

Pilot evidence

What the engines did on a real regional network

Ready when you are

See your revenue uplift on a real route.

Give us one O&D and 30 minutes. We'll show you the fares you're leaving behind — live, on your own data.