The Platform

A decision workspace,
not another dashboard.

Krila unifies aviation data and applies AI-driven analysis so network planners can evaluate routes, simulate scenarios, and optimize revenue in minutes, not days.

The Agentic Layer

From scattered tools to executed decisions, in three phases.

Phase 1 of 3 · Connect · Krila connects to your PSS and industry data sources. One layer, always current.
01

Unified Data Layer

Schedules, bookings, competitive capacity and demand signals are joined at the O&D level the moment your connectors come online. No reconciliation. No stale exports. No “let me check if the numbers match.”

In practice
Ask “show me capacity vs. bookings on every transcon route” and Krila returns the joined view in under two seconds. The same query in your existing stack takes an analyst an hour.
02

AI Route Identification

Krila ranks candidate routes against your fleet, hub structure and target margin profile. The Krila Score is explainable: every rank shows the demand signal, the connectivity it unlocks, the competitive gap and the operational fit.

In practice
A 738 freed up by a winter retirement gets matched to four high-confidence O&Ds, each with annual contribution, sensitivity and the assumptions behind the score.
03

What-If Simulation

Build a scenario the way a planner thinks: change frequency, change gauge, change day-of-week pattern. Krila reruns the network with codeshare flow, hub bank effects and spill / recapture handled natively.

In practice
“What if SEA–HNL goes daily instead of 4× weekly?” returns a side-by-side with $770K of annual contribution, a 3.4-point load factor cost, and the aircraft availability sensitivity that drives both.
04

Revenue Intelligence

Yield, RASM, fare class mix and stage-length-adjusted comparisons live alongside the schedule view. Premium uplift on a long-haul route surfaces at the same time the route does, not three meetings later.

In practice
JFK–LHR shows premium yield up 8.4%, but stage-length-adjusted RASM trailing LHR–CDG by 3.6¢. Krila flags the fare class mix as the gap, not the headline yield.
05

Competitive Monitoring

OAG and ATPCO are watched continuously. When a competitor files a new schedule or a fare change that touches your network, Krila has already pulled the relevant context and drafted a response by the time you see the alert.

In practice
Southwest files 2× daily DAL–DEN at 09:14. By 09:26, Krila has scored four response options, attached confidence levels, and written up the recommended action with assumptions visible.

See it on your routes.

30 minutes. Your data. No slides.

Request DemoHow it works

Or email us at hello@krila.ai