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Services and competences

We answer management questions with data and numerical algorithms, build business analysis as end-to-end data pipelines, and offer extensive domain expertise in airports and airlines.

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Focus areas

General competences

Demand modeling and forecasting

What. Build forecast models for future product demand. Quantify interactions of market players. Measure price elasticity, design and interpret A/B tests.

How. Econometric techniques and expert market insights. Differentiated product and logit demand specifications.

Machine learning

What. Apply state-of the art machine learning techniques for business transaction outcome predictions.

How. Probabilistic neural networks with task-tailored architectures, decision trees and other methods. Technology stack such as XGBoost and Tensorflow Probability.

Simulations and optimizations

What. Simulate business processes at atomic level. Optimize business decisions against simulations. Build custom dynamic decision engines for real-time deployment.

How. Simulation stack inspired by reinforcement learning applications. Optimizations with deterministic algorithms and randomized solution space search methods such as genetic alogirithms and reinforcement learning.

Data pipelines, large-scale data processing and analytical dashboards

What. Design and implement data pipelines to feed reports and dashboards with actionable analytics. Rapidly deploy data lakes for project purposes.

How. Technology stack such as Amazon Web Services, Apache Spark and Kedro.

Financial modeling

What. Forecast revenue, cost, cash flow and valuation metrics for capacity enhancement projects.

How. Use of volume drivers from own demand models. Extrapolation of historic unit performance and benchmarking to industry peers.

Industrial competences


What. Forecast traffic for purposes from short-term hourly operational dispatching to long-term master planning. Build future design day schedules and assess capacity bottlenecks in the sub-systems.

How. Field-tested set of forecasting and modeling techniques in end-to-end Python data pipelines. Use of industry guidelines such as International Air Transport Association Airport Development Reference Manual.


What. Plan passenger and cargo network and fleet for aircraft ordering and future business sizing.

How. Simulations and numeric optimizations as end-to-end Python data pipelines. Differentiated product modeling of market share and demand on new routes.

Work modes
Deployment for specific task within organization or wider project

Services on fixed scope or time and material basis with full or partial integration into clients' team. Examples:

  • One-off airport traffic forecast study as input into the investment case. Deliverables: report, forecast data tables, Python model.
  • Semi-annual updates of airline network and fleet plan. Deliverables: dashboards, Python model, model use training.
Effort-based services for scattered tasks, trainings and model maintenance

Services requiring short-term availability and flexible scoping. Examples:

  • Isolated task of modifying a data processing pipeline. Deliverables: Python code.
  • Co-improvement of running machine learning model with client's team. Deliverables: Python code, training sessions.
Provision of independent expert opinion within aviation domain knowledge

Services requiring third-party review or analysis by aviation industry expert. Examples:

  • Expert witness at a trial. Deliverables: report, testimony.
  • Industrial consultant review of a business case in an investment transaction. Deliverables: report.


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