Turkish Airlines innovates with Red Hat OpenShift AI
Turkish Airlines · Türkiye
Turkish Airlines' technology company, Turkish Technology, deployed Red Hat OpenShift AI on premise, on bare metal, with support from a team of 5 Red Hat consultants, to build a scalable, cloud-ready AI infrastructure. The platform provides container orchestration for GPU compute resources and integrates with the Dremio distributed query engine as a data ingestion layer. Operations teams can now create data science workspaces in minutes rather than hours, and deployment times for AI models have halved thanks to standardized YAML-based deployment. AI initiatives span more than 60 live models, including real-time dynamic pricing, payment fraud detection, ground-time predictions, tail assignments, on-time performance predictions, and generative AI use cases for employee experience and productivity. More than 200 Turkish Airlines employees now work on AI-based development as citizen data scientists. The airline's Head of Data and AI, Emre Yavuz, said AI projects are targeted to create over USD 100 million in financial impact by boosting revenue, decreasing operational costs, and increasing efficiency.
Overview
Turkish Airlines' technology company, Turkish Technology, deployed Red Hat OpenShift AI on premise, on bare metal, with support from a team of 5 Red Hat consultants, to build a scalable, cloud-ready AI infrastructure. The platform provides container orchestration for GPU compute resources and integrates with the Dremio distributed query engine as a data ingestion layer. Operations teams can now create data science workspaces in minutes rather than hours, and deployment times for AI models have halved thanks to standardized YAML-based deployment. AI initiatives span more than 60 live models, including real-time dynamic pricing, payment fraud detection, ground-time predictions, tail assignments, on-time performance predictions, and generative AI use cases for employee experience and productivity. More than 200 Turkish Airlines employees now work on AI-based development as citizen data scientists. The airline's Head of Data and AI, Emre Yavuz, said AI projects are targeted to create over USD 100 million in financial impact by boosting revenue, decreasing operational costs, and increasing efficiency.
The challenge
Turkish Technology's technology infrastructure lacked a container orchestration platform between Jupyter Notebooks and compute resources, so anyone could consume all the compute resources, leaving none for others; the airline needed to support data scientists in developing AI models and empower the entire business to become AI driven.
The solution
The airline's technology company, Turkish Technology, worked with Red Hat Consulting (a team of 5 consultants) to implement Red Hat OpenShift AI on bare metal, on premise, providing a container orchestration layer that manages GPU compute resources and integrates with the Dremio distributed query engine as a data ingestion layer. The solution included custom development environments, automated deployment for models and pipelines, and custom monitoring and alerts, with data scientists using standardized YAML-based deployment templates.
Reported business value
The operations team can now create data science workspaces in minutes rather than hours, and deployment times for AI models have halved. AI initiatives currently span more than 60 live models, including real-time dynamic pricing, payment fraud detection, ground-time predictions, tail assignments, on-time performance predictions, and generative AI use cases for employee experience and productivity. More than 200 Turkish Airlines employees now work on AI-based development as citizen data scientists. AI projects are targeted to create over USD 100 million in financial impact by boosting revenue, decreasing operational costs, and increasing efficiency.
Sources
Open any source and check the claim yourself — that is the point of the register.
Other transportation entries in the register.
How Schiphol is leveraging tech, design, data and AI-powered intelligence to redefine airport capacity and flow management
Royal Schiphol Group built in-house AI-powered tools — Dynamic Time Slots, (Passenger) Flow Balancing, and Gate Planning Insights — to align passenger demand with security and gate capacity. Dynamic Time Slots lets passengers pre-book security check times, steering an average of 7.5% of passengers away from peak moments (up to 22% on critical days), with 99.6% of passengers waiting under 10 minutes. Flow Balancing uses real-time sensor data, predictive models and simulation (a digital twin) to steer passenger groups, preventing over 4,000 minutes of crowding in 2024. Gate Planning Insights uses machine learning to optimise gate stand planning and turnaround operations. Overall passenger satisfaction score is 4.4 out of 5.
Amphitrite Rides AI Wave to Boost Maritime Shipping, Ocean Cleanup With Real-Time Weather Prediction and Simulation
France-based startup Amphitrite fuses satellite data and AI to simulate and predict oceanic currents and weather, using the NVIDIA AI and Earth-2 platforms. Its fine-tuned, three-kilometer-scale AI models (dubbed ORCAst), trained on NVIDIA GPUs, analyze ocean current, wave, and wind data to help ships optimize routes and reduce fuel consumption and carbon emissions. Amphitrite trains and runs its AI models using NVIDIA H100 GPUs on premises and in the cloud, building on the FourCastNet model from Earth-2. Fusing AI and satellite imagery, Amphitrite can improve the accuracy of global ocean current analyses by up to 2x compared with traditional methods. A case study along the Mediterranean Sea found the NVIDIA-powered Amphitrite fine-scale routing solution helped reduce one shipping line's carbon emissions by 10%. Shipping and oceanographic companies using Amphitrite's solutions include CMA-CGM, Genavir, Louis Dreyfus Armateurs, and Orange Marine; the company also works with an NGO to track and remove plastic pollution in the Pacific Ocean.
Capgemini pilots AI-RAN-connected autonomous shuttles under Horizon Europe's Project ULTIMO
Capgemini is working within Project ULTIMO, a Horizon Europe-funded initiative, to demonstrate AI-RAN support for large-scale autonomous mobility across European cities. Autonomous shuttles equipped with NVIDIA Jetson Orin modules process sensor data locally, while select video and telemetry streams are sent over 5G to agentic AI applications running on NVIDIA AI-RAN servers for scene understanding, incident and safety detection, and accessibility insights, with mission-critical 5G traffic given priority access to GPU resources.
Pony.ai Realizes Gen-7 Robotaxi City-wide Unit Economics Breakeven
Pony.ai's Gen-7 Robotaxi reached city-wide unit-economics breakeven in Guangzhou in November 2025, with daily average orders per vehicle reaching 23, following official launch of fully driverless commercial Robotaxi operations in Guangzhou, Shenzhen and Beijing. The company operated 961 Robotaxi fleet vehicles (667 Gen-7 units) as of November 23, 2025, targeting 3,000+ vehicles by end of 2026, and reported an additional 20% reduction in Gen-7 autonomous driving kit bill-of-materials costs for 2026 production versus the 2025 baseline. Robotaxi services revenue grew 89.5% year-over-year in Q3 2025, with fare-charging revenue up over 200%.
Was this helpful?
Your feedback helps us improve our use case database