Keep data in-region
Model weights, data, and the control plane run on infrastructure you operate, in the region you choose.
Own your
AI stack.
Keep weights, data, and the control plane inside your jurisdiction.
Control where and how your models run.
Apply your own policies
Set who can reach each model with role-based access and your existing access controls. Run your evaluations before serving.
Operate on your stack
Deploy on Kubernetes or bare metal, with monitoring, priority queues, and durable jobs for production workloads.
One stack for VLAs, world action models, and media
VLAs and world action models
Run vision-language-action policies and action-conditioned world models for robotics and simulation.
Your models
Serve supported weights you own, license, or build with our team.
Video
Generate video from text or images, including streaming workloads.
Image
Generate, edit, and upscale images for interactive or batch workflows.
Text
Generate, annotate, and train text for top-tier LLM performance.
Audio
Serve speech, music, and sound models for voice and real-time applications.
Engineered for your environment.
Every deployment starts with your environment. Hedra engineers assess your hardware, model requirements, and expected workload, then work with your team to rapidly deploy.
Underneath, WMR optimizes scheduling, quantization, and attention for your hardware.
Build models with our research team.
Train for your task.
Work with Hedra’s researchers on your data, training objectives, and evaluations.
Keep improving the model.
Your team keeps the pipelines, training recipes, and evaluations to continue iterating.
Plan your
sovereign stack.
Bring your jurisdiction, hardware, and model requirements. We’ll plan a deployment inside your perimeter.
