UbiOps
Model serving and orchestration platform for private AI
About UbiOps
UbiOps lets organizations deploy, scale and manage AI models and workloads on any infrastructure, including local, hybrid and multi-cloud, without managing Kubernetes directly. It emphasizes public sector, healthcare and critical infrastructure use.
Common use cases
- Deploy private LLMs
- Serve vision models
- Run time-series workloads
Products and services
UbiOps platform
Model deployment, orchestration, API management and monitoring
On-demand GPU
Scalable GPU capacity
UbiOps Training
Training offering
Key features
- Model serving
- Hybrid deployment
- Version control
- Access management
- Auto-scaling
- Auditing
Integrations
- NVIDIA
- Kubernetes
UbiOps alternatives
FAQs
Where can it run?
Locally, hybrid or multi-cloud.
Who is it for?
Enterprises needing private AI.
Does it need Kubernetes skills?
No, per its site.
Work at UbiOps? Request updates to this profile. Update this profile
Compare with similar providers
All ML Operations providersAnyscaleManaged platform for running Ray-based AI workloads at scale
BasetenInference platform to train, serve and scale open source and custom models
BentoMLOpen source framework and cloud platform for serving AI models
Blend360Data science, analytics and AI services firm
CerebriumServerless GPU infrastructure for AI workloads
ChalkReal-time feature platform and inference runtime for production AI
ClearMLAI infrastructure control plane with experiment tracking and GPU management
Edge ImpulsePlatform for building and deploying machine learning on edge devices