GPU hosting, model serving and the operations around them.
MLOps / AI Infrastructure
Run models on Webyne GPU infrastructure with the serving, scaling, monitoring and cost control that production requires — or let us operate it for you.
- Typical timeline
- 2–6 weeks to stand up
- Engagement model
- Monthly managed service
What you get
- Dedicated and shared GPU inference pools
- vLLM / Triton model serving with autoscaling
- Endpoint management with TLS, quotas and rate limits
- GPU utilisation, VRAM, latency and throughput monitoring
- Per-tenant metering of GPU-hours, tokens, storage and bandwidth
What changes
- Predictable inference cost per request
- Capacity that scales with real demand
- Utilisation data to right-size the cluster
Questions people ask
- Can we bring our own model weights?
- Yes — open-weight models and your own fine-tuned adapters both run on the platform.
Considering mlops / ai infrastructure?
Run the free assessment first. It scores feasibility against your own data and volumes, and tells you what it would cost before anyone quotes you.