AI cloud infrastructure,
built for data workloads.
GPU compute and managed services for training, fine-tuning, inference, and the pipelines that feed them. Without hyperscaler prices, lock-in, or ticket queues.
no credit card required · pay-as-you-go from $0.39/GPU-hour
Trusted by data and ML teams
The platform
One stack from raw data to serving.
Each pillar is a first-class product, designed to compose. Use one, use all four.
Inference & Serving
Low-latency model serving with autoscaling and batched throughput tuned for tabular and warehouse workloads.
Training & Fine-tuning
Multi-GPU jobs with checkpointing, spot fallback, and one-line resumes. Bring your stack, keep your weights.
Data Pipelines & Warehouse
Native connectors for Snowflake, BigQuery, Databricks, and S3. Stream features and labels without a re-platform.
Generative AI & Models
Curated open models, embeddings, and RAG primitives. Ship a working demo in an afternoon, not a quarter.
Developer experience
From zero to GPU in one command.
A small, sharp CLI and an SDK that gets out of your way. No YAML mazes, no console clicking. Reproducible by default.
$ dv login
$ dv gpu launch \
--type h100 \
--image datavere/torch:2.4 \
--mount s3://acme/warehouse:/data \
--command "python train.py"
→ provisioning h100-80g · us-west · spot
→ ready in 47s · ssh dv-3f9a
→ logs streaming · http://localhost:8265Community
Built with our community.
20,000 developers swap recipes, file PRs, and ship together. We invest in programs that put practitioners first: Data Champs, monthly meetups, and an open roadmap.
Discourse
4.2k threadsSupport, bug reports, product feedback.
GitHub
1.1k starsSDK, docs, examples, open issues.
Luma meetups
monthly, SF~65 builders per night, plus virtual.
Spin up your first GPU in 60 seconds.
Free credits for new accounts. Bring your data, bring your code, keep your weights.
- Pay-as-you-go, no commits
- Spot and reserved capacity
- Open SDK, open docs, open roadmap
- Start building