GPU infrastructure + private cloud, on tap.
H100 and L40S inference and training, plus full-stack hosting for your app. our managed AI partner with prompt caching included. Predictable monthly bills.
The problems we're built to solve.
GPU availability is unpredictable
public cloud availability for H100s is hit-or-miss. Lead times kill experimentation.
Hyperscaler bills are unpredictable
Egress, snapshot storage, and reserved instance math wreck founder runway.
Model hosting requires expertise
vLLM, TensorRT-LLM, sharding, quantization — most teams don't want to own this.
RAG data is sensitive
Customer documents flowing through public-cloud regions creates compliance friction with B2B customers.
Latency from inference to app
Inference in one region, app in another, customer in a third — the math doesn't work for real-time.
Multi-environment costs scale linearly
Dev, staging, prod — each a full duplicate on a hyperscaler. Bill grows faster than the team does.
What customers measure.
What you get on day one.
Every engagement ships with the operational foundation — encryption, audit logging, monitoring, BAA / DPA — already in place.
Bare-metal GPUs
NVIDIA H100 (8×) and L40S (4×) servers available as dedicated nodes. Lease or buy via marketplace.
managed AI integration
First-class our managed AI API on Pro and Scale tiers, with prompt caching enabled by default — typical 50-70% token cost reduction.
Inference platform
vLLM, TensorRT-LLM, llama.cpp pre-tuned and supported. Bring your own weights or use a managed open-weights deployment.
Vector DB + RAG
Managed pgvector, Qdrant, or Weaviate on dedicated tenancy. Ingest, embed, and serve from one platform.
Observability built in
Token throughput, latency, cost per request, eval results — all in one dashboard. No DIY observability stack.
Customer-data protection
Your customer data never trains a model. Customer-held keys, encrypted-at-rest indexes, audit logs by default.
“We replaced a $14k/month public-cloud bill with a $2,400/month Ultiblob bill — and we got managed prompt caching for free. The first six months of runway came back.”
Starting points, not surprises.
Real numbers for typical engagements. The estimator returns yours in 30 seconds.
- Dedicated tenancy
- Managed AI API + prompt caching
- pgvector or Qdrant
- GPU access via marketplace
- Dev / staging / prod
- 4× L40S dedicated inference
- BYOK encryption
- Multi-region failover
- 24/7 NOC
- Customer-data DPA
- 8× H100 dedicated nodes
- NVLink fabric
- Customer success engineer
- SOC 2 evidence on tap
- Dedicated MLOps engineer
Common questions, answered.
- Yes. Llama, Mistral, fine-tuned variants, custom architectures — all supported. We tune the inference runtime for your weights.
Ship your first inference workload in under two weeks.
Free architecture session with a senior engineer. We map your inference + RAG + app tier onto our private cloud and return a fixed-price build SOW.
Inference + RAG platform
Workload-isolated model serving with customer-key-encrypted embeddings.
- → User → API gateway (key auth) → router → inference pod (GPU)
- → Ingest pipeline → embed → vector store (per-tenant KEK)
- → Telemetry → metering store → billing event