Platform
Infrastructure built for production AI
Dedicated GPU clusters, hardened model endpoints, and a developer API that slots into any stack — all under one SLA.
GPU Clusters
Dedicated compute.
Zero cold-start.
Every Kybra cluster runs on dedicated silicon — no shared tenancy, no noisy neighbours. NVLink interconnects and NVMe-attached storage come standard. Provision an H100 cluster in under 60 seconds.
- H100 SXM5, A100 80GB, and L40S available
- NVLink and InfiniBand for multi-node jobs
- NVMe persistent storage, always attached
- Kubernetes-native scheduling with priority queues
- Per-job GPU telemetry and cost dashboards
- Spot and reserved pricing with automatic failover
3.2 PB/s
Bandwidth
0.8μs
Interconnect
$2.89/hr
Per H100
Model Hosting
Any model.
Production endpoint. Now.
Deploy 150+ open-source models behind a hardened inference endpoint in one command. Auto-scaling, rolling deployments, and version pinning are built in — your team never touches a server.
- Deploy from Hugging Face or custom weights
- Scales to zero when idle — instant scale-up on demand
- Version pinning and one-click rollbacks
- Private endpoints with mTLS for enterprise workloads
- Streaming, batching, and function calling included
meta/llama-3.1-70b-instruct
v3mistralai/mistral-7b-v0.3
v1google/gemma-2-27b-it
v2Identity & Access
Multi-tenant IAM.
Audited by default.
Every resource is scoped to an org, project, and user — no cross-tenant data exposure, ever. API keys are scoped to fine-grained permissions, shown once, and fully auditable. Rotate or revoke instantly.
- Org → Project → User hierarchy with role inheritance
- Scoped API keys: one-time display, rotation, and revocation
- mTLS for private inference endpoints
- 100% audit coverage — every access decision is logged
- SOC 2 Type II aligned controls
- Future: SAML SSO, SCIM provisioning, and MFA enforcement
3 roles
Org roles
12 scopes
API scopes
100% traced
Audit cover.
import kybra
client = kybra.Client(api_key="kb_...")
# Stream from any hosted model — OpenAI-compatible
for chunk in client.inference.stream(
model="meta/llama-3.1-70b-instruct",
messages=[{"role": "user", "content": "Hello"}]
):
print(chunk.delta, end="", flush=True)Developer API
Drop in, not rip out.
The Kybra API is fully OpenAI-compatible. Point your existing SDK at a new base URL and you're done — no code changes, no migration risk. SDKs for Python and TypeScript, plus a CLI for local dev.
OpenAI-compatible
Swap your base URL. Keep every line of existing code.
Streaming and batching
Server-sent events for real-time output. Async batch for throughput.
Function calling
Structured JSON outputs and tool use — same spec as OpenAI.
Your cluster is ready
in 60 seconds.
No credit card required. Scale from a single model endpoint to thousands of GPUs — at your pace.
Questions? [email protected]