Provider

Ollama + Hyperion

Transform local open-source models into production-ready enterprise services. Hyperion bridges the gap between raw local compute and infrastructure-grade reliability.

Traffic Control

Production Limits

Implement production-safe rate limits and usage quotas on local models. Prevent a single process from saturating your GPU resources.

Security

RBAC & IAM

Layer enterprise Identity and Access Management over Ollama. Control which teams or applications can access specific local models.

Efficiency

Semantic Caching

Reduce local inference load by up to 90%. Cache semantically similar queries to provide sub-millisecond responses.

Visibility

Observability

Get full traces, latency breakdowns, and token accounting for your local stack. Monitor local uptime with standard telemetry.

Production Deployment

Hyperion acts as a secure reverse-proxy for your Ollama instances, enabling deployment in air-gapped or high-security VPC environments.

Architecture

Enterprise Parity

→OpenAI Translation: Use legacy OpenAI SDKs seamlessly with any Llama, Mistral, or Gemma model.
→Load Balancing: Distribute traffic across multiple Ollama nodes in your k8s cluster.
→Zero-Trust: Terminate TLS at Hyperion and proxy to internal Ollama instances securely.

Implementation

Switching from cloud to local-enterprise compute is a one-line change.

from hyperion import HyperionClient

client = HyperionClient()

# Hyperion orchestrates your local Ollama instance with 
# enterprise features: Rate Limiting, RBAC, and Semantic Caching.
res = client.chat.completions.create(
    model="ollama/llama3.2:3b",
    messages=[{"role": "user", "content": "Analyze system logs for anomalies."}]
)

print(res.choices[0].message.content)