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InferiaLLM

InferiaLLM - The Operating System for LLMs in Production | Product Hunt

The Operating System for LLMs in Production.

InferiaLLM is an operating system for running LLM inference in-house at scale. It provides everything required to take a raw LLM and serve it to real users: user management, inference proxying, scheduling, policy enforcement, routing, and compute orchestration - as one system.

$pip install inferiallm
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Need Private, In-House LLM Infrastructure?

We work directly with teams deploying InferiaLLM for regulated and sensitive environments.

Schedule a Technical CallArchitecture discussion only
Ecosystem

Deploy on any Infrastructure

SELF-HOSTED · CLOUD-AGNOSTIC · PROVIDER-NEUTRAL

NosanaNosana
akashakash
VPC
GCPGCP
AzureAzure
AWSAWS
InferiaChatInferiaChat
System Demo

InferiaLLM In
Action.

See how InferiaLLM consolidates deployment, security, routing, and governance into a single authoritative control plane-going from raw model to production API in minutes.

USER_REQUESTSCHEDULINGINFERENCEAudit
The Reality

The Problem.

To serve models in production, teams are forced to build a massive internal platform from scratch.

Inference Proxy
User Management
Auth & RBAC
Request Scheduling
Routing Infrastructure
GPU Orchestration
Audit Logs
The Solution

What InferiaLLM Is.

The Operating System for LLM inference. It sits between users and compute, owning the lifecycle.

User & App Access
Inference Proxying
Request Validation
Scheduling & Routing
Compute Execution
Resource Tracking
Audit & Observability
Replaces the internal platform
Compute Pools
Qwen3-Coder

Qwen3-Coder

AWS (us-east-1)
Running
VRAM Usage
42GB
Throughput142 tok/s
Mixtral-8x7b

Mixtral-8x7b

Nosana (DePIN)
Scaling Up
VRAM Usage
24GB
Throughput---
DeepSeek-V3

DeepSeek-V3

GCP (europe-west)
Running
VRAM Usage
38GB
Throughput89 tok/s
Infrastructure

Execution &
Compute.

InferiaLLM runs inference across private infrastructure. The OS schedules and routes execution so applications never manage compute directly.

Zero-config Docker containers
Auto-scaling GPU orchestration
On-prem GPU clusters
Kubernetes-based inference
Isolated or sovereign environments
Developer Flow

How Developers
Use Inferia.

Framework-level integration with no fluff. InferiaLLM becomes the single entry point for your entire inference stack.

Step 01

Register

Register users and applications. InferiaLLM becomes the single entry point for all inference traffic.

Step 02

Define Rules

Define execution rules: configure who can use which models, set resource limits, and enforce security policies.

Step 03

Attach Compute

Attach models and compute backends (Kubernetes, On-prem, Cloud). The OS handles scheduling and routing automatically.

Step 04

Serve Users

Serve real users immediately. Inference execution, resource tracking, and audit logging happen automatically.

Use Cases

Who is this
For?

InferiaLLM is used to run secure, private LLM inference in-house at scale.

01

Law Firms

Running confidential AI workflows. Legal data never leaves the firm's private VPC, ensuring client privilege is maintained while leveraging LLM capabilities for contract review.

02

Healthcare & Medical

Processing sensitive patient data (HIPAA). InferiaLLM allows hospitals to run diagnostic and summary models on-premise without sending PII to public API providers.

03

Financial Institutions

Deploying regulated AI systems. Banks use InferiaLLM to govern trading bots and customer analysis tools with strict audit logs and guaranteed data sovereignty.

04

Enterprises

Replacing internal LLM platforms. Instead of building a custom API gateway, teams deploy InferiaLLM as a ready-made OS to manage thousands of internal users and apps.

05

Sovereign Entities

Organizations that cannot send data to public AI services due to national security or strict compliance requirements.

Need Private, In-House LLM Infrastructure?

We work directly with teams deploying InferiaLLM for regulated and sensitive environments.

Schedule a Technical CallArchitecture discussion only
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InferiaLLMUNIFIED EXECUTION LAYER
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