Platform
One infrastructure layer for production AI.
QNTOR unifies models, agents, retrieval and GPU compute behind a single API and a single control plane — so teams ship AI systems instead of assembling infrastructure.
One AI infrastructure layer
Everything you need to build production AI.
From experimentation to production, QNTOR provides the infrastructure required to run enterprise-grade AI systems.
Model Deployment
Deploy leading open-source and proprietary models through a unified infrastructure layer.
Private AI Agents
Build intelligent agents capable of reasoning, retrieving information and executing enterprise workflows.
Enterprise RAG
Connect AI models securely to internal documents, databases and knowledge systems.
Model Fine-Tuning
Customize models using proprietary datasets and optimized GPU training infrastructure.
High-Performance Inference
Run low-latency AI inference using scalable GPU infrastructure.
Observability
Monitor model performance, token usage, latency, infrastructure utilization and costs.
Control plane
Operate every workload from one console.
Deployments, GPU utilization, knowledge bases, API keys, latency and spend in one operational view.
console.qntor.com / overview
Overview
Production workspace · eu-west-1 · illustrative data
Active Models
14
+3 this week
Running Agents
38
6 environments
GPU Usage
72%
24 × A100 pool
Requests
4.1M
last 30 days
Average Latency
182 ms
p50 inference
Monthly Compute
$46.2k
-8% vs. prior
Token throughput
tokens / s
GPU utilization
% of pool
Inference requests
req / min
Infrastructure cost
USD / day
p99 latency
412 ms
Cache hit rate
91.4%
Queued jobs
3
Built to scale
Infrastructure designed for AI workloads.
QNTOR orchestrates compute, models and enterprise data across scalable infrastructure — routing every request to the right runtime, on the right hardware, inside your security perimeter.
Reference architecture
Application Layer
QNTOR API
Agent & Model Orchestration
Model Runtime
GPU Compute
Enterprise Data Layer
Performance
Built for production workloads.
Sample values shown below are illustrative demo figures, not real production benchmarks.
Inference Latency
182
ms p50
GPU Utilization
72
% of pool
Requests / Second
9.4
k sustained
Token Throughput
48
k tokens/s
Infrastructure Cost
-31
% vs. baseline
Deployment
Deploy AI your way.
Fully managed AI infrastructure.
Start in minutes on managed GPU capacity with built-in observability and autoscaling.
Deploy within the customer's cloud environment.
Run the control plane and model runtime inside your own accounts and network boundary.
Combine private infrastructure with scalable cloud GPU resources.
Keep sensitive data in place while bursting heavy training and inference to the cloud.
Build your AI infrastructure with QNTOR.
Deploy private AI models and intelligent agents on infrastructure designed for the next generation of enterprise software.