Ship AI workloads from your code
TIR's REST API powers the full AI lifecycle — fine-tune and deploy models, run inference, orchestrate pipelines and manage GPU clusters without leaving your terminal.
POST https://api.e2enetworks.com/myaccount/api/v1/gpu/
Authorization: Bearer <TIR_API_TOKEN>
{
"model": "llama-3-8b-instruct",
"prompt": "Summarise the E2E TIR platform.",
"max_tokens": 256
}200 OK # streamed completion// browse by category
The whole AI/ML lifecycle, as an API
From foundation models to GPU clusters — jump into the reference for what you're building.
AI Labs notebooks and GPU instances for AI/ML workloads.
ExploreStorage integrations and managed buckets for model artifacts and data.
ExploreDeploy models, serve real-time predictions and explore Playground Gen AI endpoints.
ExploreProvision training and private clusters with dedicated GPU, CPU and RAM.
ExploreNetworking primitives for your TIR projects and endpoints.
ExploreEndpoints for RAG.
ExploreBuild serverless training workflows with reliable retries and unlimited re-runs.
Explore// developer experience
Purpose-built for AI teams
GPU-native primitives with the ergonomics of a modern REST API.
Token authentication
Authenticate with your TIR API token and project context in the Authorization header.
End-to-end AI lifecycle
Fine-tune, deploy and serve models, then orchestrate pipelines — all through one API.
GPU-native
Spin up optimized GPU containers with PyTorch, TensorFlow and Triton pre-configured.