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Inference platform by Inference.net
Inference platform is a platform for understanding, evaluating, and improving the AI systems you ship.
Create an account to get started with the Inference platform.
The Inference platform
Inference platform is built around two products. Use them on their own or together.
Tracing
Capture full traces of every LLM call, tool call, and agent step. Then let Halo, our open-source agent-loop optimizer, read your traces and tell you what to fix in prompts, tools, and the harness itself.
Gateway
Route LLM traffic through Inference Gateway to capture every request, watch usage and cost, build datasets, run evals, and fine-tune and deploy task-specific models on dedicated GPUs.
Tracing is for agent improvement. Gateway is for inference observability and training task-specific models from your captured traffic. Most teams start with one and add the other later. They also compose: when your agent calls LLMs through Gateway, trace spans line up with the same requests Gateway is recording.
Quick Start
Tracing
Capture your first trace
Install the tracing SDK and capture LLM calls, tool calls, and agent steps in minutes.
Analyze your traces
Inspect trace trees in the dashboard and run Halo to find what to improve.
Gateway
Record your first LLM call
Route traffic through Inference Gateway to capture LLM calls and view metrics.
Run your first eval
Define quality, measure it, and compare models side by side.
Train and deploy a model
The full loop: data, training, and a production endpoint.
Use the Inference API
Call open-source, popular closed-source, and custom models with one API key.
Inference platform
Tracing
Collect OpenInference-shaped traces from LLM SDKs, agent frameworks, and custom application code.
Gateway
Capture your LLM traffic and get metrics and visibility into your production usage.
Datasets
Create and manage datasets for evaluation and training.
Evaluate
Evaluate models to measure quality across model candidates.
Train
Train a custom model on your production data to improve performance, lower latency and cost.
Deploy
Deploy a model to a dedicated GPU to use in production.