> ## Documentation Index > Fetch the complete documentation index at: https://docs.tetryx.io/llms.txt > Use this file to discover all available pages before exploring further. # Lynx > Batch simulation orchestration and distributed runner management by Tetryx Lynx is a simulation orchestration platform by Tetryx. It runs large-scale Monte Carlo studies across a pool of distributed runners, tracks every job from submission to completion, and exposes a simple HTTP API for submitting work and reading results. ## How it works You submit a batch of simulation runs to the Lynx API. Lynx distributes those runs across your runner pool. Each runner picks up jobs, executes your simulation, and reports results back. You poll the API for status and retrieve results when complete. `POST /jobs` with your simulation config and run count. Lynx generates the parameter samples and queues the jobs. Your runners pick up jobs from the queue, run your simulation, and report results. Poll batch or job status via the API. Fetch results when jobs reach a terminal state. ## Base URL ``` https://api.lynx.tetryx.io ``` ## Key concepts | Term | Meaning | | -------- | ----------------------------------------------------------- | | `batch` | A submitted collection of jobs — one Monte Carlo study | | `job` | One individual simulation run within a batch | | `runner` | A worker process you deploy that picks up and executes jobs | ## What is available today * Submit Monte Carlo batches via `POST /jobs` * Inspect batch and job status via the read APIs * Manage your runner pool: inspect, drain, and resume runners * Retry handling: failed jobs are automatically retried up to `max_retries` The following features are planned but not yet available: * Sessions (long-lived interactive workloads) * Artifact retrieval APIs * API authentication (currently unauthenticated) ## Get started Submit your first batch and verify job results in minutes. Learn how to deploy and manage your runner pool. Understand the job and batch model. Full HTTP API reference.