> ## Documentation Index
> Fetch the complete documentation index at: https://docs.getimpala.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Impala AI is a dynamic inference platform built for enterprises running AI at production scale.

Unlike inference solutions optimized for chat-speed latency, Impala is purpose-built for high-volume asynchronous workloads. By dynamically adapting to real workload shapes across heterogeneous GPU infrastructure, Impala delivers up to 10x lower cost per token compared to leading inference platforms — no rate limits, no pre-warming.

Impala is built to adapt to your workloads in real time through async adaptive scheduling. It treats inference as a high-performance computing problem, not a web service problem. It runs on your cloud, in your VPC.

Impala is vertically integrated across the entire stack — optimizing end-to-end from kernels to orchestration.

## Use cases

* Nightly ETL with AI-enriched transformations
* Data curation and labeling pipelines (computer vision, NLP)
* Compliance report generation (financial services, AML/CTF analysis)
* Document processing and summarization at volume
* Web scraping and content enrichment
* MCP agent orchestration
* Code review / analysis pipelines
* Multi-step agentic workflows (planning, executing, evaluating, retrying)