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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.

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.

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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)