# HiveQ

> AI-native institutional trading platform. Author quantitative strategies in
> Python, backtest them on an engine that simulates real market microstructure,
> optimize, and deploy to live capital -- with no market-data contracts or
> servers of your own. This file (the llms.txt convention, see llmstxt.org)
> points AI assistants to clean, machine-readable versions of key HiveQ pages.

## Documentation
- [HiveQ Flow SDK -- API reference](https://docs.hiveq.ai/): the Python SDK for building, backtesting, and deploying strategies (SDK source v1.0.0).
- [SDK reference, full text for LLMs](https://docs.hiveq.ai/llms-full.txt): the complete API reference as one markdown file.
- [SDK documentation provenance](https://docs.hiveq.ai/sdk-docs-source.json): the exact GitHub commit and canonical file hashes used for this deployment.
- [Runnable SDK examples](https://github.com/Khawk-LLC/hiveq_sdk/tree/main/examples): complete strategy and remote-function examples from the source repository.

## Guides
- [Protected product onboarding](https://portal-preview.hiveq.ai/onboarding): six videos and nine written steps from SDK installation through an inspected backtest and human-confirmed competition handoff.

## Product preview
- [Unified product front door](https://hiveq.ai/preview): the connected HiveQ public preview.
- [Competition experience](https://hiveq.ai/preview/competitions): public discovery, sealed-rank model, and browser-only submission simulation.
- [Competition and scoring design](https://hiveq.ai/preview/scoring): Competition Score, durable HiveQ Score, and private Allocation Score. LLM text: https://hiveq.ai/preview/scoring/llms.txt
- [HiveQ sign in](https://staging.hiveq.ai/sign-in?redirect=%2F): authenticated application handoff. The public preview does not store credentials or alter the staging application.

## Notes
- Preview pages are pre-launch and not indexed by search engines. Competition
  identities, submissions, scores, dates, prizes, and resolved results are
  illustrative. These
  llms.txt files exist so anyone with the link can hand an AI a clean version of
  the content instead of asking it to parse rendered HTML.