> For the complete documentation index, see [llms.txt](https://quandora.gitbook.io/quandora-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://quandora.gitbook.io/quandora-docs/getting-started/introduction.md).
# Introduction
## About Quandora
Quandora is a finance-agent infrastructure for AI-native quant trading workflows.
We give finance agents the infrastructure they need across the workflow: factor mining, factor evaluation, strategy construction, strategy evaluation, paper trading, monitoring, and supervised deployment. The infrastructure enables your agent to produce structured reports on: what was tested, what passed, what failed, and what to improve next.
## Thesis
As trading becomes more agentic, it converges toward quant trading because serious agents need data, validation, feedback loops, risk controls, and evidence rather than vibes.
Finance does not need another chatbot. It needs:
* signal validation
* overfit detection
* microstructure / liquidity analysis
* cost and turnover realism
* backtesting and walk-forward checks
* reviewed factor memory
* reporting and audit trails
* security-aware workflows
The scarce layer is not another dashboard or raw data feed. The scarce layer is the evidence system that says whether an idea survived validation, failed out-of-sample, became too expensive to trade, decayed, duplicated prior attempts, or needs deeper review.
{% hint style="info" %}
Quandora is finance-agent infrastructure. It is not a guaranteed-profit tool, copy-trading product, or autonomous live-trading bot.
{% endhint %}
---
# Agent Instructions
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## Querying This Documentation
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