# TextData

> Adaptive AI infrastructure for organizational research. TextData is adaptive research infrastructure for acquiring, preparing, and analyzing textual data in organizational research, built on an LLM-empowered deep-research engine and installed as an open-source system that can be extended and modified by a community of scholars.

Research infrastructure in development. The existing implementation is not yet ready for wide external adoption. Proposed work adapts it for TextData and supports the continuing development of its tools, workflows, and agents. Content updated November 2026.

## Pages

- [Home](https://textdata.info/): what TextData is, and an interactive drawing of how it works.
- [How it works](https://textdata.info/how-it-works/): Four interdependent elements. Researcher-directed inquiry. An engine for continuing adaptation..
- [Toolkit](https://textdata.info/toolkit/): Six toolkit items, three qualitative and three quantitative, each packaged for researcher use and further development.
- [Research foundation](https://textdata.info/foundation/): Research on textual methods, AI systems and agent design, and data sources.
- [Engine](https://textdata.info/engine/): The adaptive core of the infrastructure.
- [Colophon](https://textdata.info/colophon/): How this site is made.
- [AI defects](https://textdata.info/ai-defects/): illustrative failure modes and component evidence.
- [Blog](https://textdata.info/blog/): longer explanations of the research design.
- [When AI goes wrong in textual research](https://textdata.info/blog/when-ai-goes-wrong/): failure modes, examples and proposed responses.

## Components (one page each)

- [Deep-research engine](https://textdata.info/engine/): A researcher-directed engine for successive inquiry across literature, primary sources and technical repositories.
- [Textual-data literature reviews and database](https://textdata.info/foundation/literature-reviews/): Methodological syntheses and a searchable database for text annotation, model comparison and annotation-workflow design.
- [AI research systems and agent design](https://textdata.info/foundation/ai-research-systems/): A survey of AI research systems and reusable infrastructure, with a focused database of current agent-design and orchestration approaches.
- [Rich textual-data sources review](https://textdata.info/foundation/textual-data-sources/): A representative survey of textual sources and complementary structured data.
- [Grounded Theory](https://textdata.info/toolkit/grounded-theory/): A reusable AI toolkit for research using grounded-theory techniques.
- [Gioia Methodology](https://textdata.info/toolkit/gioia-methodology/): A reusable AI toolkit for Gioia-style qualitative analysis.
- [Eisenhardt Case Methodology](https://textdata.info/toolkit/eisenhardt-case-methodology/): An AI-assisted toolkit for Eisenhardt case-method research preparation.
- [Large-scale data acquisition](https://textdata.info/toolkit/large-scale-data-acquisition/): A reusable AI workflow for assembling, cleaning, and verifying large textual collections.
- [Combining ML, NLP and LLMs](https://textdata.info/toolkit/combining-ml-nlp-llms/): A measurement-design toolkit with a searchable methods catalogue, structured specifications, and a database interface.
- [LLM-annotation workflow](https://textdata.info/toolkit/llm-annotation-workflow/): A reusable LLM-annotation workflow prototype with executable tools for versioned requests, quotation checks and source-linked features.

## Explore with your AI

- [how-it-works](https://textdata.info/prompts/how-it-works.md)
- [foundation](https://textdata.info/prompts/foundation.md)
- [toolkit](https://textdata.info/prompts/toolkit.md)
- [colophon](https://textdata.info/prompts/colophon.md)
- [ai-defects](https://textdata.info/prompts/ai-defects.md)
- [blog](https://textdata.info/prompts/blog.md)
- [when-ai-goes-wrong](https://textdata.info/prompts/when-ai-goes-wrong.md)
- [Deep-research engine](https://textdata.info/items/deep-research-engine/AI-PROMPT.md)
- [Textual-data literature reviews and database](https://textdata.info/items/literature-reviews/AI-PROMPT.md)
- [AI research systems and agent design](https://textdata.info/items/ai-research-systems/AI-PROMPT.md)
- [Rich textual-data sources review](https://textdata.info/items/textual-data-sources/AI-PROMPT.md)
- [Grounded Theory](https://textdata.info/items/grounded-theory/AI-PROMPT.md)
- [Gioia Methodology](https://textdata.info/items/gioia-methodology/AI-PROMPT.md)
- [Eisenhardt Case Methodology](https://textdata.info/items/eisenhardt-case-methodology/AI-PROMPT.md)
- [Large-scale data acquisition](https://textdata.info/items/large-scale-data-acquisition/AI-PROMPT.md)
- [Combining ML, NLP and LLMs](https://textdata.info/items/combining-ml-nlp-llms/AI-PROMPT.md)
- [LLM-annotation workflow](https://textdata.info/items/llm-annotation-workflow/AI-PROMPT.md)

## Repository

- [View TextData on GitHub](https://github.com/joyzhzh/textdata)