> For the complete documentation index, see [llms.txt](https://docs.mindee.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mindee.com/v1/docti/docti-overview.md).
# docTI Overview
## What is docTI
docTI is an LLM based solution that enables users to create within a few minutes an API to extract the precise data and fields they need from any form of document such as transport tickets, bank statements, tax returns, etc.
By defining the fields to extract on your specific documents, users can obtain a consistent model to accurately extract all of their documents with minimal human involvement.
The Mindee docTI can extract data in any languages, from both handwritten and printed text, photos, images, and multi-page pdfs, without any training.
Just as any LLM, docTI relies mainly on the text and the context it provides to extract data needed.
docTI offers to users a simple but powerful interface to build the data model (list of fields to extract from documents).
## Using docTI
Below is a quick overview on how to tailor your document data extraction API using Mindee docTI
* [Set up your custom API](/v1/docti/set-up-your-custom-api.md).
* [Test it using the Live Interface.](/v1/platform-ui-tour/live-interface.md)
* [Edit your data model.](/v1/docti/edit-your-data-model.md)
* [Create an API key.](/v1/get-started/create-api-key.md)
* Set your custom Mindee REST API in your application code using the language of your choice.
For more in-depth information check How to build your document parsing API.
---
# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.
## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.
Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:
```
GET https://docs.mindee.com/v1/docti/docti-overview.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
