> For the complete documentation index, see [llms.txt](https://docs.uptiq.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.uptiq.ai/document-ai/get-started/document-ai-1.md).
# Document AI
UPTIQ Document AI is the document-processing layer behind UPTIQ Solutions. It turns raw files into structured, reviewable, and actionable data. Teams use it to classify incoming documents, extract fields, detect fraud signals, generate outputs, measure accuracy, and send results to downstream systems.
Document AI supports document-heavy workflows across commercial lending, SBA, CRE, consumer lending, equipment finance, and digital banking. It combines OCR, layout analysis, LLM-based reasoning, configurable rules, and validation where precision matters.
### Supported Document Types
Each type has a dedicated extraction schema. Upload a supported document and Document AI returns structured fields.
{% hint style="info" %}
**At a glance:** Document AI helps teams move from raw documents to trusted outputs with a workflow built around classification, extraction, validation, review, and delivery.
{% endhint %}
### What Document AI does
{% columns %}
{% column %}
* **Understand the file** — identify it with [Document Classification](/document-ai/guides-1/document-classification.md).
* **Turn content into data** — extract fields, tables, and layout with [Document Extraction](/document-ai/guides-1/document-extraction.md).
{% endcolumn %}
{% column %}
* **Produce outputs** — review and download generated results with [Document Generation](/document-ai/guides-1/document-generation.md).
* **Screen for risk** — apply configurable checks with [Fraud Detection](/document-ai/guides-1/fraud-detection.md).
{% endcolumn %}
{% endcolumns %}
### How the workflow fits together
1. **Ingest documents** in the application or through an integrated pipeline.
2. **Classify** each file when the type is unknown or mixed.
3. **Extract** structured data from the confirmed document type.
4. **Validate** results with fraud rules, human review, or test coverage.
5. **Deliver** data and outputs to operations teams or connected systems. This flow lets teams reduce manual review without losing control over accuracy, routing, or auditability.
> Ingest → Classify → Extract → Validate → Deliver.
### Teams
{% tabs %}
{% tab title="Operations" %}
Organize, process, and review documents.
{% endtab %}
{% tab title="Risk and underwriting" %}
Validate data, flag risk, and prepare financial outputs.
{% endtab %}
{% tab title="Engineering" %}
Connect results to internal systems and workflows.
{% endtab %}
{% endtabs %}
### Frequently asked questions
What product capabilities does Document AI include?
Document AI supports classification, extraction, fraud screening, document generation, accuracy testing, and webhook-based delivery. It gives teams one workflow for turning raw documents into structured outputs and operational actions.
Can Document AI classify documents before extraction?
Yes. [Document Classification](/document-ai/guides-1/document-classification.md) identifies document type and category before extraction. Teams use it to route unknown files, mixed files, and unlabeled inboxes into the right extraction flow.
What kinds of documents can Document AI handle?
Document AI uses a shared registry of 115 document types across classification and extraction. Coverage includes financial statements, tax forms, bank statements, credit reports, identity documents, real estate documents, and more. See [Document Types](/document-ai/guides-1/document-types.md).
Can it process batches, ZIP files, or mixed PDFs?
Yes. Document AI supports single documents, batch uploads, ZIP archives, and multi-document PDFs. Classification can segment longer PDFs before extraction, and extraction can process multi-document files as part of the workflow.
Does Document AI only extract text?
No. [Document Extraction](/document-ai/guides-1/document-extraction.md) returns structured fields, tables, and layout data. That gives teams both machine-readable outputs and reviewable context against the source document.
Can teams review and correct extraction results?
Yes. Extracted values can be reviewed against the source document and corrected. Some document types also support Chart of Accounts review for balance sheets, profit and loss statements, and property operating statements.
Does Document AI support fraud detection?
Yes. [Fraud Detection](/document-ai/guides-1/fraud-detection.md) runs pre-OCR visual checks and post-extraction rule-based checks. Teams can use recommended templates, natural-language rules, and custom logic to score document risk.
Can it generate finished reports or outputs?
Yes. [Document Generation](/document-ai/guides-1/document-generation.md) turns structured section data into downloadable DOCX reports. It is designed for outputs such as credit memos and financial summaries.
---
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