Invoice data
Extract suppliers, dates, line items and amounts. Check relationships and totals before sending data to the destination system.
Use cases / Data and knowledge
Information extraction
Extract information with AI. Turn it into data your business can use.
Turn contracts, emails and documents into names, dates, amounts and references your systems can use. Define the fields and use an AI model to find them in unstructured content.
With QDivZero, you can deploy language models to automate data extraction through an API. Your application prepares content, validates results and connects them with your CRM, ERP or workflow.
From content to data
Define the fields. Let the model find them.
Turn scattered information into fields your application can use. Define an output structure and validate results.
Contract information
Retrieve parties, deadlines and terms from contracts. Link each field to its original passage to support review.
Emails and requests
Turn messages into structured requests. Identify your workflow’s fields and flag missing information before proceeding.
Document processing
Use a common schema for files with different formats. Validate fields and retain references to the document each value comes from.
Build it with QDivZero
Define the fields. Get data you can use.
Define fields and output format, then send content to a compatible model. Your application checks values, flags missing data and connects results to the destination system.
Your application flow
Content
Prepare document text or images.
Fields
Define required data and the output format.
Extraction
The model identifies values in the content.
Validation
Your application checks fields and their structure.
Integration
Send validated data to your system or process.
Open-weight / Hugging Face
You can start with…
Compare language models with real documents and your required output schema. Assess accuracy by field, available context and support for structured output; scanned pages may need a vision model. Test complete and partial outputs with the same schema. Assess fidelity to original data and the ability to indicate missing fields, especially before connecting extraction to processes that store information.
Text and vision
Qwen3.8-27B
For conversation, code, and tasks combining text, images, and your own context.
View model on Hugging FaceText and vision
GLM-5.3 Flash
Combine conversation, visual understanding, and work with tools.
View model on Hugging FaceMultimodal reasoning
DeepSeek V4.1 Flash
Explore reasoning and understanding of text and images in multi-step tasks.
View model on Hugging FaceInformation extraction
Information extraction: frequently asked questions
What is AI information extraction?
AI information extraction identifies specific data in text or documents and returns it in a defined structure. Extract names, dates, amounts, and references for applications, databases, or business processes.
How do I extract document data with an LLM?
Send the content and describe the fields you need. Define an output format and include examples where useful. A compatible LLM can identify values; your application validates the result before storage or delivery to another system.
Can I automatically extract invoice and contract data?
Yes. Define fields such as supplier, date, amount, parties, or deadlines and process documents with compatible models. For scanned pages or data that depends on layout, prepare images and use a multimodal model.
How do I convert unstructured text into JSON?
Describe the keys, types, and JSON structure your application needs. Use a schema where the model and runtime support structured outputs. Check JSON validity and whether values match the source content.
What is the difference between text and information extraction?
Text extraction recovers document words. Information extraction selects specific data and assigns meaning, such as a due date or total amount. Combine both stages to turn documents into records your system can use.
Can I integrate data extraction through an API?
Yes. Deploy a compatible model on QDivZero and connect your application to its endpoint. Your workflow prepares documents, sends requests, validates fields, and delivers results to the destination system. Organize batches according to deployed capacity.
How do I validate data extracted by AI?
Check that the output follows your schema and validate types, dates, amounts and required fields. Compare values with the source document and define cases that need human review. Measure accuracy for each field with representative examples before automating delivery to other systems.
Can I automate data extraction for a CRM or ERP?
Yes. Your integration can prepare documents or messages, request extraction from the model and transform validated fields into the format your CRM or ERP expects. QDivZero serves the model; your application manages business rules, error handling and the connection to the destination system.
Ready to turn documents into useful data?
Automate information extraction from contracts, emails and documents with AI models. Define your output structure, deploy a compatible model in QDivZero and connect validated data with your company’s systems.