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Account and Security

Yes. Users can configure MFA by navigating to their Profile Settings (click the user icon in the top left corner) and clicking “Set up MFA”. Affinda Extract supports both email and authenticator apps.If you would like to require MFA for all users in your organisation, reach out to the Affinda team, and we can enable this security requirement.For more on Affinda Extract’s certifications and data handling, see our security & compliance overview.
Affinda Extract doesn’t limit the number of users you can add to your organization.
Affinda Extract is ISO27001:2022 certified and SOC 2 Type 2, GDPR and HIPAA compliant.

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Capabilities

Affinda Extract supports over 50 languages, including the following:
Yes, Affinda Extract supports multilingual documents.
The default page limit in Affinda Extract is 20 pages per document. If you need to increase this to fit your use case, get in contact with the Affinda team.
All data exports include a rawText field containing the full, unstructured text extracted from the document.For every field Affinda Extract extracts, you’ll get two values:
  • raw — the value exactly as it appears on the document.
  • parsed — the value after data-type processing and text transformations (e.g., date/number normalization).
After splitting is enabled, the original multi-document file remains available as the “parent” record, and each piece of it becomes a “child” document. The parent–child relationship means you can still access the full set of pages and see which children were created. In practice, when a file is split Affinda Extract creates new files with suffixes on the filename (e.g., [filename]_1, [filename]_2).In the app, you can use the “Edit Pages” function to split or combine pages again.
Affinda Extract’s fingerprinting algorithm uses both textual and visual content to construct a representative embedding of the document’s meaning and layout. This includes not just the physical aspects (layout, text location, formatting) but also analyzes the semantic meaning of the text itself.
Affinda Extract requires you to configure a document type to extract data off your document. To do so, see Creating a New Model. You can do this quickly by letting the model intelligently suggest fields for you. Simply,
  1. Upload one document
  2. Create a new document type
  3. Select “Set up fields for me”, the model will analyse the content of your document to extract the key fields 
  4. Click “Finish configuration” and see the data extracted off your documents
  5. Upload more documents of the same type to see your data extracted
Yes, Affinda Extract can extract table data, preserving the relationship between data belonging to the same row. To extract tables, you need to first define your table field. 
  1. Navigate to a document with a table you want to extract
  2. Click “Configure fields” in the top right corner
  3. Create a new field and set the data type to Table
  4. Add the column fields you want to extract e.g. “description”, “unit” or “total”
  5. Click “Finish configuration” and reparse the document
See Groups and Tables in the configuration guide for more information. For tips on how to correct and validate table data, review the Tables Editor tutorial. 

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Configuration

Yes, Affinda Extract is completely configurable, so you can add custom fields as you like. See Field Configuration to see how to add custom fields to your document types in Affinda Extract.
Affinda Extract does not currently support creating calculated fields within the app; however, we are working towards it on our product roadmap. For the time being, Affinda Extract can support your calculated fields by automating the extraction of the source fields in a structured and usable format, so you can build calculated fields in your own systems.
Absolutely - Affinda Extract allows customers to create validation rules using a natural language description of the logic that they would like to implement:
  1. Type your rule in plain language, referencing any extracted field with @field_name.
  2. Click Generate to create the rule and view the underlying code.
The prompt can handle a broad range of validations.If you require more specific logic, Affinda Extract doesn’t support uploading custom code directly. Instead, you can:
  • Pull the extracted data via the API,
  • Run your own checks locally, and
  • Push the results back to Affinda Extract through our Create Validation Result API so the outcomes appear in the app and flag documents for review.
Affinda Extract document types are built to handle multiple layouts and templates. If the information you’re extracting follows the same schema (i.e., the same fields and structure), you don’t need a new document type for each template.However, our models perform best with simpler schemas. If the extraction schema differs significantly across templates, consider splitting them into separate document types.
By default, documents that the model doesn’t match to one of the document types linked to your workspace will remain in “For Review” as unclassified. Users can review and manually classify these documents as they like.Alternatively, users can configure their workspace so documents that are left unclassified are automatically rejected. To do this, navigate to the Workflow settings → Configure Classification and enable “Reject Documents”.

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Performance & Troubleshooting

We do not publish a universal benchmark as processing time varies by document and workload.What you can expect, in practice:
  • Simple 1 to 3 page docs typically complete in about 30 seconds end to end.
  • Medium sets, for example 5 to 20 pages or documents with many fields, often take 1 to 3 minutes.
  • Heavy docs, for example long multi page tables or poor quality scans, can take several minutes.
What drives the variance:
  • Page count.
  • Field count and complexity. A dense multi table invoice is slower than a header only form.
  • Pre processing needs. OCR on scans and automatic document splitting add time.
  • Concurrency and queue depth when you upload in bulk.
About bulk uploads and queues
If you upload many documents at once, they may enter a queue. This can add a wait before processing starts. The size of that delay depends on your concurrency, your account limits, and the current system load.Resume ParsingOur Resume Parser uses a different model type that is faster and more lightweight than our other document type models. Expected time to process a resume document is typically 2-3 seconds.
Documents uploaded to Affinda Extract might cause an error for a number of reasons. Review our Error Glossary to understand the error and how you can fix it.
If Affinda Extract models are repeatedly mixing up two of your document types in classification, there are a few steps you can take to improve performance.Firstly, ensure there are adequate examples in your model memory of both document types. Check that you have not confirmed any documents that are labelled as the wrong document type.Secondly, check that the name and description of each document type are clear and relevant. The models use these to predict classifications. Add disambiguation hints (unique keywords, fields, or layout cues) to help the model tell similar types apart.
From time to time, users may hit an unexpected error when taking action in the Affinda Extract app. If this occurs, try refreshing the page and trying again. If problems persist, get in touch with Affinda Support.

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About Us and Contact

Fill out the form here, and our team will get back to you.
Affinda specialises in enterprise AI transformations in business process automation, enabling intelligent document processing. Affinda’s AI platform, and customised solutions, automate end-to-end processes for faster, smarter operations and real productivity gains.Affinda Extract’s document AI technology combines 10+ years of IP in document reconstruction, with the latest advancements in computer vision, natural language processing and deep learning.Our technology is used by enterprises globally across a wide range of industries to automate their document processing workflows.We are headquartered in Melbourne, Australia, with a global team across Asia Pacific, North America and Europe.For more information head to our website.
Affinda Extract offers flexible and scalable pricing plans to meet businesses’ needs. For full pricing details, please head to our website pricing pages.