Affinda
AI document parsing platform for resumes, invoices, receipts, annotations, collections, data points, and extraction workflows.
Supports document automation across uploaded files, parsed fields, annotations, custom data points, and organization-level workspaces and tags.
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Example Use Cases
These are example ways Snow can use Affinda when building apps with you. This list is meant to show examples, not document every possible capability. Connecting an account does not make Snow run these automatically on its own.
Tool to add a tag to multiple documents in a single operation. Use when you need to organize or categorize multiple documents by assigning them a shared tag. Tags enable efficient filtering and grouping of documents in your workspace.
Batch create multiple document annotations in a single API call. Use this action to efficiently create multiple annotations at once for documents that have been processed by Affinda. This is useful for programmatically adding structured data to documents or importing annotation data from external sources. Prerequisites: - Documents must be created first using 'Create Document' action - Obtain document identifiers from 'Create Document' or 'Get Documents' actions - Know the data point identifiers for your collection (from extractor configuration) Common use cases: - Importing annotation data from external systems - Programmatically adding structured data to documents - Creating annotations for validation or training purposes
Batch create multiple validation results for document annotations in a single API call. Use this action to efficiently record validation outcomes for multiple documents or rules at once, rather than making individual create requests for each validation result. This is particularly useful for bulk validation workflows or when validating multiple rules across many documents. Prerequisites: - Obtain document identifiers from Get Documents or Create Document actions - Get annotation IDs from Get Annotations for those documents - Define kebab-case rule slugs that identify your validation rules Common use cases: - Bulk recording of validation results across multiple documents - Validating multiple business rules on the same document - Automated validation workflows for large document batches
Batch delete multiple document annotations in a single API call. Use this action to efficiently remove multiple annotations at once rather than making individual delete requests for each annotation. Prerequisites: - Obtain annotation IDs using the 'Get Annotations' action with a document filter - Annotations must exist in documents that have been processed by Affinda Common use cases: - Removing incorrect or unwanted annotations in bulk - Cleaning up annotations after document reprocessing - Deleting specific extracted data fields programmatically
Batch update multiple document annotations in a single API call. Use this action to efficiently update parsed values or other fields across many annotations at once, rather than making individual update requests for each annotation. Prerequisites: - Obtain annotation IDs using the 'Get Annotations' action with a document filter - Annotations must exist in documents that have been processed by Affinda Common use cases: - Correcting OCR/extraction errors in bulk - Updating parsed values after manual review - Modifying annotation data programmatically
Tool to create a new API user within an organization. Use when you need to generate a new API user with authentication credentials for programmatic access to Affinda services.
Tool to create a new collection. Use after you have a valid workspace ID and want to group documents by a specific extractor within that workspace.
Tool to create a data field for a collection along with a new data point. Use when you need to add a custom field to a collection for document processing and validation.
Tool to create a custom data point for document extraction. Use when you need to define a new field that should be extracted from documents in a specific extractor. Note: This endpoint is deprecated but still functional. Data points define custom fields for extraction models.
Tool to create a custom data point choice. Use when you need to add a new choice option for a specific data point in a collection or organization. Note: This endpoint is deprecated but still functional.