# Affinda AI integration on Definable

> Affinda provides an AI-powered document processing platform that automates data extraction from various document types.

## What this connects

Affinda provides an AI-powered document processing platform that automates data extraction from various document types.

Vendor: https://www.affinda.com/

## Tools available

**105** tools available. First 12:

- `AFFINDA_ADD_TAG_TO_DOCUMENTS` — Add Tag to Documents — 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.
- `AFFINDA_BATCH_UPDATE_ANNOTATIONS` — Batch Update Annotations — 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
- `AFFINDA_CREATE_API_USER` — Create API User — 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.
- `AFFINDA_CREATE_BATCH_ANNOTATIONS` — Batch Create Annotations — 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
- `AFFINDA_CREATE_COLLECTION` — Create Collection — 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.
- `AFFINDA_CREATE_DATA_FIELD_FOR_COLLECTION` — Create Data Field For Collection — 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.
- `AFFINDA_CREATE_DATA_POINT` — Create Data Point — 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.
- `AFFINDA_CREATE_DATA_POINT_CHOICE` — Create Data Point Choice — 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.
- `AFFINDA_CREATE_DATA_SOURCE` — Create Data Source — Tool to create a custom mapping data source. Use when you need to set up a new data source for mapping AI-extracted values to your database records.
- `AFFINDA_CREATE_DATA_SOURCE_VALUE` — Create Data Source Value — Tool to add a new value to a mapping data source. Use when you need to add entries to a data source for mapping or validation purposes. The created value can then be referenced in document extraction and mapping workflows.
- `AFFINDA_CREATE_DOCUMENT` — Create Document — Upload a document to Affinda for parsing and data extraction. Use this action when you need to: - Parse resumes/CVs to extract candidate information - Process invoices to extract line items, amounts, and vendor details - Extract data from any supported document type (PDF, DOCX, images) You can upload either a file directly or provide a publicly accessible URL. The document will be processed by Affinda's AI extraction engine. Prerequisites: - For collection-based uploads: Get collection ID from get_collections action - For workspace-specific uploads: Get workspace ID from get_workspaces action
- `AFFINDA_CREATE_DOCUMENT_TYPE` — Create Document Type — Tool to create a new document type in the specified organization. Use when you need to define a new category of documents for processing. Document types allow you to organize and categorize documents within an organization.

## Auth

Auth schemes: `API_KEY`.

## How agents use Affinda

Inside a Definable workflow, Affinda is one of the tools the **Distributor specialist** can call. Example coordination patterns:

- **Researcher → Affinda** — the Researcher (GPT-5.5) pulls context from Affinda (records, threads, documents), synthesises findings, and briefs the rest of the team.
- **Writer → Distributor → Affinda** — the Writer (Claude Opus 4.7) drafts copy in brand voice, the Verifier passes it, then the Distributor writes the result into Affinda (create record, post message, draft email).
- **Designer / Engineer → Distributor → Affinda** — the Designer ships an asset or the Engineer ships a code change, the Distributor delivers it via Affinda (attach file, open PR comment, post status).

The Verifier checks every Affinda call. On rate limit, schema drift, or auth refresh it self-heals and retries — the workflow completes without manual intervention.

## Categories

- artificial intelligence — https://definable.ai/apps/category/artificial-intelligence/
- ai document extraction — https://definable.ai/apps/category/ai-document-extraction/

## Related

- HTML page: https://definable.ai/apps/affinda/
- Same category (artificial intelligence): https://definable.ai/apps/category/artificial-intelligence/
- All integrations: https://definable.ai/apps/
- Workflow (multi-agent loop): https://definable.ai/workflow/
- Apps llms.txt index: https://definable.ai/llms-apps.txt