Built by Metorial, the integration platform for agentic AI.
Create a new workspace within an organization. A workspace is a logical container for document processing that can have its own configuration, document types, and access permissions.
Permanently delete a document from Affinda. This removes the document and all its extracted data from the database. This action cannot be undone.
Permanently delete a workspace and all its contents. This removes the workspace, its collections, and all documents within it. This action cannot be undone.
Retrieve Affinda's redacted PDF for a parsed document. The original document is not modified. The PDF file is returned as a Slate attachment and structured output is limited to metadata.
Search through parsed resumes or job descriptions using Affinda's Search & Match algorithm. Match resumes against job descriptions or vice versa, or search using custom criteria like job titles, skills, experience, education, and location. Returns a ranked shortlist with matching scores for each category.
List available document types (extractors) configured in your Affinda account. Document types define the AI model configuration for specific document kinds such as resumes, invoices, bank statements, passports, etc. Use this to discover available document type identifiers for uploading documents.
List all organizations accessible with the current API key. Organizations are the top-level containers that hold workspaces, document types, and team members. Use this to discover organization identifiers needed for workspace and document type operations.
Retrieve a specific document and its extracted data from Affinda. Returns document metadata, processing state, and the structured data extracted by the AI model. Use this to check parsing status or fetch results for a document uploaded with `wait: false`.
Upload a document to Affinda for AI-powered parsing and data extraction. Supports uploading via a publicly accessible URL. The document will be processed according to the workspace or collection configuration, extracting structured data such as resume fields, invoice line items, or other document-specific data points. Set **wait** to `true` to receive parsed results immediately, or `false` to get the document identifier and poll later.
Retrieve all annotations (extracted data points) for a specific document. Each annotation represents a field extracted by the AI model, such as a name, date, amount, or address.
Update multiple document annotations in a single request. Use this to programmatically correct or confirm extracted data points. Each update specifies an annotation ID and the new values to set.
Get a compatibility score between a specific resume and a specific job description. Returns an overall match score (0 to 1) along with category-level breakdowns for skills, experience, education, and more. Both the resume and job description must already be uploaded and parsed in Affinda.
List and search documents in Affinda. Filter by workspace, collection, processing state, tags, or search by filename. Supports pagination and sorting. Use this to browse uploaded documents or find specific ones.
List all workspaces within an organization. Workspaces are logical project containers where documents are processed. Optionally filter by name.
List Affinda validation results for a document. Use this to inspect validation rule outcomes after a document has been parsed and reviewed.
Update Affinda document metadata and lifecycle state. Use this to rename a document, move it to another workspace or collection, update custom identifiers, set an expiry time, archive, confirm, reject, or skip parsing.
List and manage Affinda Search & Match indexes and indexed documents. Use indexes to make parsed resumes or job descriptions searchable before calling Search & Match tools.
List, get, create, update, delete, add, and remove Affinda tags. Tags group documents and can be used as filters when listing documents.