Endpoints

All endpoints are authenticated via Authorization: Bearer <key>. Responses are JSON unless otherwise noted.

Method	Path	Description
`POST`	`/api/v1/documents`	Upload a file, base64, or URL for processing (supports webhook_url)
`GET`	`/api/v1/documents/jobs/{document_id}`	Retrieve full result by document ID
`GET`	`/api/v1/documents/{id}/summary`	48 summary metrics (bank statements)
`GET`	`/api/v1/documents/{id}/custom-export`	Download org-configured Excel export
`GET`	`/api/v1/documents/{id}/export`	Schema-based Excel export (audited_financial_statement, credit report, SLIK)
`GET`	`/api/v1/documents`	List documents with optional filters
`DELETE`	`/api/v1/documents/{id}`	Soft-delete a document
`POST`	`/api/v1/verify`	Cross-document verification across 2–50 processed documents
`POST`	`/api/v1/batch`	Create a batch job or process from URL
`POST`	`/api/v1/batch/upload`	Batch upload multiple files as multipart form-data
`GET`	`/api/v1/batch/{batch_id}`	Check batch status and progress
`GET`	`/api/v1/batch/{batch_id}/results`	Get full results for all batch documents
`POST`	`/api/v1/documents/merge`	Merge multiple files into one document for processing
`PUT`	`/api/v1/documents/{id}/transactions`	Edit transactions on a processed document
`POST`	`/api/v1/documents/{id}/transactions/revert`	Restore original extracted transactions
`POST`	`/api/v1/documents/{id}/transactions/revalidate`	Re-run validation and metrics after edits

POST/api/v1/documents

body parameters

Field	Type	Description
`file`	file	Multipart file upload (PDF, PNG, JPG; maximum 100 MB).
`file_base64`	string	Base64-encoded file content (data URI prefix accepted).
`file_url`	string	Public or S3 presigned URL to fetch the file from.
`filename`	string	Required with file_base64; optional with file_url; inferred for multipart uploads.
`document_type`required	string	Document type (see table above).
`password`	string	PDF password, if encrypted.
`webhook_url`	string	URL that receives a POST when processing completes or fails.
`folder_id`	string	Assign the document to a folder.
`applicant_id`	string	Link the document to an applicant record.
`schema_definition`	object	Custom extraction schema (JSON) for enterprise custom document types.

One input per request

Provide exactly one of file, file_base64, or file_url.

Option A: File upload (multipart)

Python

result = client.process(
  "statement.pdf",
  "bank_statement",
  wait=True,            # Wait for completion (default: True)
  poll_interval=2,      # Seconds between status checks
  timeout=600,          # Max wait time in seconds
  password=None,        # PDF password if encrypted
  show_progress=True    # Show progress spinner
)

Option B: Base64 JSON upload

Send file contents as a base64 string in a JSON body. Useful when the file is already in memory (browser FileReader, database, another API). Data URI prefix is accepted and stripped automatically.

Python

import base64

with open("invoice.pdf", "rb") as f:
  b64 = base64.b64encode(f.read()).decode()

result = client.process_base64(b64, "invoice.pdf", "sales_invoice")

Option C: URL (S3 presigned, public URL)

Pass a file_url and Kita will fetch the file server-side. Works with S3 presigned URLs, GCS signed URLs, or any publicly accessible link. Pair with webhook_url for a fully async fire-and-forget flow.

Python

result = client.process_url(
  "https://my-bucket.s3.amazonaws.com/docs/statement.pdf?X-Amz-...",
  "bank_statement"
)

GET/api/v1/documents/jobs/{document_id}

Python

result = client.get_result(12345)
print(result.metadata)
result.save_json("output.json")