Mindee OCR API
★ Only Publicly Available OpenAPI DocumentAI/MLVisionbearer12 EndpointsREST
For Agents
Submit a document image or PDF and receive structured field extractions for invoices, receipts, IDs, and custom forms. Supports synchronous predictions for fast paths and asynchronous queues for batch processing.
Use for: I need to extract line items and totals from a supplier invoice PDF, Parse the merchant, date, and amount from a scanned receipt, Submit a passport scan and get the name, MRZ, and expiry date back, Check whether a queued async prediction job has finished
Not supported: Does not handle accounting ledgers, tax filing, or document storage — use for OCR field extraction from documents only.
Jentic publishes the only available OpenAPI specification for Mindee OCR API, keeping it validated and agent-ready. Mindee is a document processing and OCR platform that extracts structured fields from invoices, receipts, identity documents, passports, and custom forms. The API exposes synchronous and asynchronous prediction endpoints, queue polling for long-running jobs, document feedback for retraining, and workflow execution for multi-step document pipelines. Predictions return parsed key-value pairs with confidence scores so agents can route documents without manual review.
Install Jentic One Beta
Connect the Mindee OCR API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Mindee OCR API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Mindee OCR API.
Submit invoices and receipts to /v1/products/{account}/{product}/{version}/predict and receive parsed line items, totals, vendor, and tax fields
Queue large document batches via predict_async and poll job status until extraction completes
Execute multi-step document workflows with /v1/workflows/{workflow_id}/executions to chain classification, extraction, and validation
Send corrected field values back through PUT /v1/documents/{document_id}/feedback to improve future model accuracy
Discover available custom and off-the-shelf products with GET /v1/customers/self/products
Retrieve a parsed document by its document_id to fetch all stored predictions and metadata
Use Cases
Patterns agents use Mindee OCR API for, with concrete tasks.
★ Accounts Payable Invoice Capture
Automate invoice intake by submitting supplier PDFs to the Mindee invoice product and receiving structured supplier name, invoice number, line items, tax, and totals. Agents can post extracted fields directly into accounting systems without manual keying. Synchronous predictions return in seconds for low-volume flows; asynchronous queues handle thousands of invoices per hour.
Submit invoice.pdf to /v1/products/mindee/invoices/v4/predict and return supplier_name, invoice_number, total_amount, and line_items as JSON
Receipt Expense Reporting
Extract merchant, date, total, and tax from receipt photos for expense management apps. The receipt product handles thermal prints, photos, and PDFs in over 60 languages, returning parsed fields with confidence scores so agents can flag low-confidence values for human review.
Send receipt.jpg to the receipt product predict endpoint and create an expense entry with merchant, date, and total_amount fields
ID and Passport Verification
Capture name, document number, date of birth, and expiry from passports and national IDs as part of KYC onboarding. Mindee parses MRZ codes and visual zones in a single call, returning structured fields plus crop coordinates so agents can build verification flows without bespoke ML.
Submit passport.jpg to the passport product and verify that the parsed expiry_date is in the future and the surname matches the user record
Agent-Driven Document Workflows
AI agents discover the Mindee API through Jentic by intent (parse a receipt, extract invoice fields). Jentic returns the predict endpoint with its input schema, the agent uploads the document, and parsed fields stream back. The Mindee bearer token stays in the Jentic vault so the agent never sees the raw secret.
Search Jentic for 'extract invoice data', load the Mindee predict schema, and execute against three queued invoice PDFs
Key Endpoints
12 endpoints — jentic publishes the only available openapi specification for mindee ocr api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/v1/products/{account}/{product}/{version}/predict
Synchronous document prediction
POST
/v1/products/{account}/{product}/{version}/predict_async
Queue an asynchronous prediction
GET
/v1/products/{account}/{product}/{version}/documents/queue/{job_id}
Poll async job status
GET
/v1/products/{account}/{product}/{version}/documents/{document_id}
Retrieve a parsed document
PUT
/v1/documents/{document_id}/feedback
Send field-level correction feedback
POST
/v1/workflows/{workflow_id}/executions
Execute a document workflow
POST
/v1/products/{account}/{product}/{version}/predict
Synchronous document prediction
POST
/v1/products/{account}/{product}/{version}/predict_async
Queue an asynchronous prediction
GET
/v1/products/{account}/{product}/{version}/documents/queue/{job_id}
Poll async job status
GET
/v1/products/{account}/{product}/{version}/documents/{document_id}
Retrieve a parsed document
PUT
/v1/documents/{document_id}/feedback
Send field-level correction feedback
POST
/v1/workflows/{workflow_id}/executions
Execute a document workflow
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
The Mindee bearer token is stored encrypted in the Jentic vault. Agents call the predict endpoints through scoped Jentic execution requests; the raw token never enters the agent's context window or logs.
Intent-based discovery
Agents search Jentic by intent (e.g. 'extract invoice data', 'parse a receipt') and Jentic returns the matching Mindee predict operation with its input schema, so the agent calls the right product slug without browsing Mindee documentation.
Time to first call
Direct Mindee integration: 1-2 days to wire bearer auth, choose the right product version, and handle async queue polling. Through Jentic: under 30 minutes — search, load schema, execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Mindee OCR API through Jentic.
Why is there no official OpenAPI spec for Mindee OCR API?
Mindee does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Mindee OCR API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the Mindee OCR API use?
Mindee OCR API uses HTTP bearer token authentication. The token is sent in the Authorization header as `Bearer <token>`. When called through Jentic, the bearer token is stored in the Jentic vault and injected at execution time so the agent never sees the raw secret.
Can I extract line items from invoices with the Mindee OCR API?
Yes. Submit the invoice file to POST /v1/products/{account}/{product}/{version}/predict using the invoices product slug and Mindee returns parsed line_items, supplier_name, invoice_number, total_amount, and tax fields with per-field confidence scores.
How do I handle large document batches without timing out?
Use POST /v1/products/{account}/{product}/{version}/predict_async to queue the document, then poll GET /v1/products/{account}/{product}/{version}/documents/queue/{job_id} until the job_id transitions to a completed state. The completed response contains the parsed prediction.
How do I improve extraction accuracy on documents Mindee gets wrong?
Send corrected field values to PUT /v1/documents/{document_id}/feedback. Mindee uses these corrections to retrain the underlying models for custom products and surface the corrected values on subsequent predictions of the same document.
How do I extract receipt data through Jentic?
Run `pip install jentic`, then search Jentic for 'parse a receipt'. Jentic returns the Mindee predict operation with its input schema. Load the schema, supply the receipt file as the document field, and execute. Parsed merchant, date, and total fields return as JSON.
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