Azure OCR

The Azure OCR app wraps two Azure AI services behind a single Prisme.ai app: Azure Computer Vision for lightweight image OCR (Read, Caption, Tags, Objects, People) and Azure Document Intelligence for structured extraction of documents (layouts, invoices, receipts, ID documents, …).

Computer Vision

Fast OCR and visual analysis for images via a single synchronous call

Document Intelligence

Async, structured extraction for PDFs and complex layouts with prebuilt models

Prerequisites

An Azure subscription with access to Azure AI services
A Computer Vision (or Multi-Service Cognitive) resource and its endpoint + API key
A Document Intelligence resource and its endpoint + API key

You can configure only one of the two services — each automation only requires the config of the service it targets.

Installation

Go to Apps in your workspace
Search for Azure OCR and install it
Open the app instance configuration and fill in the required fields

Configuration

Field	Description
Computer Vision — Endpoint	Azure endpoint hostname, e.g. `az-aismsa-xxx.cognitiveservices.azure.com`
Computer Vision — API Key	API key, stored as the workspace secret `computervisionApiKey`
Document Intelligence — Endpoint	Azure endpoint hostname, e.g. `az-di-xxx.cognitiveservices.azure.com`
Document Intelligence — API Key	API key, stored as the workspace secret `documentIntelligenceApiKey`

Endpoints are stored as hostnames only — the app automatically strips https:// and trailing slashes, so both https://xxx.cognitiveservices.azure.com/ and xxx.cognitiveservices.azure.com work.

Available Instructions

analyzeImage (Computer Vision)

Send an image URL to Azure Computer Vision and return the analysis result (OCR and optional visual features). This call is synchronous.

Argument	Description
`source`*	Public URL of the image to analyze
`features`	Comma-separated features (default `Read`). Accepted values: `Read`, `Caption`, `Tags`, `Objects`, `People`
`language`	Language hint (default `en`, e.g. `fr`)

Uses the Image Analysis API version 2024-02-01.

- Azure OCR.analyzeImage:
    source: https://example.com/receipt.jpg
    features: Read,Caption,Tags
    language: fr
    output: result

Returns the raw Azure response body (readResult, captionResult, tagsResult, …).

analyzeDocument (Document Intelligence)

Send a document (URL or base64) to Azure Document Intelligence, poll for the result, and return either a simplified or raw extraction. This automation handles the async submit-and-poll cycle internally (2s interval, 60s timeout).

Argument	Description
`source`*	Document URL or base64 content
`sourceType`	`url` (default) or `base64`
`model`	Document Intelligence model (default `prebuilt-layout`). See list below
`pages`	Pages to analyze, e.g. `1-3,5,7-9`
`locale`	Locale hint, e.g. `fr-FR`
`outputContentFormat`	`text` (default) or `markdown`
`outputFormat`	`simple` (default, post-processed) or `raw` (full Azure response)

Available prebuilt models:

Model	Use case
`prebuilt-read`	Pure text extraction (fastest, lightweight)
`prebuilt-layout`	Text + tables + structure (default)
`prebuilt-invoice`	Structured invoice fields
`prebuilt-receipt`	Structured receipt fields
`prebuilt-idDocument`	Passports, IDs, driver’s licences
`prebuilt-businessCard`	Business card fields

Uses the Document Intelligence API version 2024-11-30.

URL source

- Azure OCR.analyzeDocument:
    source: https://example.com/invoice.pdf
    model: prebuilt-invoice
    locale: fr-FR
    outputContentFormat: markdown
    output: invoice

Base64 source

- Azure OCR.analyzeDocument:
    source: '{{pdf_base64}}'
    sourceType: base64
    model: prebuilt-layout
    pages: 1-3
    output: layout

Raw output

Set outputFormat: raw to bypass the internal simplification and receive the full analyzeResult payload from Azure (pages, tables, key-value pairs, styles, …).

- Azure OCR.analyzeDocument:
    source: '{{document_url}}'
    model: prebuilt-layout
    outputFormat: raw
    output: raw_result

Error Handling

Both instructions emit an error event and return a structured error payload instead of raising. The payload shape is:

{
  "error": "ConfigurationError | ValidationError | NetworkError | AzureError | Unauthorized | Forbidden | NotFound | RateLimited | ServerError | ProcessingFailed | Timeout",
  "message": "Human-readable explanation",
  "details": {
    "service": "computervision | documentIntelligence",
    "automation": "analyzeImage | analyzeDocument",
    "status": 401,
    "body": {}
  }
}

Error	Typical cause
`ConfigurationError`	Missing endpoint or API key in the app config
`ValidationError`	`source` argument is empty
`NetworkError`	Endpoint unreachable — check hostname format (no scheme, no path)
`Unauthorized`	Invalid or revoked API key
`Forbidden`	The resource exists but the key lacks access (Computer Vision only)
`NotFound`	`prebuilt-<model>` does not exist, or the Computer Vision resource is missing
`RateLimited`	Azure throttling — retry with back-off
`ServerError`	Azure 5xx
`ProcessingFailed`	Document Intelligence could not process the document (corrupted, password-protected, unsupported format)
`Timeout`	Document Intelligence polling exceeded 60s — try `prebuilt-read` or fewer pages

Listening for Errors

Because both instructions emit an error event on failure, you can globally monitor Azure OCR issues from another automation:

slug: onAzureOcrError
when:
  events:
    - error
do:
  - conditions:
      '{{payload.details.service}} == "documentIntelligence" || {{payload.details.service}} == "computervision"':
        - comment: Forward to monitoring
        - fetch:
            url: '{{config.monitoringWebhook}}'
            method: POST
            body: '{{payload}}'

Example Use Cases

Invoice OCR
ID Verification
Image OCR
Markdown Layout

Extract structured invoice data from a PDF sent by email.

- Azure OCR.analyzeDocument:
    source: '{{attachment.url}}'
    model: prebuilt-invoice
    locale: fr-FR
    output: invoice
- conditions:
    '{{invoice.error}}':
      - emit:
          event: invoice.ocr.failed
          payload: '{{invoice}}'
    default:
      - emit:
          event: invoice.parsed
          payload: '{{invoice}}'

Run KYC-style extraction on a passport scan.

- Azure OCR.analyzeDocument:
    source: '{{scan_base64}}'
    sourceType: base64
    model: prebuilt-idDocument
    output: id

Quick text extraction from a receipt photo.

- Azure OCR.analyzeImage:
    source: '{{photo_url}}'
    features: Read
    language: fr
    output: ocr

Get a markdown-formatted rendering of a multi-page document for LLM ingestion.

- Azure OCR.analyzeDocument:
    source: '{{doc_url}}'
    model: prebuilt-layout
    outputContentFormat: markdown
    outputFormat: simple
    output: layout

Best Practices

Hostname only — always strip https:// and the trailing slash from endpoints to avoid NetworkError.
Pick the right model — prebuilt-read is ~3× faster than prebuilt-layout; use layout only when tables or structure matter.
Prefer url over base64 for large documents — base64 uploads go through the Prisme.ai runtime and inflate the request size by ~33%.
Handle the 60s timeout — for long PDFs, either reduce pages or split the document upstream.
Use simple output for LLM pipelines (flattened text/markdown) and raw when you need Azure’s full structured result (bounding boxes, tables, key-value pairs).

External Resources

Azure Computer Vision

Image Analysis 4.0 reference

Azure Document Intelligence

Document Intelligence overview and prebuilt models

Prebuilt Models

Full list of prebuilt and custom models

API Keys & Endpoints

Create a Multi-Service Cognitive resource

Integration Overview

Apps Marketplace

Computer Vision

Document Intelligence

Prerequisites

Installation

Configuration

Available Instructions

analyzeImage (Computer Vision)

analyzeDocument (Document Intelligence)

URL source

Base64 source

Raw output

Error Handling

Listening for Errors

Example Use Cases

Best Practices

External Resources

Azure Computer Vision

Azure Document Intelligence

Prebuilt Models

API Keys & Endpoints

Integration Overview

Apps Marketplace

Computer Vision

Document Intelligence

​Prerequisites

​Installation

​Configuration

​Available Instructions

​analyzeImage (Computer Vision)

​analyzeDocument (Document Intelligence)

​URL source

​Base64 source

​Raw output

​Error Handling

​Listening for Errors

​Example Use Cases

​Best Practices

​External Resources

Azure Computer Vision

Azure Document Intelligence

Prebuilt Models

API Keys & Endpoints

Prerequisites

Installation

Configuration

Available Instructions

analyzeImage (Computer Vision)

analyzeDocument (Document Intelligence)

URL source

Base64 source

Raw output

Error Handling

Listening for Errors

Example Use Cases

Best Practices

External Resources