# Claims Evidence Packager — Photos, Invoices & Reports (`armourylabs/claims-evidence-packager`) Actor Bundles claim evidence — photos, invoices, incident reports, policy excerpts — into structured, assessor-ready packages via API. Built for insurance claims teams and loss adjusters: cut hours of manual collation per claim to a single call. - **URL**: https://apify.com/armourylabs/claims-evidence-packager.md - **Developed by:** [Christopher Smith](https://apify.com/armourylabs) (community) - **Categories:** Automation, Developer tools, Other - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $2,000.00 / 1,000 claim evidence bundles This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Claims Evidence Packager > Collate photos, invoices, incident reports and policy excerpts into a structured, assessor-ready evidence bundle — in milliseconds, not hours. --- ### What it does Insurance claims handlers spend hours manually gathering scattered documents (emails, portals, scanned PDFs) and assembling them into a coherent evidence pack for assessors. This Actor accepts a claim's metadata plus a list of document objects and returns a **fully structured evidence bundle** containing: | Section | What you get | |---|---| | **Claim metadata** | Normalised claimant, policy, and incident details | | **Document records** | Classified, date-extracted, and checksummed document entries | | **Timeline** | All documents ordered chronologically by detected date | | **Financial summary** | Per-invoice breakdown and grand total claimed (AUD) | | **Coverage check** | Cross-validates policy numbers mentioned in documents against the declared policy | | **Bundle summary** | Document-type counts, completeness flag, and any documents with validation issues | | **Integrity checksums** | SHA-256 per document — auditable chain of evidence | #### Document types recognised `photo`, `invoice`/`receipt`, `incident_report`/`police_report`, `policy_excerpt`/`policy_schedule`, `correspondence`/`email`/`letter`, `other` #### Date formats supported - ISO 8601: `2024-03-15` - Australian: `15/03/2024` - Long form: `15 March 2024` --- ### Who buys this - **Insurance claims teams** at Australian general insurers (motor, home, commercial) - **Loss adjusting firms** that receive unstructured document bundles from claimants - **Claims management software vendors** embedding evidence assembly into their workflow --- ### Local demo ```bash python3 main.py '{ "claim_id": "CL-2024-001", "claimant_name": "Jane Smith", "policy_number": "POL-99001", "incident_date": "10/03/2024", "incident_description": "Vehicle damaged in hail storm on M1 motorway.", "documents": [ { "id": "doc1", "type": "invoice", "content_text": "Invoice for panel repairs $3,450.00. Date: 2024-03-18. Policy POL-99001.", "source": "email", "filename": "panel_repairs_invoice.pdf" }, { "id": "doc2", "type": "photo", "content_text": "Damage photograph taken 12 March 2024 at Goulburn St carpark.", "source": "portal", "filename": "damage_front.jpg" }, { "id": "doc3", "type": "incident_report", "content_text": "Police event number E12345. Incident on 10/03/2024. POL-99001 holder present.", "source": "portal", "filename": "police_report.pdf" }, { "id": "doc4", "type": "policy_excerpt", "content_text": "Policy schedule POL-99001. Comprehensive motor cover. Excess $750.", "source": "portal", "filename": "policy_schedule.pdf" } ] }' ```` #### Run tests ```bash pytest tests/ -v ``` *** ### Suggested Apify pricing | Tier | Volume | Price | |---|---|---| | **Pay-per-claim** | Any | **$8 per claim bundle** | | **Starter** | Up to 100 claims/month | **$350/month** | | **Professional** | Up to 500 claims/month | **$1,200/month** | | **Enterprise** | Unlimited + SLA | Custom quote | Loss adjusters processing 200+ claims/month break even versus manual collation (~2 hours/claim at $60/hr) within the first week. *** ### Input schema See `.actor/input_schema.json` for full field definitions. ### Output shape (abbreviated) ```json { "bundle_id": "A3F1...", "generated_at": "2024-03-20T04:12:00Z", "claim_metadata": { ... }, "bundle_summary": { "total_documents": 4, "documents_by_type": { "invoice": 1, "photo": 1, "incident_report": 1, "policy_excerpt": 1 }, "bundle_complete": true, "documents_with_issues": [] }, "timeline": [ ... ], "financial_summary": { "invoice_count": 1, "grand_total_claimed_aud": 3450.00 }, "coverage_check": { "declared_policy_number": "POL-99001", "policy_numbers_in_documents": ["POL-99001"], "consistent": true }, "documents": [ ... ], "errors": [] } ``` # Actor input Schema ## `claim_id` (type: `string`): Unique identifier for this claim (e.g. CL-2024-001). Required. ## `claimant_name` (type: `string`): Full name of the claimant. ## `policy_number` (type: `string`): Insurance policy number (e.g. POL-99001). Used to cross-validate references found in document texts. ## `incident_date` (type: `string`): Date the incident occurred. Accepts ISO format (2024-03-10), Australian format (10/03/2024), or long form (10 March 2024). ## `incident_description` (type: `string`): Brief narrative describing the incident (e.g. 'Vehicle damaged in hail storm'). ## `documents` (type: `array`): List of document objects to include in the evidence bundle. Each document must have an id, type, and content\_text. ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("armourylabs/claims-evidence-packager").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("armourylabs/claims-evidence-packager").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call armourylabs/claims-evidence-packager --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=armourylabs/claims-evidence-packager", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Claims Evidence Packager — Photos, Invoices & Reports", "description": "Bundles claim evidence — photos, invoices, incident reports, policy excerpts — into structured, assessor-ready packages via API. Built for insurance claims teams and loss adjusters: cut hours of manual collation per claim to a single call.", "version": "0.1", "x-build-id": "IVYo2b9a2IasLTnAy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/armourylabs~claims-evidence-packager/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-armourylabs-claims-evidence-packager", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/armourylabs~claims-evidence-packager/runs": { "post": { "operationId": "runs-sync-armourylabs-claims-evidence-packager", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/armourylabs~claims-evidence-packager/run-sync": { "post": { "operationId": "run-sync-armourylabs-claims-evidence-packager", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "claim_id", "documents" ], "properties": { "claim_id": { "title": "Claim ID", "type": "string", "description": "Unique identifier for this claim (e.g. CL-2024-001). Required." }, "claimant_name": { "title": "Claimant Name", "type": "string", "description": "Full name of the claimant." }, "policy_number": { "title": "Policy Number", "type": "string", "description": "Insurance policy number (e.g. POL-99001). Used to cross-validate references found in document texts." }, "incident_date": { "title": "Incident Date", "type": "string", "description": "Date the incident occurred. Accepts ISO format (2024-03-10), Australian format (10/03/2024), or long form (10 March 2024)." }, "incident_description": { "title": "Incident Description", "type": "string", "description": "Brief narrative describing the incident (e.g. 'Vehicle damaged in hail storm')." }, "documents": { "title": "Documents", "type": "array", "description": "List of document objects to include in the evidence bundle. Each document must have an id, type, and content_text.", "items": { "type": "object", "properties": { "id": { "title": "Document ID", "description": "Unique identifier for this document within the claim (e.g. 'doc1', 'invoice_march').", "type": "string" }, "type": { "title": "Document Type", "description": "Type of document. Accepted values: photo, image, invoice, receipt, tax_invoice, incident_report, report, police_report, policy, policy_excerpt, policy_schedule, correspondence, email, letter. Unknown values default to 'other'.", "type": "string" }, "content_text": { "title": "Content Text", "description": "Full text content of the document (OCR output, email body, PDF extract, etc.). Used for date detection, amount extraction, and policy number cross-referencing.", "type": "string" }, "source": { "title": "Source", "description": "Where the document was obtained (e.g. 'email', 'portal', 'fax', 'upload').", "type": "string" }, "filename": { "title": "Filename", "description": "Original filename of the document (e.g. 'invoice_march.pdf').", "type": "string" }, "date": { "title": "Document Date (hint)", "description": "Optional date hint for the document. If not supplied, a date is extracted from content_text automatically.", "type": "string" } }, "required": [ "id", "type", "content_text" ] } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```