Reported impact
Business outcome
Lion Parcel accelerated Delivery Order processing, improved finance-data accuracy, and created a centralized digital repository for a previously manual workflow.
- Cost Reduction
- Productivity Improvement
- Risk Reduction
Alibaba CloudLogisticsDocument ProcessingAI and Machine LearningData AnalyticsGenerative AI / LLMCost ReductionProductivity ImprovementRisk ReductionUndated Alibaba CloudAC#ff6a00LogisticsIndonesiaLion Parcel needed to eliminate manual delivery-order transcription in finance, reduce document-entry errors, centralize document traceability, and convert growing volumes of paper logistics records into structured…15,000+ delivery couriers5Document ProcessingAlibaba Cloud Model Studio · Qwen-VL-Plus Model0 0000-00-00 5
Lion Parcel
Document Processing
Lion Parcel needed to eliminate manual delivery-order transcription in finance, reduce document-entry errors, centralize document traceability, and convert growing volumes of paper logistics records into structured digital data for downstream financial reporting.
15,000+ delivery couriers
3,000+ land fleets
350+ aircraft
7,000+ agents
Solution
Lion Parcel implemented an OCR-driven document-processing pipeline on Alibaba Cloud to automate Finance handling of Delivery Orders. A client application sends parcel-label and delivery-order images to Alibaba Cloud Model Studio, where Qwen-VL-Plus Model extracts printed and handwritten content and returns structured JSON fields. That output is then passed into a backend processing layer that validates, normalizes, deduplicates, and applies business rules before storing the result in a database and making it available to downstream Finance workflows. The design intentionally blends automation with human validation so staff can review uncertain fields while still eliminating most repetitive data-entry work. Because the company operates at logistics scale—covering 99% of Indonesia and more than 50 countries with thousands of couriers and fleets—the shift from spreadsheets and hardcopy files to AI-assisted extraction gives Lion Parcel a more scalable, traceable, and accurate finance-document process.
Data flow
Parcel-label and delivery-order images are uploaded to Model Studio, Qwen-VL-Plus extracts JSON fields, backend services validate and normalize the output, and approved records are stored for downstream finance reporting.
Solution architecture
- Serving
- Alibaba Cloud Model Studio Receives document images and invokes the OCR model used by the finance workflow.
- Qwen-VL-Plus Model Extracts structured fields from printed and handwritten delivery-order documents.
Architecture clues
- Backend processing validates and normalizes extracted fields before storage
- Results are exported into standardized finance-reporting formats
- The OCR pipeline supports both printed and handwritten content
- The workflow includes user validation and duplicate detection
Evidence from the source
"API call script or client application sends parcel-label images to Alibaba Cloud Model Studio , where Qwen-VL-Plus Model performs OCR on printed and handwritten content, and returns extracted fields as structured JSON."
"Alibaba Cloud’s OCR solution powered by Qwen helped us accelerate Document Order processing in Finance. It’s improving accuracy while saving both time and operational costs."
"The parsed output is forwarded to the Backend Data Processing layer, which validates and normalises the fields, applying required rules."
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value90/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth25/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact15/251 metric describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence74%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence15/203 direct source quotes retained.
- Date provenance0/10The publication date has no documented provenance.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity10/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.alibabacloud.com/customers/lion-parcelAlibaba CloudFirst-party
Lion Parcel customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
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