The PDF Invoice Parser System is a scalable, cloud-native solution designed to process invoices from 1000+ vendors with unique formats. The system employs a strategy pattern for vendor-specific parsing, supports both digital and scanned PDFs, and is optimized for serverless deployment.
graph TB
subgraph "Client Layer"
A[Web Portal]
B[API Clients]
C[Batch Upload]
end
subgraph "API Gateway"
D[Load Balancer]
E[Auth Service]
F[Rate Limiter]
end
subgraph "Processing Layer"
G[Ingestion Service]
H[Message Queue]
I[Vendor Detection]
J[Parser Orchestrator]
end
subgraph "Parser Engines"
K[Text Parser]
L[OCR Engine]
M[AI Parser]
end
subgraph "Data Layer"
N[Document Storage]
O[Parser Registry]
P[Results Database]
end
subgraph "Supporting Services"
Q[Monitoring]
R[Logging]
S[Cache Layer]
end
A --> D
B --> D
C --> D
D --> E
E --> F
F --> G
G --> H
H --> I
I --> J
J --> K
J --> L
J --> M
K --> P
L --> P
M --> P
G --> N
I --> O
J --> S
Q -.-> G
Q -.-> J
R -.-> G
R -.-> J
flowchart LR
subgraph "Ingestion Layer"
A1[API Handler]
A2[File Validator]
A3[Queue Publisher]
A1 --> A2
A2 --> A3
end
subgraph "Detection Layer"
B1[Text Extractor]
B2[Vendor Matcher]
B3[AI Classifier]
B1 --> B2
B2 --> B3
end
subgraph "Parsing Layer"
C1[Strategy Selector]
C2[Parser Factory]
C3[Parser Pool]
C1 --> C2
C2 --> C3
end
subgraph "Storage Layer"
D1[(S3 Bucket)]
D2[(DynamoDB)]
D3[(Redis Cache)]
end
A3 --> B1
B3 --> C1
C3 --> D2
A2 --> D1
B2 --> D3
sequenceDiagram
participant Client
participant API
participant Queue
participant Detector
participant Parser
participant Storage
participant Cache
Client->>API: Upload PDF Invoice
API->>API: Validate & Generate ID
API->>Storage: Store Original PDF
API->>Queue: Publish Parse Job
API-->>Client: Return Job ID
Queue->>Detector: Dequeue Job
Detector->>Storage: Fetch PDF
Detector->>Detector: Extract Text
Detector->>Cache: Check Vendor Cache
alt Vendor Found in Cache
Detector->>Parser: Send with Vendor ID
else Vendor Not in Cache
Detector->>Detector: Run AI Classification
Detector->>Cache: Update Cache
Detector->>Parser: Send with Vendor ID
end
Parser->>Parser: Select Strategy
Parser->>Parser: Execute Parsing
Parser->>Storage: Store Results
Parser->>Queue: Publish Completion
Client->>API: Poll/Webhook Status
API->>Storage: Fetch Results
API-->>Client: Return Parsed Data
flowchart TD
A[Receive PDF Document] --> B{Is Digital PDF?}
B -->|Yes| C[Text Extraction Module]
B -->|No| D[OCR Module]
C --> E{Extraction Quality Check}
D --> F{OCR Confidence Check}
E -->|High Quality| G[Rule-Based Parser]
E -->|Medium Quality| H[Hybrid Parser]
E -->|Low Quality| I[AI Parser]
F -->|High Confidence| G
F -->|Medium Confidence| H
F -->|Low Confidence| I
G --> J[Apply Vendor Template]
H --> K[Template + AI Assist]
I --> L[Full AI Processing]
J --> M[Validate Results]
K --> M
L --> M
M --> N{Validation Pass?}
N -->|Yes| O[Store Results]
N -->|No| P[Error Handler]
P --> Q{Retry Available?}
Q -->|Yes| I
Q -->|No| R[Manual Review Queue]
graph LR
subgraph "API Functions"
A1[Upload Handler]
A2[Status Handler]
A3[Result Handler]
end
subgraph "Processing Functions"
B1[Vendor Detector]
B2[Text Parser]
B3[OCR Parser]
B4[AI Parser]
end
subgraph "Support Functions"
C1[Cache Warmer]
C2[Health Check]
C3[Cleanup Job]
end
subgraph "Triggers"
D1[API Gateway]
D2[SQS Queue]
D3[EventBridge]
end
D1 --> A1
D1 --> A2
D1 --> A3
D2 --> B1
D2 --> B2
D2 --> B3
D2 --> B4
D3 --> C1
D3 --> C2
D3 --> C3
graph TB
subgraph "Container Registry"
A[Base Python Image]
B[Parser Libraries Layer]
C[AI/ML Models Layer]
end
subgraph "Lambda Containers"
D[Vendor Detector Container]
E[Text Parser Container]
F[OCR Parser Container]
G[AI Parser Container]
end
subgraph "ECS/Fargate Tasks"
H[Batch Processor]
I[Model Training]
J[Data Pipeline]
end
A --> D
A --> E
A --> F
A --> G
B --> D
B --> E
B --> F
C --> F
C --> G
A --> H
B --> H
C --> I
erDiagram
INVOICE_JOB {
string job_id PK
string status
timestamp created_at
timestamp updated_at
string vendor_id FK
string document_url
json metadata
}
VENDOR {
string vendor_id PK
string vendor_name
string parser_strategy
json parser_config
boolean is_active
timestamp last_updated
}
PARSE_RESULT {
string result_id PK
string job_id FK
json extracted_data
float confidence_score
string parser_used
json validation_errors
}
PARSER_TEMPLATE {
string template_id PK
string vendor_id FK
string template_version
json field_mappings
json extraction_rules
}
INVOICE_JOB ||--|| VENDOR : "belongs to"
INVOICE_JOB ||--|| PARSE_RESULT : "produces"
VENDOR ||--o{ PARSER_TEMPLATE : "has"
graph TD
subgraph "Network Security"
A[CloudFront CDN]
B[WAF Rules]
C[VPC Private Subnets]
end
subgraph "Application Security"
D[API Key Auth]
E[JWT Tokens]
F[Role-Based Access]
end
subgraph "Data Security"
G[Encryption at Rest]
H[Encryption in Transit]
I[Data Masking]
end
subgraph "Compliance"
J[GDPR Controls]
K[Audit Logging]
L[Data Retention]
end
A --> B
B --> C
D --> E
E --> F
G --> I
H --> I
J --> K
K --> L
graph LR
subgraph "Metrics Collection"
A[CloudWatch Metrics]
B[Custom Metrics]
C[Application Metrics]
end
subgraph "Logging"
D[CloudWatch Logs]
E[Application Logs]
F[Audit Logs]
end
subgraph "Tracing"
G[X-Ray Traces]
H[Distributed Tracing]
end
subgraph "Dashboards"
I[Performance Dashboard]
J[Error Dashboard]
K[Business Metrics]
end
A --> I
B --> I
C --> I
D --> J
E --> J
F --> K
G --> I
H --> J
graph TB
subgraph "Load Metrics"
A[Queue Depth]
B[Response Time]
C[Error Rate]
end
subgraph "Scaling Policies"
D[Lambda Concurrency]
E[ECS Task Count]
F[DynamoDB Capacity]
end
subgraph "Scaling Actions"
G[Scale Out]
H[Scale In]
I[Circuit Breaker]
end
A --> D
B --> E
C --> F
D --> G
D --> H
E --> G
E --> H
F --> I
graph LR
subgraph "Source Control"
A[GitHub Repository]
B[Feature Branches]
C[Main Branch]
end
subgraph "Build Stage"
D[Unit Tests]
E[Integration Tests]
F[Container Build]
end
subgraph "Deploy Stage"
G[Dev Environment]
H[Staging Environment]
I[Production Environment]
end
subgraph "Validation"
J[Smoke Tests]
K[Performance Tests]
L[Rollback Trigger]
end
B --> D
C --> D
D --> E
E --> F
F --> G
G --> J
J --> H
H --> K
K --> I
K --> L
graph TD
subgraph "Cache Layers"
A[CDN Cache]
B[API Gateway Cache]
C[Redis Cache]
D[Lambda Memory Cache]
end
subgraph "Cached Data"
E[Vendor Mappings]
F[Parser Templates]
G[ML Model Weights]
H[Frequent Results]
end
subgraph "Cache Policies"
I[TTL Management]
J[Invalidation Rules]
K[Warm-up Strategy]
end
A --> E
B --> F
C --> E
C --> F
D --> G
D --> H
I --> A
I --> B
I --> C
J --> C
K --> D
pie title "Estimated Cost Distribution"
"Lambda Functions" : 35
"Storage (S3)" : 20
"Database (DynamoDB)" : 15
"API Gateway" : 10
"Data Transfer" : 10
"ML/AI Services" : 10
- Serverless First: Lambda for stateless processing, ECS for long-running tasks
- Event-Driven: SQS/SNS for decoupling components
- Multi-Strategy Parsing: Text, OCR, and AI approaches based on document quality
- Vendor Registry: Centralized configuration for parser strategies
- Horizontal Scaling: All components designed for horizontal scaling
- Fault Tolerance: Circuit breakers, retries, and dead letter queues
- Cost Optimization: Resource pooling and intelligent caching
- Languages: Python 3.11+
- Frameworks: FastAPI, AWS Lambda Runtime
- PDF Processing: pdf-plumber, PyPDF2, pdfminer
- OCR: Tesseract, AWS Textract, Google Vision API
- AI/ML: OpenAI API, Anthropic Claude, AWS Comprehend
- Storage: S3, DynamoDB, Redis
- Compute: Lambda, ECS/Fargate
- Messaging: SQS, SNS, EventBridge
- Monitoring: CloudWatch, X-Ray
- Security: IAM, KMS, Secrets Manager