Connect with Us
backdrop

Jindal Steel Power - Document Management

JSPL implemented a serverless AWS Lambda-based system to automate document management, digitization, and translation across multiple regional facilities, enabling high-volume document workflows with automated processing and role-based access control.

backdrop

Automating Document Management at Scale

Serverless Translation & Digitization

About The Customer

An organization operating across PAN-India states with multiple production units and operational facilities. The organization's diverse workforce spans multiple regions with teams in various departments. Regional teams often work in local languages, creating communication and documentation challenges across the organization.

The Document Management Challenge

The organization faced significant operational challenges around document management and communication across geographically distributed facilities. Local personnel in regional departments struggled with English-language organizational policies, communications, and documents, creating knowledge barriers. Manual document management processes required personnel to upload, scan, and tag documents manually. Physical document storage created bulk management challenges, while human translators introduced inconsistencies, correctness concerns, and deployment delays.

Without automated workflows, no systematic tracking existed for document status, file metadata, or version control. Lack of security controls meant no regulated verification system for translations, creating data governance gaps.

Event-Driven Document Processing

By implementing serverless AWS Lambda architecture, document digitization, translation, and metadata tracking were automated across all facilities. Scheduled Lambda functions process uploaded files every 5 minutes without manual intervention, applying machine translation models to regional languages while maintaining security through role-based access control and complete audit trails.

Challenge Analysis

Identified manual document workflows, language barriers, and lack of automation causing inefficiencies across regional facilities.

Serverless Architecture

Designed event-driven Lambda system with automated document processing, language-specific translation, and metadata tracking.

Implementation

Deployed Lambda functions, S3 storage, automated translation pipeline, scheduled processing, and role-based access control.

Operations

Achieved automated bulk processing, large-scale document handling, improved accessibility, and complete audit trails.

The Solution Architecture

Document Digitization

Hardcopy document scanning and digitalization with automated case-wise tagging and unique identification codes for tracking and retrieval.

Automated Translation

Machine translation engines with language-specific models and custom routing, enabling automated translation to regional languages with optional manual verification.

Secure Access Control

Role-based access control ensuring only designated machines and departments can access assigned folders, with complete audit trails for compliance.

backdrop

Insphere implemented a serverless, event-driven architecture using AWS Lambda to transform JSPL's document management into a fully automated, intelligent system processing documents at scale across all regional facilities.

System Components:

  • AWS Lambda providing serverless compute for document processing functions without infrastructure management
  • Amazon S3 serving as centralized repository for source documents, processed files, and metadata backups
  • Amazon RDS (MySQL) logging comprehensive metadata including file URLs, sizes, types (PDF/WORD), and processing timestamps
  • Amazon EC2 instances for OS-level access, long-running processes, and specialized computing tasks
  • Machine translation models with custom scripting for language routing and regional language generation

Processing Pipeline:

  • Document Upload & Tagging: Hardcopy documents digitalized, scanned, and tagged with case-specific identifiers for organization
  • Scheduled Processing: Lambda functions triggered every 5 minutes automatically detect and process uploaded files without manual intervention
  • Intelligent Translation: Custom translation machine picks appropriate regional language models based on document metadata and routing rules
  • File Status Validation: Each processed file validated with language translation models and optional manual verification before final deployment
  • Metadata Logging: Complete capture of document metadata including URL, file size, type, processing timestamp, and version information
  • Role-Based Distribution: Processed files segregated by department with only designated machines and authorized personnel able to access assigned folders

Security & Compliance:

The system enforces strict role-based access control where each department can access only their assigned document collections. Complete audit trails capture every file operation, enabling compliance with data governance requirements and security audits. Optional manual correction capability ensures any machine-generated translation errors can be rectified, maintaining data quality and accuracy.

Fallback and backup mechanisms provide redundancy, ensuring processed files are safely stored and can be recovered if primary systems fail. MySQL metadata logging provides complete visibility into document lifecycle, supporting troubleshooting and compliance investigations.

Operational Impact & Results

Operational Efficiency:

  • Bulk documents processed automatically without manual intervention, eliminating manual uploading and tagging tasks
  • Drastic reduction in document processing timelines with automated workflows compared to manual processes
  • Regional personnel now receive documents in their native languages, improving accessibility and comprehension

Scalability & Performance:

  • System handles multiple locations, large document volumes, and different languages simultaneously without performance degradation
  • Serverless architecture scales automatically with document processing demand, requiring no infrastructure management
  • 5-minute scheduled processing ensures documents are available to regional teams within minimal delay

Translation & Accessibility:

  • Machine translation provides significant reduction in manual labor while maintaining baseline translation accuracy
  • Language-specific models ensure regional appropriateness and cultural relevance of translated documents
  • Consistent translation across organization reduces ambiguity and improves understanding of policies and procedures

Security & Governance:

  • Role-based data segregation ensures only authorized personnel and machines access assigned documents
  • Every processed file traceable through comprehensive MySQL audit logs, improving accountability and compliance
  • Regulated verification system for translations and file metadata, preventing unauthorized access or modifications

Risk Management:

  • Fallback correction capability available if machine-generated translations contain errors requiring human review
  • Comprehensive backup mechanisms ensure processed documents are safely stored and recoverable
  • Complete version control through metadata logging enables historical tracking and error investigation

By implementing serverless document processing with AWS Lambda, JSPL transformed organizational communication, enabling seamless document management and translation across its geographically diverse operations while maintaining security and compliance requirements.

Accessibility Settings