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AI-Powered Job Listing Aggregation Platform for Nonprofit Career Services
  1. case
  2. AI-Powered Job Listing Aggregation Platform for Nonprofit Career Services

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AI-Powered Job Listing Aggregation Platform for Nonprofit Career Services

future-processing.com
Non-profit
Education
Human Resources

Operational Inefficiency in Job Listing Aggregation

Manual data entry processes required 15 minutes per job listing, consuming excessive time and resources while increasing error risk. Legacy workflows hindered scalability and delayed job board updates, limiting the organization's ability to serve partners and job seekers effectively.

About the Client

US-based public charity supporting first-generation college graduates with career development, job placement, and networking services

Automation and Efficiency Goals

  • Reduce job listing processing time by 66% through AI automation
  • Eliminate manual data entry errors via intelligent extraction
  • Enable seamless integration with partner systems
  • Create scalable architecture for future growth

Core System Capabilities

  • URL input interface for job listing submission
  • AI-powered content extraction using foundation models
  • Automated data mapping to partner system formats
  • Error detection and validation workflows
  • Processing time tracking dashboard

Technology Stack Requirements

AWS Amplify
AWS Lambda
Amazon Bedrock
Claude 3

System Integration Needs

  • Partner job board APIs
  • AWS security services
  • Content delivery networks

Operational Requirements

  • Horizontal scalability for 10x volume growth
  • 99.9% system uptime SLA
  • Enterprise-grade data encryption
  • Sub-5 minute processing latency

Expected Business Outcomes

Processing time reduction from 15 to 5 minutes per listing will save 1,200+ annual labor hours, decrease errors by 90%, and enable real-time job board updates. The solution will improve partner satisfaction through faster listings while reducing operational costs by 40%.

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