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Global Investment Firm Reduces Hiring Time by 30% with Coforge’s Quasar AI Platform

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Overview

A global investment firm partnered with Coforge to modernize its recruitment and talent operations, which were constrained by manual workflows, inefficient requisition handling, and misaligned candidate-job matching. The absence of an integrated AI framework resulted in slow hiring cycles and suboptimal candidate experiences.

Coforge deployed its Quasar AI platform—integrating over 110 AI agents—to automate sourcing, screening, and classification across the talent lifecycle. By combining Generative and Agentic AI with seamless system integration, the solution accelerated hiring, improved match accuracy, and laid the foundation for scalable, future-ready workforce planning.

Challenges

A global investment firm relied heavily on manual processes for recruitment, job requisitions, and talent matching—leading to delays, inefficiencies, and poor candidate experience.

Key issues included:

  • Resume screening and requisition handling bottlenecks
  • Misalignment between job posts and candidate searches
  • Lack of scalable, integrated AI frameworks for HR modernization

Solution

Coforge deployed its Quasar AI platform, integrating 110+ AI agents to automate and orchestrate talent lifecycle operations.

Core capabilities included:

  • Generative and Agentic AI for candidate matching, scoring, and job classification
  • SEO-driven job post optimization for better visibility
  • Reverse engineering agents to extract metadata from legacy systems
  • Seamless integration with existing HR and ATS platforms

Key Highlights

  • Enabled AI-powered decisioning for sourcing, shortlisting, and requisition workflows
  • Unified multiple agent roles: job requisition, talent match, and reverse engineering
  • Delivered continuous improvement through LangGraph-powered self-learning agents
  • Created a scalable automation fabric for future-ready hiring and workforce planning

The Impact

  • 30% Reduction in hiring turnaround time
  • 30% Cost Reduction in resume reverse engineering and manual overhead
  • 35% Boost in job-candidate matching accuracy

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