- Geography: India
- Industry: Financial Services
- Employees: 100+
- Solution: AWS
- Services: AWS GenAI Implementation
The client
Jarvis Invest is a mid-to-large enterprise with a high demand for continuous hiring across technical and business roles. Managing large volumes of candidate applications while maintaining hiring quality, speed, and consistency had become an increasingly complex challenge for the organization.
Client requirements
Standardized Job Description Creation
Establish a consistent and structured process for creating accurate, role-specific job descriptions.
Intelligent Candidate Screening
Automate resume evaluation and candidate-job matching to improve hiring accuracy and reduce manual effort.
Streamlined Interview Coordination
Simplify interview scheduling and collaboration between HR and hiring teams through automated workflows.
Centralized Candidate Tracking
Create a single source of truth for interview feedback, candidate status, and hiring progress.
Data-Driven Recruitment Visibility
Enable real-time reporting and insights to support faster, informed hiring decisions.
Scalable & Secure Hiring Operations
Strengthen recruitment with secure access, continuous monitoring, and a scalable platform to support growing hiring demands.
Our approach
enreap designed and implemented a GenAI-powered recruitment solution on AWS for Jarvis Invest, built to automate the hiring lifecycle end-to-end and bring intelligent decision-making into every stage of recruitment. The solution centers on Amazon Bedrock for AI-driven content generation and candidate evaluation, and Amazon Kendra for contextual resume analysis, orchestrated through Amazon EC2 as the central application layer. Supporting services, including Amazon S3, Amazon DynamoDB, Amazon Cognito, and Amazon SNS, ensure secure, scalable, and efficient data handling and communication, while Amazon CloudWatch provides continuous monitoring and observability across the platform. As a result, Jarvis Invest achieved a significant reduction in manual effort and hiring turnaround time, improved candidate quality through AI-driven insights, and established a standardized, scalable, and data-driven recruitment process.
Our solution
Secure User Authentication
Implemented Amazon Cognito-based authentication with a secure AWS architecture to provide controlled access for recruiters and hiring teams.
AI-Powered Job Description Generation
Automated the creation of standardized, role-specific job descriptions using Amazon Bedrock foundation models, improving consistency and reducing manual effort.
Automated Interview Evaluation
Enabled AI-driven analysis of interview transcripts and interviewer feedback to generate structured candidate assessments and hiring recommendations
Centralized Candidate Data & Notifications
Stored recruitment data securely using Amazon S3 and DynamoDB, while automating recruiter notifications through Amazon SNS for faster decision-making.
Intelligent Resume Screening
Leveraged Amazon Kendra and Amazon Bedrock to analyze resumes, assess candidate-job fit, generate match scores, and automate shortlisting recommendations.
Scalable & Secure AWS Foundation
Built a secure, cloud-native architecture with AWS IAM, AWS KMS, private networking, and monitoring services to ensure scalability, governance, and operational reliability.
Business benefits
- Reduced resume screening effort by 70–80% through AI-powered automation
- Achieved a 40–60% faster hiring cycle, significantly improving time-to-hire
- Improved quality of hire through standardized, data-driven candidate evaluation
- Eliminated manual effort in job description creation, screening, and feedback generation
- Enabled unbiased, consistent candidate assessment using AI-driven scoring models
- Enhanced recruiter productivity by automating repetitive tasks
Technology stack
