Recruitment firm accelerated hiring by 30% with Gen AI-powered candidate screening
Our client is a staffing and recruitment organization with over 25 years of experience in building high-performing workforce pipelines. They wanted a solution that could automate the manual screening of high volume of resumes. We built a Gen AI-powered resume pre-screening solution that helps the client streamline candidate evaluation and improve hiring efficiency. They achieved 40% faster candidate screening, 90% less decision-making bias, 30% shorter time-to-hire, and 25% lower recruitment costs.
Industry: Recruitment
Business type: Enterprise - Services: Generative AI solution
- Technology: Generative AI, Cognitive services, Power Platform
Client profile
Our client is a leading staffing and recruitment firm with over 25 years of industry expertise. They help organizations address talent shortages, accelerate hiring cycles, and build high-performing teams. With a deep understanding of talent acquisition dynamics, they support organizations with 1000+ employees. They also maintain a candidate network of over 500,000 professionals and process hundreds of thousands of resumes each year.
Technical challenges
Our client faced a set of unique challenges in talent acquisition that needed immediate attention. These challenges had a direct impact on their ability to identify and secure the best-fit candidates for their clients. Some of the core challenges included:
High volumes of resumes
Our client spent hours manually screening thousands of resumes, making it difficult to shortlist qualified candidates. This caused delays in responding to clients with urgent hiring requirements.
Skill validation challenges
The client struggled to identify the right candidates with domain-specific skills, as resumes often lacked standardized formats. Skill validation became slow and inconsistent. It was heavily dependent on recruiter experience.
Reducing bias
The recruitment team had an unconscious bias during the candidate evaluation process. This created inconsistencies in hiring decisions. It affected diversity goals and increased the risk of overlooking qualified candidates.
Evaluation inefficiencies
Different recruiters followed different evaluation approaches during interviews and screenings. This led to inconsistent candidate assessments, repeated interview rounds, and difficulty in suitable candidate identification.
Repetitive candidate inquiries
Recruitment teams manually handle repetitive queries on application status, interview schedules, and job descriptions. Their valuable time was wasted on solving queries, slowing the hiring process.
Limited skill growth
Rejected candidates received limited feedback after interviews, leaving them without clear direction on areas of improvement. This reduced engagement and weakened the company’s long-term candidate relationship strategy.
Our solution
We built a Gen AI-powered resume pre-screening solution to help the client streamline candidate evaluation and improve hiring efficiency. After analyzing their recruitment workflow, our experts developed an intelligent system that automated resume screening, identified relevant skills, reduced manual effort, and enabled recruiters to make faster and more consistent hiring decisions.
Built a Generative AI-powered resume screening solution
Our AI specialists built a Generative AI-powered resume analysis solution to help our clients automate the extraction of skills, experience, qualifications, and certifications from resumes. We significantly reduced the time and effort required for manual resume screening by integrating AI models into the recruitment workflow. Our team enabled recruiters to process large volumes of applications faster so that they can focus on evaluating high-potential candidates.
Designed an intelligent skill matching engine using cognitive services
Our team worked closely with recruiters to understand role requirements and address the challenges they faced while identifying candidates. We have developed an intelligent skill-matching engine using cognitive services and natural language processing capabilities that evaluate candidate profiles against job descriptions based on context and relevance. This helped recruiters accurately identify qualified candidates, improving the quality of candidate shortlisting.
Developed an evaluation framework based on predefined rules
We conducted a discovery workshop and identified that personal biases often influenced candidate evaluations. Our AI engineers developed an AI-powered evaluation framework that assesses candidates based on predefined job qualifications, skills, and experience requirements. We standardized evaluation criteria and ensured candidates were reviewed using objective parameters. Thus, helping the client promote fairness and consistency throughout the recruitment process.
Used Microsoft Power Platform to design recruitment workflows
Our consultants collaborated with recruitment managers and operations teams to understand the existing hiring processes and identify workflow bottlenecks. We designed and implemented customizable recruitment workflows by using Microsoft Power Platform that aligned with the client’s hiring policies and approval structures. The solution automated recruiter assignments and evaluation stages while allowing administrators to modify workflows based on changing business requirements.
Deployed a Generative AI-powered chatbot for instant responses
Our team analyzed common applicant questions related to job openings, application status, interview scheduling, and hiring processes. We developed and deployed a Generative AI-powered chatbot that was capable of providing instant responses. It also guided candidates throughout their application journey. Integrating the chatbot into their recruitment platform improved candidate engagement and reduced response delays.
Built a recommendation engine to generate personalized feedback
We identified that rejected candidates rarely received actionable feedback to improve future job prospects. Our AI experts built a recommendation engine that analyzes candidate profiles, interview outcomes, and job requirements to generate personalized feedback. The solution generated tailored learning recommendations with response emails, helping candidates understand skill gaps. This strengthened the client’s long-term candidate engagement and talent relationship strategy.
Business goals and measurable outcomes
| Business objective | Business benefit delivered |
|---|---|
| Enhanced screening volume | 40% faster candidate screening |
| Boost productivity | 30% quicker time-to-hire |
| Improved decision making | 90% less decision-making bias |
| Reduced cost | 25% recruitment cost savings |
Tech stack
- Generative AI
- Azure OpenAI Service, GPT-4, Large Language Models (LLMs)
- AI & Cognitive Services
- Azure AI Document Intelligence (Form Recognizer), Azure AI Language, Azure AI Vision, Azure AI Speech (optional)
- Natural Language Processing (NLP)
- Named Entity Recognition (NER), Semantic Search, Skill Extraction, Text Classification
- Workflow Automation
- Microsoft Power Automate, Power Apps
- Business Intelligence
- Microsoft Power BI
- Conversational AI
- Microsoft Copilot Studio (formerly Power Virtual Agents), Azure OpenAI
- Knowledge Base & Search
- Azure AI Search (Cognitive Search), Vector Search
- Backend Development
- .NET, ASP.NET Core, C#
- Integration
- Microsoft Graph API, REST APIs, Azure Logic Apps
- Data Storage
- Azure SQL Database, Azure Blob Storage
- Security & Identity
- Microsoft Entra ID (Azure Active Directory), Role-Based Access Control (RBAC)
- Cloud Platform
- Microsoft Azure
- Monitoring & Logging
- Azure Monitor, Application Insights
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