AI-Powered Boolean Search: 75% Cut In Sourcing Time

The Challenge

Traditionally, recruiters manually distilled job requirements into Boolean search strings to scour job boards for suitable candidates. This process was time-consuming and relied heavily on recruiters' expertise. The objective was to enhance this process by integrating OpenAI and Large Language Model (LLM) technologies into a cloud-based platform. This integration aimed to automate and refine candidate sourcing through customized Boolean search strings, ensuring precise matching between job requirements and candidate profiles. By leveraging advanced AI capabilities, the platform automates the generation of Boolean search strings based on natural language job descriptions. This automation replaces the iterative manual process, enhancing the efficiency and accuracy of candidate sourcing efforts. Recruiters no longer need to manually craft search strings, freeing up time to focus on strategic aspects of recruitment.

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The Solution

Prompt Engineering: Utilizes prompt engineering to define and refine the AI's understanding and generation of Boolean search criteria from job descriptions.

Structured LLM Outputs (JSON mode): Ensures that outputs from the LLM are structured in JSON format, facilitating seamless integration with the platform's backend systems and processes.

NLP Techniques: Incorporates advanced natural language processing techniques for text pre-processing and post-processing, enhancing the accuracy and relevance of generated Boolean search strings.

Boolean Logic: Integrates Boolean logic principles to ensure that the generated search strings effectively capture the nuanced requirements of job orders.

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Result:

93% Reduction in Workload: By automating the search string generation process, the platform has reduced the workload associated with manual candidate sourcing tasks. Recruiters now spend less time on administrative tasks and more time engaging with candidates and stakeholders.

Improved Recruitment Efficiency: Faster identification of suitable candidates has streamlined the recruitment process, enabling HR departments to fill positions more quickly with candidates who closely match job requirements.

‍Recruiters: Experience a significant increase in efficiency during candidate sourcing. Automated Boolean search generation allows recruiters to quickly identify and reach out to suitable candidates, reducing time spent on manual search string creation.

HR Departments: Benefit from improved alignment between job requirements and candidate qualifications. The automated process ensures that candidate pools are more closely matched to the job specifications, leading to higher-quality hires and reduced time-to-fill positions.

Case Studies

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Automating Financial Reviews to Boost Margins and Client Satisfaction

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AI Integration In RPO: 30% Improvement In Hire Quality

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Boost In Recruiter Productivity

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Decrease In Operational Costs

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A Texas retail electric provider needed better energy forecasts to offer competitive prices. We built a machine learning model using historical load data.

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Expanded Their Account Management Team's Span Of Control

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Reduced Compliance And Security Costs

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RPO Giant Slashes Hiring Costs 50%

A recruitment outsourcing provider needed a 5-year technology roadmap, including a custom platform, top recruiting integrations, and advanced analytics.

102%

Increase In Candidate Placements

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50% Efficiency Boost: RPO's AI-Driven Transformation

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AI-Powered Boolean Search: 75% Cut In Sourcing Time

See how OpenAI and LLM technologies automated Boolean search, boosting recruiter efficiency, speeding up hiring, and improving job-candidate alignment.

93%

Reduction In Workload

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Improved Recruitment Efficiency

50%

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Reduction In Creating Requirements. ‍

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Error Rate Reduction In Requirements Definition

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‍

The Solution

Prompt Engineering: Utilizes prompt engineering to define and refine the AI's understanding and generation of Boolean search criteria from job descriptions.

Structured LLM Outputs (JSON mode): Ensures that outputs from the LLM are structured in JSON format, facilitating seamless integration with the platform's backend systems and processes.

NLP Techniques: Incorporates advanced natural language processing techniques for text pre-processing and post-processing, enhancing the accuracy and relevance of generated Boolean search strings.

Boolean Logic: Integrates Boolean logic principles to ensure that the generated search strings effectively capture the nuanced requirements of job orders.

‍

Result:

93%

Reduction In Workload

45%

Improved Recruitment Efficiency

50%

Reduction In Administrative Overhead

93% Reduction in Workload: By automating the search string generation process, the platform has reduced the workload associated with manual candidate sourcing tasks. Recruiters now spend less time on administrative tasks and more time engaging with candidates and stakeholders.

Improved Recruitment Efficiency: Faster identification of suitable candidates has streamlined the recruitment process, enabling HR departments to fill positions more quickly with candidates who closely match job requirements.

‍Recruiters: Experience a significant increase in efficiency during candidate sourcing. Automated Boolean search generation allows recruiters to quickly identify and reach out to suitable candidates, reducing time spent on manual search string creation.

HR Departments: Benefit from improved alignment between job requirements and candidate qualifications. The automated process ensures that candidate pools are more closely matched to the job specifications, leading to higher-quality hires and reduced time-to-fill positions.

AI-Powered Boolean Search: 75% Cut In Sourcing Time

The Challenge

The Solution

MEET THE TEAM

Anand Krishnan

Sai Ganesh

Shamik Mitra

Andy Komandur

Andrew Zarkadas

MEET THE TEAM

Anand Krishnan

Sai Ganesh

Shamik Mitra

Andy Komandur

Andrew Zarkadas

Result:

Case Studies

Inferring Senior Well-Being Through Environmental Sound Classification

Hyper-Personalized Senior Care Through Machine Learning

Automating Financial Reviews to Boost Margins and Client Satisfaction

Azure's Innovative Cloud Security and Governance

Serverless Functions Optimize Resource Usage by 40%

Expedited VC Due Diligence: From 30 Days to 24 Hours

From Crisis To Cloud: POS Overhaul Success

AI Integration In RPO: 30% Improvement In Hire Quality

Streamlining Prepaid Card Operations Boost Growth 30%

AI-Driven Demand Forecasting Saves $1M for REPs

Smart Grid AI Optimizes 10,000+ Solar Panels

80% Faster Onboarding: FinTech Modernization Success

RPO Giant Slashes Hiring Costs 50%

Consero's FaaS Evolution: MVP to Full Rollout

50% Efficiency Boost: RPO's AI-Driven Transformation

AFR 2.0 Increases Stakeholder Confidence By 40%

AI Assistant Boosts Recruiter Productivity By 35%

AI Recruitment Enables 3x Faster Candidate Screening

Top Recruiting Firm Increases Hires Per Recruiter By 75%

AI-Powered Boolean Search: 75% Cut In Sourcing Time

Dynabot: Seamless Chatbot Integration In Just 35 Hours

Thinkurl: Streamlining Code Generation by 50%

30% Faster User-Centric Product Development With thinkPlanner

How to have a Tech-Forward Business

The Solution

Result:

How to have a Tech-Forward Business

How to have a Tech-Forward Business

How to have a Tech-Forward Business