HR & Recruiting

TalentSense Agent

Accelerate candidate screening & deliver structured insights

Trusted by

Built on vetted NLP modules and used in beta trials with HR teams in tech and service sectors with positive feedback.

Success Story

**Unilever reduced video-interview screening time by 50,000 candidate-hours and cut hiring time by 90% using AI video assessment tools.**

Integrates with

applicant-tracking-systems-via-apihris-hr-platformsemail-notification-systems

⏱️

Screening throughput

~20 candidates per hour→~200 candidates per hour

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Time to shortlist

7 days→1–2 days

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Recruiting cost per hire (screening stage)

$500→$100

Problem

Many companies face overwhelming resume volumes, inconsistent screening decisions, human bias, and long time-to-hire — especially when initial filtering is manual or spreadsheet-based. Juniors or non-specialist HR teams waste hours scanning low-fit candidates.

Solution

TalentSense Agent uses large language models and rule-based scoring to automatically parse resumes, evaluate alignment to job requirements, score candidates, and produce summary reports with strengths/weaknesses. Recruiters review top-scoring candidates and can override or flag. This eliminates manual filtering drudgery and ensures objective, consistent initial screening.

Result

Users can expect to reduce screening time by 5×–10×, boost consistency among hiring teams, and surface higher-fit candidates earlier in process.

Use Cases

resume-screeningcandidate-rankinghr-reportingtalent-acquisitionai-screeningcandidate-evaluationhiring-assistanthr-automatiorecruitment-analytics

TalentSense Agent helps HR teams reduce time spent on early-stage hiring by automatically evaluating resumes, ranking candidates, and generating structured reports. It matches applicants to roles using your job requirements and past hiring data, flags red/green signals, surfaces risks or gaps, and allows recruiter override. Designed for medium to large talent volumes, it boosts consistency, fairness, and speed without replacing human judgment.

Integrations

applicant-tracking-systems-via-apihris-hr-platformsemail-notification-systems

Connect to your existing tools seamlessly

Technology Stack

Automation

large-language-models-transformerresume-parsing-embedding-modulesscoring-layers

Automation

workflow-engine-or-orchestrationscheduling-batching

Infrastructure

cloud-serverstorage-databaseapi-gateway-microservice-endpoints

Implementation Timeline

≈ 2–7 days

Requirements & Data Alignment

~1 week

Define project scope, data sources, and target outcomes. Align on screening criteria, evaluation metrics, and compliance requirements. Collect sample resumes and structure data for integration readiness.

Integration Setup with ATS / Resume Sources

~1–1.5 weeks

Connect the system with ATS platforms or resume databases. Set up data pipelines and authentication flows for candidate import/export. Validate data integrity and access permissions.

Model Calibration & Rule Mapping

~2 weeks

Train or calibrate the model with historical screening data. Define rule sets and weightings for experience, skills, and role fit. Conduct preliminary accuracy tests and adjust scoring thresholds.

Pilot Run with Sample Candidate Pool

~1 week

Run a controlled pilot using a representative candidate sample. Compare AI screening results with recruiter evaluations. Identify discrepancies and refine rules or parameters.

Feedback, Tuning & Rollout

~1–1.5 weeks

Gather recruiter feedback and implement improvements. Finalize configurations, approval workflows, and scoring explanations. Roll out the AI screening system to production.

Monitoring & Iteration

~1 week

Monitor performance metrics (accuracy, bias, efficiency). Adjust models and rules based on new hiring data. Prepare documentation for continuous updates and audit readiness.

Support Included

Includes comprehensive documentation and onboarding guide, prebuilt templates and rule sets for faster setup, and active support via email and chat according to SLA.