Every case below is live in production. IP fully transferred to the client on delivery. We don't retain access or use your data for model training.
Hiring Automation9.1
End-to-End AI Hiring Pipeline — From JD to Offer Letter
A high-growth tech company hiring 200+ roles a year had a TA team of 6 drowning in manual work. We built an AI hiring pipeline that auto-screens resumes against role parameters, conducts async voice assessments for shortlisted candidates, schedules final rounds autonomously, and generates compliant offer letters — with a human in the loop only for the final decision.
Outcome: Time-to-offer: 34 days → 9 days. TA team capacity freed to focus on senior roles. Offer acceptance rate improved 22%.
9 days
Time-to-offer (from 34)
22%
Offer acceptance improvement
85%
Process steps automated
Resume screening AIVoice assessmentAuto-schedulingOffer automation
Attrition Intelligence9.2
AI Employee Intelligence — Predict Attrition Before It Happens
A 2,000-person services company was losing critical talent without warning. Exit interviews revealed patterns visible months earlier — declining engagement, reduced peer interaction, increased leave requests — but no system was connecting the dots. We built an employee intelligence layer that aggregates signals from HRMS, project tools, and survey data to generate individual flight risk scores and manager-specific retention recommendations.
Outcome: Voluntary attrition in high-risk cohorts reduced 37% after 6 months. 140 employees retained through proactive conversations.
6 months
Time to measurable impact
HRMS integrationSignal aggregationAttrition modellingManager intelligence