Verified employees reached
Within an initial 600+ employee population. This measures initial reach.
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Case study 03 / Employee listening & applied AI
PUJA
Connecting employee conversations to sentiment changes that HRBPs can investigate.
01 / Problem
The question behind the work.
Employee listening needs a way to surface changes in sentiment and bring them to HRBPs for investigation. Conversations become more useful when they can inform timely follow-up.
02 / My ownership
What I took on.
I designed and deployed the employee-listening and early-warning system, orchestrating a primary conversation agent and reviewing sub-agents through scripts and APIs.
03 / Solution
From problem to working solution.
- 01
Coordinate a primary conversation agent with reviewing sub-agents through scripts and APIs.
- 02
Track sentiment and surface changes for HRBP investigation, connecting the AI workflow to human follow-up.
- 01Employee conversations
- 02Agent review
- 03HRBP investigation
04 / Evidence
The work, with context.
05 / Results
What changed.
Deployed an AI-enabled employee-listening workflow that surfaced sentiment changes for HRBP investigation, reaching more than 150 verified employees within the initial population.