HR AI Chatbot Agent
Built released backend query and mutation endpoints for an HR AI chatbot agent, supporting business operations such as KPI data access, performance appraisal creation and approval flow, expense data, ATS candidate records, and other HR workflows.
HR workflows needed an agent-ready backend layer so AI-driven operations could safely interact with product functionality instead of relying on manual operations in the Better HR Dashboard.
- The agent needed backend operations it could call reliably for real HR-related actions
- Queries and mutations had to map cleanly into HR workflows instead of relying on loosely structured responses
- Released product behavior required stronger backend support than a prototype-style assistant
Built backend queries and mutations for the HR AI agent so it could support operational HR workflows through structured agent actions.
- Implemented agent-facing queries for KPI data, expense data, ATS candidate records, and other HR-related operational information
- Implemented mutations for business workflows such as performance appraisal creation and approval actions
- Structured backend operations so the released HR agent could interact with product workflows more safely and predictably
Approached the work as production-facing backend integration, prioritizing structured operations and controllable agent behavior over a purely conversational implementation.
- Exposed capabilities through explicit queries and mutations instead of opaque free-form backend behavior
- Kept the agent aligned with operational workflows by giving it structured access patterns into the system
- Wrote user-friendly, business-oriented descriptions for queries and mutations so the AI could perform better with real product operations
Accepted added backend complexity in exchange for making the agent more usable and safer in a real product environment.
- Agent-ready operations required more structured backend design than a simple chat interface
- Queries and mutations needed clear boundaries so AI-driven actions would stay predictable
- Business-friendly endpoint descriptions required extra care, but they improved how well the AI understood and used operational capabilities
The released HR AI agent gained a more production-ready backend foundation through structured operation endpoints for real workflow support.
- Enabled the HR AI agent to work with KPI data, expense data, ATS candidate records, and appraisal workflows through structured operations
- Improved AI performance by pairing backend endpoints with clearer business-oriented query and mutation descriptions
- Strengthened backend control over how AI-driven interactions connect with real HR operations