Intellectual Property India Publishes Patent Application for 'Recruitagent: A Neuro-Symbolic Multi-Agent System For Autonomous Interview Scheduling With Constraint Optimization, Live Calendar Integration, And Fairness Instrumentation' Filed by Mr. Priyansh Tomar; Mr. Kushagra Singhal; Mr. Kartikey Sangal; and Mr. Pankaj Pratap Singh

MUMBAI, India, June 16 -- Intellectual Property India has published a patent application (202611054111 A) filed by Mr. Priyansh Tomar; Mr. Kushagra Singhal; Mr. Kartikey Sangal; and Mr. Pankaj Pratap Singh, Ghaziabad, Uttar Pradesh, on April 28, for 'recruitagent: a neuro-symbolic multi-agent system for autonomous interview scheduling with constraint optimization, live calendar integration, and fairness instrumentation.'

Inventor(s) include Mr. Priyansh Tomar; Mr. Kushagra Singhal; Mr. Kartikey Sangal; and Mr. Pankaj Pratap Singh.

The application for the patent was published on June 5, under issue no. 23/2026.

According to the abstract released by the Intellectual Property India: "The present invention discloses RecruitAgent, a neuro-symbolic multi-agent platform de-signed to autonomously manage the complete interview scheduling lifecycle in enterprise recruitment workflows. Existing automated scheduling tools operate within rigid rule-based boundaries and cannot interpret ambiguous natural-language availability expressions, coor-dinate across distributed interviewer panels in multiple time zones, or provide any formal guarantee of scheduling correctness. Recent large language model (LLM)- based systems handle language fluently but produce scheduling outputs whose correctness is neither verifi-able nor reproducible. The disclosed system resolves this conflict through a stakeholder-decomposed three-agent architecture: a Candidate Agent that parses free-form availability and manages candidate-facing communication, a Recruiter Agent that enforces organisational constraints and panel-composition policies, and a Scheduling Agent that couples an LLM module (GPT-4o / LLaMA-3) with an OR-Tools CP-SAT constraint solver in a generate-verify-critiqueloop. All confirmed events are written directly to enterprise calendars via the Google Calendar APIv3 and Microsoft Graph (Outlook) API. A built-in Fairness Audit Layer computes disparateimpact ratios, time-zone equity scores, accommodation success rates. Keywords: Multi-Agent Systems, Interview Scheduling, Large Language Models, Con-straint Satisfaction Programming, Recruitment Automation, Neuro-Symbolic AI, CalendarAPI Integration, Fairness-Aware AI, HR Workflow Automation."

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