Intelligent Dispatching Hub

Functional Overview

With the Gnu intelligent agent as the dispatching center, a five-step closed loop of "automatic demand decomposition → intelligent matching → pre-exit proactive matching → AI interview → multi-role collaboration" is implemented, achieving the leap from manual negotiation to human-machine collaboration.

Customer Pain Points

  • Frequent demand fluctuations and long response cycles—personnel demand changes rapidly, and under traditional models, multi-level manual coordination is required, taking several weeks from demand proposal to personnel availability.
  • Insufficient supply-demand pull—lack of unified manpower demand pool and talent pool; supply-demand matching relies on manual撮合 by HR and PM, with low efficiency and low success rate.
  • Low efficiency in placing exiting personnel—project completion lacks a proactive matching mechanism for personnel release; new positions are only sought after exit notices are issued, resulting in large numbers of idle personnel waiting and high costs.
  • Redundant middle management levels—transactional work such as demand communication, interview invitations, and feedback confirmation consumes large amounts of management resources, leading to high management costs.

Solution Advantages

  • Human-machine collaborative dispatching hub: hiring department → Gnu (AI Agent) → AI digital employee → employee, forming a closed loop of "demand – dispatch – execution," reducing intermediate management nodes and enabling 7×24 uninterrupted dispatch response.
  • Automatic demand decomposition and structuring: after a demand is raised, AI digital employees automatically decompose customer requirements (PO) into structured JDs, including position, requirements, time period, and other information, and publish them to the talent pool with one click.
  • Pre-exit proactive matching: before exit, AI digital employees proactively match the demand pool and support department selection, improving the success rate of internal reallocation for exiting personnel. Placement cycle is compressed from 3 weeks to 3 days.
  • AI interview process automation: AI interviewers automatically complete online interview invitations, multimodal interactive interviews, intelligent evaluation, and matching recommendation push, with zero manual intervention in the interview process and interview efficiency improved by more than 5×.
  • Multi-role collaborative dispatching: AI digital employees can simultaneously coordinate hiring departments, HR, PMs, and employees, automatically completing transactional work such as communication, invitations, feedback, and confirmation, achieving end-to-end dispatch closed loop.

Architecture Diagram

Architecture Diagram