Internal HR Chatbot for Automating Employee Communications
Internal LLM-powered Chatbot Integrated Into the Company’s Corporate Messenger
Challenge
The HR department of a large company was receiving dozens of repetitive requests from employees every day — regarding vacation days, sick leave, benefits, company policies, and internal procedures.
This created a significant workload for the HR team, increased response times, and reduced the efficiency of internal communication.
The company needed a solution that could provide quick, accurate answers to common employee questions while maintaining personalization and data security.
Solution
Hidden Core developed an internal LLM-powered chatbot integrated into the company’s corporate messenger.
The system combines semantic search across internal documents with a generative model to provide precise, contextually relevant answers.
Key components of the solution:
Query processing through the LLM with contextual memory;
Connection to HR document databases and company policies via a retrieval pipeline;
Integration with internal information systems;
Analytics module to track query types and automation coverage.
Thanks to integration with corporate systems, the chatbot can provide instant personalized responses — for example, showing available vacation days, notifying about upcoming company events, or providing links to relevant internal documents.
Impact
The AI chatbot now automatically handles over 70% of routine HR requests, reducing HR workload and cutting response times from several hours to under one minute.
Employee satisfaction with internal support increased by 35%, while the HR team can focus on strategic tasks such as analytics, talent development, and improving service quality.
Hidden Core Contribution
Our team delivered the full development lifecycle — from data preparation and model training to architecture design, integration with HR systems, and deployment within the company’s infrastructure.
We also adapted the model to corporate terminology, implemented usage analytics, and provided ongoing support and development for the system.