HR & IT Helpdesk Chatbot with Audio Transcription
This workflow creates an intelligent chatbot specifically designed for HR and IT service desks, supporting both text and voice interactions. It features audio transcription capabilities, converting employees' voice inquiries into text in real-time, and builds a knowledge base by analyzing internal policy documents to enable quick and accurate responses. By integrating advanced language models and vector databases, the chatbot can continuously remember the context of conversations, providing personalized support, effectively reducing the pressure on human customer service representatives, and enhancing the user experience.
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Workflow Name
HR & IT Helpdesk Chatbot with Audio Transcription
Key Features and Highlights
This workflow develops an intelligent HR and IT helpdesk chatbot that supports both text and voice message interactions, featuring built-in audio transcription to convert employees’ spoken inquiries into text for real-time processing. By downloading and parsing internal company policy PDF documents, it constructs a vector-based knowledge base to enable precise and rapid question-and-answer responses. Leveraging OpenAI’s language models and PostgreSQL’s vector database, the chatbot maintains conversational context for personalized and coherent support.
Core Problems Addressed
- Automates handling of employee inquiries regarding HR and IT policies, reducing the workload on human customer service
- Supports unified processing of both text and voice inputs, enhancing user experience
- Builds a customized knowledge base from internal documents to ensure accurate and company-compliant answers
- Maintains dialogue context to enable continuous, multi-turn intelligent Q&A
Application Scenarios
- Internal corporate HR helpdesk where employees can query policies on leave, payroll, attendance, etc., anytime
- IT support services providing quick answers to common technical issues and troubleshooting guides
- Any enterprise scenario requiring intelligent Q&A based on internal documentation
Main Workflow Steps
- Download and Extract Internal Policy Documents: Use HTTP request nodes to fetch company handbook PDFs and extract text content.
- Create Policy Vector Store: Chunk the extracted text, convert it into vectors using OpenAI embedding models, and store them in PostgreSQL’s vector database.
- Message Processing and Classification: Monitor Telegram messages, differentiate between text and voice inputs, and transcribe voice messages.
- AI-Powered Q&A: Invoke an AI agent that combines vector retrieval with chat memory to generate contextually relevant natural language responses.
- Send Replies: Deliver answers back to users via Telegram for real-time interaction.
Involved Systems and Services
- Telegram: Message trigger and interaction platform
- OpenAI: Provides text embeddings, audio transcription, and language model services
- PostgreSQL: Stores vector data and chat context for efficient retrieval and memory
- n8n Built-in Nodes: HTTP requests, file extraction, text chunking, and other data processing nodes
Target Users and Value Proposition
- HR and IT managers aiming to improve employee self-service efficiency
- Developers building internal customer service systems requiring multi-channel (text + voice) support
- Technical teams seeking to create intelligent Q&A bots based on internal documents to reduce repetitive manual workload
- Enterprises pursuing digital transformation projects to enhance employee satisfaction and response speed
This workflow leverages high automation and intelligence to help enterprises build a professional, efficient, and user-friendly internal helpdesk, significantly improving service quality and operational efficiency.
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