Monitors WhatsApp messages, classifies intent with GPT-4, routes to specialized AI agents, automates leave, attendance, FAQs, complaints, and candidate shortlisting, and notifies users with final responses.
This AI agent listens to incoming WhatsApp messages and uses GPT-4 to classify intent into HR categories. It routes messages to specialized AI agents (Leave, Attendance, HR FAQs, Complaints, Shortlisting) and uses Google Sheets, Google Calendar, and policy embeddings to perform actions. It returns interactive responses via WhatsApp and logs outcomes for auditing.
One supporting sentence with short explanation.
Monitor incoming WhatsApp messages.
Classify intent with GPT-4 and assign to the correct AI agent.
Retrieve data from Google Sheets for context and routing.
Execute actions via Google Calendar and Sheets.
Provide final WhatsApp responses with interactive options.
Log outcomes for auditing and SLA tracking.
This AI agent automates the HR workflow on WhatsApp, reducing manual triage and ensuring consistent policy handling.
One supporting sentence with short explanation.
Incoming WhatsApp message is captured and triggers the classification process.
LLM analyzes intent and routes to the appropriate AI agent based on category.
The selected AI agent uses connected tools to complete tasks and returns a WhatsApp response.
One supporting sentence with short explanation.
Scenario: An employee sends a WhatsApp message at 9:12 AM asking for two days of leave starting next Monday. The AI agent classifies the request as Leave. The Leave AI agent fetches the employee's balance from Google Sheets, verifies policy, and logs the request. If approved, the system schedules a calendar event and sends a WhatsApp confirmation with the approval status and next steps.
One supporting sentence.
Standardizes HR messaging and maintains auditable decisions.
Delivers instant answers to common questions and routes complex queries.
Keeps leave and attendance data accurate for payroll.
Automates shortlisting and routing of candidates.
Maintains integrations and ensures secure data access.
Keeps an auditable trail of automated decisions for governance.
One supporting sentence with short explanation.
Receives messages and delivers final responses to users.
Performs transcription, intent classification, and chatbot interactions.
Stores employee data, job descriptions, applicants, and logs actions.
Schedules meetings, leave approvals, and reminders.
Semantically searches policy documents for accurate responses.
One supporting sentence with short explanation.
One supporting sentence with short explanation.
Yes. Data in transit is protected with encryption and access is controlled by role-based permissions. Logs are retained for auditing with retention aligned to your policy. The agent adheres to your privacy rules and governance. You can configure data minimization and retention policies.
Absolutely. You can update the LLM prompt, add or modify intents, and adjust routing rules. The system supports expanding to new HR domains like payroll or IT support. Training data from your documents can improve accuracy over time. Changes can be tested in a staging environment before production.
Yes. Your policy documents are embedded into a vector store for semantic search, and the agent references these embeddings to inform decisions. Updates to policies are reflected by re-embedding documents. The integration ensures responses stay consistent with current rules. Regular audits verify alignment with policy.
The classifier assigns a probable category; if confidence is low, the message can be routed to a general HR assistant or flagged for escalation. The system may ask clarifying questions via WhatsApp to resolve intent. Escalation can trigger human review if required. This minimizes misrouting and keeps the user informed.
Yes. You can clone a working AI agent pattern to add Payroll, IT Support, or other care-paths. Each new agent uses the same data sources and toolset to maintain consistency. You can adjust integrations and prompts to fit the new domain. Scaling remains modular and drag-and-drop friendly.
The AI agent logs every action and outcome, enabling SLA dashboards and audits. You can define targets for response time and resolution rate. Reports summarize volume, routing accuracy, and user satisfaction. Alerts notify owners if thresholds are breached.
You need WhatsApp API access, OpenAI credentials, and data in Google Sheets and Google Calendar. A guided setup connects these services and creates initial intents and routes. You can customize prompts and embeddings to align with your policies. After setup, you can test end-to-end flows in a staging environment.
Monitors WhatsApp messages, classifies intent with GPT-4, routes to specialized AI agents, automates leave, attendance, FAQs, complaints, and candidate shortlisting, and notifies users with final responses.
