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Integration: The chatbot can seamlessly integrate with existing Oracle Database and workflows, making it easy to deploy and use within the warehouse environment.
Scalability: As the volume of orders increases, the chatbot can scale to handle the additional workload, providing consistent support to warehouse personnel.
Analytics and Reporting: The chatbot can track and analyze common issues encountered during the picking process, providing valuable insights for process improvement.
User-Friendly Interface: The chatbot can offer a user-friendly interface for warehouse personnel to interact with, making it easy to request assistance and resolve issues.
Training and Onboarding: The chatbot can assist new employees with training and onboarding by providing guidance and support during the picking process.
24x7 Support: Since the chatbot operates round the clock, warehouse personnel can access assistance at any time, improving overall operational efficiency.
Real-time Assistance: The chatbot can provide immediate assistance to warehouse personnel when they encounter difficulties in picking items from the list and encounter issues with physical inventory and system inventory.
Efficiency: By automating the process of identifying the issue and recommending the solution, the AI/ ML-enabled chat BOT assists in finding the root cause of the problem and provides an action plan.
Accuracy: The chatbot can ensure that the correct API is triggered based on issues identified by the Warehouse personnel, validating it with system issues, minimizing the errors, and improving order accuracy.
Cost Savings: By resolving issues quickly and efficiently, the chatbot can help reduce costs associated with manual intervention and errors in the picking process.
Expected Implementation Timeline: Within Six Months (Horizon 1)