Agentic Al in Action: A Multi-Agent Chatbot for DRP

ABOUT THE CLIENT

In modern supply chain management, efficient distribution resource planning (DRP) is key to optimizing inventory and meeting customer demands. To enhance this process, we developed an AI-powered chatbot using the Agentic AI framework. The chatbot handles sales and inventory queries, leveraging multi-agent AI to automate data retrieval and provide real-time insights. It streamlined decision-making,reduced manual efforts, and improved operational efficiency in DRP.

PROBLEM

System Fragility

Traditional chatbots struggle with processing complex queries due to a lack of structured task delegation.

Manual Work

Conventional chatbots rely on sequential processing, often requiring manual intervention for decision-making.

Bottlenecks And Inefficiencies

Traditional systems process all queries through a single execution path, leading to bottlenecks and inefficiencies.

Lacking Accuracy

Generic chatbots provide broad, generalized responses, lacking domain-specific accuracy.

Single-Point Vulnerability

Traditional chatbots often suffer from single points of failure.

SOLUTION

Master Agent

Directs queries to the relevant sub-agent (Sales or Inventory) based on the execution plan.

Planner Agent

Analyzes queries and formulates an optimal execution plan for retrieving required data.

Inventory Agent

Manages inventory-related queries,such as stock status,shortages, excess stock, and cover days.

Sales Agent

Handles sales-related queries, such as overselling, underselling,performance analysis, and forecasting.

Tasks Distribution

Each agent has a defined role, ensuring efficient and accurate query execution. This structured tasks distribution prevents bottlenecks and allows specialized processing, improving accuracy and efficiency.

BENEFITS

The shift to a high-tech model delivered significant business benefits:

Enhanced User Experience

Enhanced user experience with faster query resolution.

Improved Accuracy

Improved accuracy in data retrieval and analysis.

Decision-Making

Enhanced decision-making processes.

Error Isolation

If agent fails, the system itself ensures that it remains functional.

Fallback Mechanisms

Agents can reroute failed queries to alternative processes,reducing disruptions.

Dynamic Load Balancing

Workloads are distributed across agents, preventing system overloads.

TOOLS & TECHNOLOGIES USED

Client
Testimonials

ZingWorks LLP delivered exceptional results, generating additional revenue while maintaining excellent communication across time zones.

Executive, Mambo Media, Inc

ZingWorks successfully integrated solutions into one of the largest LMSs in the US, exceeding our goals with their innovative approach.

Karen Evans

Executive Director, Black Women Playwrights' Group

ZingWorks LLP automated our distribution process, increasing fill rate by 10% and truck utilization by 3% with their tailor-made solutions.

Sreerangarajan Srinivasan

Head of Logistics & Customer Service, Nivea India Pvt Ltd

ZingWorks LLP successfully deployed the app's features with seamless implementation and outstanding communication.

Nitesh Kumawat

CTO, Teevra Edutech Private Limited

ZingWorks LLP delivered on time and within budget, with a customer-centric approach that made all the difference.

Nitin Kulkarni

Director, Edgelytics Solutions Pvt Ltd

ZingWorks LLP delivered the project on time with excellent communication and seamless management.

Anonymous

VP, Radionome

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