Project Overview
About 3A Brands
3A is a leading company in Italy in the distribution of clothing, footwear, and accessories, offering a wide range of products to both consumers and business partners. With a strong presence in the market and a commitment to quality, 3A Sport is constantly seeking ways to enhance customer satisfaction and streamline its operations.Key Challenges
- High Dependency on Manual Processes
- Time-Consuming Administrative Tasks
- Inefficient Ticket and Query Handling
- Inefficient Ticket Management
3A Brands partnered with Nivara to implement AI solutions that streamline operations, enhance customer service, and automate manual processes for improved efficiency and customer satisfaction.
Our Solution
Nivara developed a comprehensive AI ecosystem for 3A Brands, integrating multiple technologies to address their specific challenges.Sales Condition Creation
Creating sales conditions by automating the extraction of relevant data from customer communications and determining pricing, discounts, and surcharges based on pre-defined business rules.
Centralized Shipment Tracking
Replace the current manual, multi-portal login process with a unified tracking system that aggregates shipment data from various shipping providers.
Automated ERP Data Registry Generation
Automate the creation of structured XLS reports by extracting and transforming ERP data, thereby reducing manual intervention and ensuring up-to-date, accurate reporting.
Conversational AI Interface
Advanced natural language processing to understand and respond to customer queries, streamlining the customer service process.
Implementation Approach
1
Phase 1: Assessment
Comprehensive interviews and surveys to understand 3A Brands’ existing systems, workflows, and pain points.
2
Phase 2: Planning
Detailed analysis and AI solution design tailored to 3A Brands’ specific requirements and business processes.
3
Phase 3: Execution
Implementation of the Nivara Customer Service AI platform with its core features, followed by testing and deployment.
Getting Started with Nivara Customer Service AI
This guide will help you understand the Nivara Customer Service AI application and how to get started with using its various features.
Overview
Nivara Customer Service AI is a comprehensive solution designed to streamline shipment tracking, sales condition management, and excel report generation. With its intuitive interface and powerful features, Nivara Customer Service AI helps you manage your customer service operations efficiently.
System Requirements
Application Requirements
- Web Browser: Latest version of Chrome, Firefox, Safari, or Edge
- Internet Connection: Required for accessing the application
Nivara Customer Service AI is optimized for modern browsers and responsive design, allowing you to access it from any device with an internet connection.
Authentication
Nivara Customer Service AI leverages Supabase to implement a secure authentication system with comprehensive user management features:Login Options
Login Options
Nivara Customer Service AI uses a secure whitelisted email login system. Users enter their email address to receive a magic link for authentication.
User Access
User Access
Only whitelisted email addresses can access the portal. Contact your administrator to be added to the whitelist.
Access Control
Access Control
Protected routes require authentication via magic link. Unauthenticated users and non-whitelisted emails will be redirected to the login page.
Quick Start
Follow these steps to quickly get started with Nivara Customer Service AI:1
Log In/Create an Account
Visit the Nivara Customer Service AI Login Page and enter your email to receive the magic link.
2
Explore the Dashboard
Navigate to the dashboard to get an overview and enquire about the available features.
3
Track Your First Shipment
Use the shipment tracking feature to search for and track your first shipment.
4
Create a Sales Condition
Set up your first sales condition to streamline your business operations.
5
Generate Excel Report
Fetch data from your registry in an Excel format.
Core Components
Nivara Customer Service AI offers a comprehensive set of features designed to streamline your customer service operations:Shipment Tracking
Search for shipments by customer name or order ID with intelligent matching capabilities.
- View detailed shipment information
- Natural language query interface
- Fuzzy matching for customer names
Sales Condition Creation
Create and manage comprehensive sales conditions for your customers.
- Detail-based or type-based conditions
- Customizable pricing and discounts
- Payment terms management
Excel Report Generation
Generate customized Excel reports with comprehensive filtering options.
- Filter by customers and orders
- Downloadable Excel format
Conversation History
Maintain and manage conversation history for all features.
- Save and retrieve conversations
- Rename and organize threads
- Context-aware responses
Tech Stack
Frontend
- TypeScript: Core UI
Backend
- FastAPI: Modern, high-performance web framework for building APIs
- Uvicorn: ASGI server for FastAPI
- Python: Programming language
- SQLite: Database for storing conversations, user profiles, and shipping records
Deployment
- Docker: Containerization for consistent deployment
- Compute Engine: Application Serving
- GitHub Actions & WatchTower: CI/CD pipeline for automated deployment
Agent Details
Nivara Customer Service AI uses OpenAI’s language models to power its conversational interfaces:Agent Implementation
- Models Used:
- OpenAI o3-mini: For shipment tracking, sales condition, and Excel download agents
- Framework: pydantic-ai for agent creation and management
- Agent Types:
- Shipment Tracking Agent: Handles shipment tracking queries
- Sales Condition Agent: Assists with creating sales conditions
- Excel Download Agent: Helps generate Excel reports
Other Experiments
During the development of Nivara Customer Service AI, we conducted experiments with various LLM providers to evaluate their performance, reliability, and suitability for our specific use cases.
- Gemini
- DeepSeek
- Comparison
Gemini 2.0 Flash Experiment
We evaluated Google’s Gemini 2.0 Flash model as an alternative to OpenAI’s models for our agent implementation. Our testing revealed several limitations:
Key Findings
Conclusion
While Gemini showed promise in general language understanding, its limitations in following precise formatting instructions made it less suitable for our structured agent workflows, leading us to continue with OpenAI’s models for production deployment.