Client Overview
Plastic AI assists users in identifying product sustainability. When products are not eco-friendly, the chatbot recommends alternatives from its knowledge base. The client needed a scalable, intelligent solution handling real-time queries with high accuracy and minimal latency.
Business Challenge
Users lack quick, dependable information on plastic environmental impact, making manual research time-consuming and inconsistent.
Info Fragmentation
Eco data is scattered and hard to interpret quickly.
Manual Research
Time-consuming, inconsistent product sustainability checks.
Recommendation Gaps
Lack of automated eco-friendly alternative suggestions.
Scalability & Latency
Growing traffic requiring low-latency, reliable responses.
Solution Design
GenClouds developed Plastic AI leveraging AWS services and custom ML models.
AI-driven NLP Chatbot
Real-time product query understanding and eco validation using AWS Lex.
Recommendation Engine
Sustainable alternative suggestions from a curated knowledge base.
Omnichannel Deployment
Available across web and mobile applications.
Serverless Architecture
Cost-efficient scaling with low-latency responses using AWS Lambda.
Advanced Analytics
Interaction, trends, and eco-impact dashboards.
Enterprise-grade Security
Compliance-ready data handling with IAM roles and encrypted storage.
Results & Outcomes
Significant improvements in user experience, efficiency, and scalability.
Instant eco validation: immediate product sustainability assessment
High-accuracy sustainable alternative recommendations
Increased user engagement through simplified eco-decisions
Serverless model reduced infrastructure costs by 40%
Designed to handle thousands of daily queries at scale
Increased sustainability awareness among users
Conclusion
GenClouds delivered Plastic AI using AI, NLP, and serverless AWS architecture. The solution enables sustainable alternative adoption while maintaining reliability, security, and cost efficiency.