A Public Generative AI Solution by Electromech Cloudtech
About the Solution
Electromech Cloudtech’s AI-Powered Intelligent Information Assistant is a Generative AI–driven question-answering platform designed to help large institutions make complex, content-heavy websites easily accessible through natural language interactions.
The solution enables users to ask questions in plain language and receive accurate, contextual, and up-to-date responses without navigating multiple web pages or menus. It is built on AWS Generative AI and serverless architecture, ensuring scalability, security, and cost efficiency.
This solution has been successfully implemented for Gujarat Technological University (GTU) as a reference deployment.
Reference Customer Example: Gujarat Technological University (GTU)
Gujarat Technological University (GTU), established in 2007 by the Government of Gujarat under Gujarat Act No. 20 of 2007, is a premier academic and research institution. With a vast ecosystem of affiliated colleges and thousands of students, GTU maintains a comprehensive website containing academic, administrative, and campus-related information.
GTU served as a reference implementation for this solution to demonstrate how Generative AI can significantly improve information accessibility for students.
Business Challenge (Common Across Institutions)
Large institutional websites typically face the following challenges:
Information is spread across numerous URLs and nested menus
Students struggle to find relevant information quickly
High dependency on manual support from administrative teams
Difficulty in keeping information updated and easily discoverable
Underutilization of available information due to poor accessibility
Institutions require a solution that prioritizes:
Ease of access
High accuracy
Simple content updates
Cost efficiency
Optional enterprise-grade security
Why a Generative AI Assistant is Needed
1. Interactive Prompt System
Natural Language Processing (NLP): Users can ask questions in plain language.
Conversational Interface: Human-like interactions improve usability and engagement.
Always-on access to information without dependency on office hours or manual support.
4. Personalized Responses (Optional)
Context-aware responses based on user profile and previous interactions.
5. System Integration (Optional)
Integration with institutional systems for:
Application status tracking
Real-time data access
Secure role-based access
6. Multi-Language Support (Optional)
Supports diverse and international user bases.
Proposed Public Solution Architecture
Solution Components
1. Data Access & Preparation
Institution provides a list of publicly available URLs or documents.
Electromech Cloudtech preprocesses, cleans, and structures the data for AI consumption.
2. AI Model Training & Fine-Tuning
Models are trained using AWS Bedrock services.
Fine-tuned to understand institutional context and reference original content accurately.
3. Backend API Layer
RESTful APIs enable secure communication with AI services.
Efficient retrieval of contextual responses using semantic search.
4. Frontend Integration
Can be embedded into existing websites or portals.
Supports chat-based or search-based user interfaces.
5. User Access Management
Role-based access control for public and authenticated users.
Secure handling of sensitive or restricted data when required.
Technology Stack
AWS Services
AWS Bedrock (Titan, Mistral)
AWS IAM
AWS EC2
Amazon RDS
Amazon DynamoDB
Amazon OpenSearch
Serverless Architecture
Third-Party Tools
Docker
Reference Architecture: RAG-Based Design
The solution uses Retrieval Augmented Generation (RAG) to improve accuracy and relevance.
How RAG Works
Content is indexed into a vector store
User queries trigger a semantic search
Relevant documents are retrieved in real time
AI responses are generated using retrieved data, not hallucinations
Benefits of RAG
Up-to-date responses
Reduced misinformation
Improved trust and accuracy
Extendable beyond model training cut-off
Key Benefits
For Institutions
Reduced administrative workload
Improved digital engagement
Data-driven insights into user behavior
Scalable and cost-effective information delivery
For End Users
Faster access to information
Accurate, contextual answers
24×7 availability
Improved overall experience
Reference Deployment Outcomes (GTU)
Significant improvement in information accessibility
Reduced dependency on manual support
Enhanced student experience
Overall effective utilization of information increased by ~90%
Conclusion
Electromech Cloudtech’s AI-Powered Intelligent Information Assistant demonstrates how Generative AI can transform large, complex information systems into intuitive, user-friendly platforms.
The successful implementation at Gujarat Technological University (GTU) serves as a reference use case, showcasing the solution’s scalability, accuracy, and real-world impact.
This solution is publicly reusable and adaptable across:
The full architecture behind GTU's generative AI programme: retrieval, identity, analytics and delivery, for one of India's largest public universities.
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