Challenges
Modernizing student support with AWS-powered gen AI
A global e-learning academy delivering intellectual property education needed to provide learners with fast, reliable support for registration, certification, finance, navigation, and academic queries. Existing support relied on email, consultations, and a manually maintained RASA chatbot, making it difficult to scale and keep information up to date. The result was slower responses, repetitive work for administrators and tutors, and a growing need for intelligent, always-available, context-aware learner support.
Solution
Gen AI assistants transform student support for a global e-learning academy
Zensar implemented a cloud-native gen AI solution featuring a digital administrator assistant and tutor assistant to support administrative and academic workflows.
Built on Amazon Bedrock and a retrieval-augmented generation (RAG) architecture, the solution combines foundation models with institutional knowledge to generate grounded responses.
Content from Amazon S3, SharePoint, and Confluence is indexed in Amazon OpenSearch Service, while Amazon Bedrock Guardrails, secure AWS infrastructure, and built-in observability ensure response quality, security, and operational visibility.
Digital administrator assistant and tutor assistant provide natural-language support for registration, certification, finance, navigation, course content, debates, quizzes, research, and other learner interactions.
A RAG architecture combines Amazon Bedrock foundation models with institutional knowledge to generate accurate, context-aware responses grounded in trusted content.
Data from Amazon S3, SharePoint, and Confluence is indexed into Amazon OpenSearch Service, while Amazon RDS for PostgreSQL securely maintains conversation history to support contextual interactions.
Amazon Bedrock Guardrails, LLM-as-a-Judge validation, AWS WAF, Amazon ECS, and built-in observability improve response quality, security, and operational efficiency.
Solution enablers
Tech stack:
Cloud-native gen AI
Retrieval-augmented generation
Semantic vector search
LLM-as-a-Judge
Observability
Zensar services:
Solution Architecture
GenAI Implementation
AWS Deployment
Application Development
Operational Optimization
AWS services:
Amazon Bedrock
Amazon OpenSearch Service
Amazon ECS
Amazon RDS for PostgreSQL
Amazon S3
Impact
Enhanced learner support with faster responses and higher engagement
Round-the-clock support for learner queries
60% faster responses and 30% faster registrations
30% higher learner engagement with GenAI support
More time for high-value learner support activities
Business outcome
The AWS-powered generative AI solution transformed learner support by delivering faster, context-aware assistance, improving response times, registration efficiency, student engagement, and operational productivity.
Conclusion
By combining gen AI with trusted enterprise knowledge, the solution delivers secure, scalable learner support while improving operational efficiency and user experience.