How did Arivihan and AWS build a real-time NEET question AI enrichment pipeline?
About Company
Arivihan is building India’s first fully automated online learning platform focused on NEET and K-12 education in vernacular languages.
With a mission to make high-quality education affordable for 200M+ students in Tier 2 and smaller cities, Arivihan delivers personalized, interactive learning at nearly 10% of traditional coaching costs.
Challenges
- Ingesting high volumes of NEET questions reliably in real time.
- Decoupling enrichment workflows to avoid bottlenecks and back-pressure.
- Combining foundation models with custom ML inference seamlessly.
- Ensuring least-privilege access and secure AI orchestration.
- Isolating failures without impacting upstream ingestion.
- Managing quota-aware Bedrock and SageMaker usage.
- Establishing observability, CI/CD automation and DR readiness.
Solutions
- DynamoDB + Streams for real-time question ingestion and event triggers.
- AWS Lambda to validate payloads and route questions into subject-wise SQS queues (Physics, Chemistry, Biology) with DLQs.
- ECS Fargate workers (ECR-backed) to orchestrate AI enrichment.
- Amazon Bedrock for explanations, summaries and embeddings.
- Amazon SageMaker for custom inference such as difficulty scoring.
- Amazon S3 data lake (raw → processed → enriched) with versioning and analytics readiness.
- CloudWatch + IAM for observability, governance and least-privilege security.
- CI/CD with CodeCommit, CodeBuild and CodePipeline for automated deployments.
- Terraform-driven DR with DynamoDB PITR and S3 versioning aligned to defined RTO/RPO.
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Published By: Akhil Khandelwal
Akhil, Senior Manager of AWS Migration at AceCloud, has over 13 years of experience in the IT industry. His technical expertise is backed by an impressive array of certifications, including AWS Certified Solutions Architect, Professional, Google Cloud Associate Cloud Engineer, AWS SysOps Administrator, and ITIL v3. Follow him on LinkedIn.