Introduction:
Kridaverse is not like other IT companies. They are a vibrant fusion of creative storytellers, game development heavyweights (C++, Blueprint), and mobile app artisans (Flutter, UI/UX). However, this versatile entrepreneur need a solution as quick and imaginative as they are when their ambitious GenAI learning assistant encounters serious performance problems.
Client
Kridaverse – Creativity Meets Code
Industry:
EdTech
Offering:
GenAI
AWS Services: The Technology Behind the Transformation
The solution leveraged several AWS technologies to create a comprehensive communication ecosystem:
Amazon Bedrock, Amazon API Gateway, Amazon DynamoDB, AWS Lambda, MongoDB, and Amazon VPC.
Business Need:
When AI Brilliance Hits a Speed Bump
With an on-premise GenAI LLM (Llama3) already in place, Kridaverse was ready to take a big step further by creating an advanced RAG (Retrieval Augmented Generation) solution. Their objective was to provide customized customer experiences by using their wealth of private data. But there was a crucial barrier on their path:
- Crippling Latency: Their existing system suffered from slow response times, creating a frustrating user experience.
- Barrier to Real-Time Interaction: This delay made seamless, real-time AI conversations impossible.
- Undermining AI Effectiveness: The latency directly threatened the core value and effectiveness of their ambitious GenAI initiative.
Solution Approach:
Rapyder carefully crafted a high-performance, scalable solution on AWS to overcome Kridaverse’s latency issue and unleash their GenAI potential. The multifaceted approach concentrated on each phase of the user interaction:
- Rapid Data Access (MongoDB): Optimized MongoDB queries, accelerated data retrieval by 40%, feeding the AI faster.
- Precision AI Core (Amazon Bedrock): Leveraged Bedrock’s LLMs with meticulously fine-tuned prompts for highly accurate, context-aware responses. The key lesson: nuanced prompt engineering was crucial for truly insightful AI.
- Seamless Workflow (AWS Lambda & API Gateway): API Gateway managed user requests flawlessly, while serverless AWS Lambda functions orchestrated efficient processing and interaction with data sources.
- Contextual Conversations (Amazon DynamoDB): DynamoDB enabled persistent session management and chat history, creating fluid, human-like AI interactions.
- Secure Foundation (Amazon VPC): The entire solution was housed within a secure Amazon VPC.
Reaping Rewards:
A Quantum Leap in Performance & User Delight
The strategic GenAI solution, architected by Rapyder on AWS, didn’t just meet Kridaverse’s expectations; it shattered them, delivering transformative results across the board:
- AI Speed Boost (60% Faster): Response times dropped from 10 to just 4 seconds, delighting users.
- Smarter, Personal AI: Bedrock’s LLMs provided precise, trusted recommendations.
- Seamless Conversations: DynamoDB ensured smooth, continuous chat.
- Quicker Data (40% Faster): Optimized MongoDB fueled faster AI.
- Effortless Scaling & Lower Costs: Serverless AWS cut overhead and scaled easily.
- Always On, Always Actionable: Reliable AWS provided uninterrupted service and real-time insights.
Conclusion:
Beyond Speed – Unlocking EdTech’s Potential
The success of Kridaverse with AWS and Rapyder shows the significant influence of well-thought-out cloud solutions. By overcoming latency, they not only sped up an AI but also established a more effective, engaging, and human-centered learning environment, therefore raising the bar for AI in EdTech.
