Client: Fortune 500 Tech Company
GenAI Knowledge Assistant
Built LLM-powered knowledge assistant using RAG and fine-tuning enabling instant access to company knowledge.
Project Outcomes
95% Accuracy
Highly accurate responses
40% Faster Support
Reduced support tickets
$2M Savings
Support cost reduction
10K+ Queries Daily
High adoption rate
24/7 Availability
Always on support
Multi-Language
Supports 10 languages
Problem Statement
High Support Cost
Large support team needed
Limited Availability
Only 9-5 support
Long Resolution Time
Hours to resolve
Knowledge Loss
Expert knowledge not captured
Scaling Difficulty
Hard to scale globally
Quality Inconsistency
Variable support quality
AI Assistant
Use Case & Architecture
RAG-Based LLM
Retrieval-Augmented Generation with knowledge base integration.
LLM Service
Claude API for generation
Knowledge Base
Vectorized documents
Embedding Model
Text similarity search
Chat Interface
Web and mobile UI
Analytics
Query tracking
Feedback Loop
Continuous improvement
Accuracy
95% response quality
Volume
10K+ queries daily
Cost Saving
$2M annually
AWS Services
Bedrock LLM
Managed LLM service
Lambda
Serverless functions
DynamoDB
Conversation storage
S3
Document storage
OpenSearch
Vector search
CloudWatch
Monitoring
API Gateway
API management
Cognito
User authentication
QuickSight
Analytics
Conclusion
Delivered AI-powered knowledge assistant improving customer support with 95% accuracy.