AI-Powered Survey Analysis

An Employee Feedback and Analytics Company

Client

A leading employee feedback and analytics company that humanizes data to help organizations improve employee and organizational performance. The client specializes in providing comprehensive talent insight solutions through cloud-based technology platforms and advisory services, serving organizations of all sizes across various industries with their employee engagement, retention, and culture improvement initiatives.

Challenge

The client required a comprehensive enterprise-grade survey analysis platform to transform their employee feedback capabilities into actionable business insights. We were tasked with developing a comprehensive end-to-end solution that encompasses an intuitive self-service frontend, a robust serverless backend architecture, and an advanced AI-powered analytics engine. Key deliverables included designing a scalable AWS infrastructure with a unified API architecture and implementing secure authentication. The platform needed to support real-time organizational data discovery, intelligent document management, summary export functionality, streaming chat interfaces, and seamless integration between MongoDB and AWS services. Additionally, the project required establishing automated CI/CD deployment pipelines with Terraform infrastructure as code and implementing enterprise-grade monitoring and logging across all components.

Key Results

Reduced manual survey analysis time by 85% through automated AI-powered summarization with dynamic context enhancement
Increased survey insight accuracy by 70% through contextual document integration and demographic filtering
Reduced infrastructure complexity by 60% through consolidation from multiple Lambda functions to a single, endpoint-driven Lambda architecture

Solution

We implemented a comprehensive production-ready AI survey summarization platform using AWS serverless architecture and advanced MLOps practices. The solution included:

Secure Authentication System– Implemented AWS Cognito to authenticate users.
AI Survey Analysis– Integrated AWS Bedrock with Claude Sonnet 4 for intelligent survey summarization with better accuracy than previous models.
Dynamic Context Enhancement– Enabled users to upload context documents and files in multiple formats (PDF, DOCX, XLSX) to enrich survey analysis with organizational background and provide more accurate, relevant insights.
Data Segmentation– Built an advanced demographic filtering system allowing users to segment survey data across multiple dimensions, including geography, departments, business units, and custom fields for precise targeted analysis.
Self-Service Frontend Platform– The Frontend Platform is designed to enable users to independently input contextual information, upload files for survey enrichment, and configure data segmentation parameters. The platform provides self-service capabilities for downloading surveys and maintaining a comprehensive history of generated survey summaries.
Real-Time Chat Interface– Developed streaming conversational AI allowing users to interact with survey insights through natural language queries with context awareness
Automated CI/CD Pipeline– Established a comprehensive CI/CD pipeline using Terraform infrastructure as code, AWS CodePipeline, and CodeBuild for automated testing, building, and deployment.

Technologies Used

AWS Bedrock (Generative AI)
AWS Lambda (Serverless Computing)
AWS API Gateway (REST API Management)
AWS Cognito (Authentication & Authorization)
AWS S3 (Static Website Hosting & Storage)
AWS CloudFront (Content Delivery Network)
AWS CodePipeline (CI/CD Orchestration)
AWS CodeBuild (Build & Deployment Service)
Terraform (Infrastructure as Code)
js (Frontend Framework)
MongoDB (Data Source)
Python (Backend Development)
js (Frontend Build Process)
AWS Secrets Manager (Secure Configuration Management)
AWS CloudWatch (Logging & Monitoring)

Summary

We transformed a leading employee feedback and analytics company’s manual AI POC into a production-ready, self-service platform with intuitive dropdown interfaces and dynamic demographic filtering, reducing manual analysis time by 85% while improving user adoption by 95% through AWS serverless architecture. The solution leveraged AWS Bedrock with Claude AI for intelligent survey insights, implemented comprehensive CI/CD pipelines with Terraform infrastructure as code, and featured contextual document and system prompt integration.