Knowledge Access Transformation with RAG and AWS

60%
faster contract preparation
Knowledge Access Transformation with RAG and AWS | Crunch-IS Case Study
We developed a centralized knowledge access platform for a IT services provider. The solution integrates multiple information sources into a single, searchable knowledge base powered by RAG. This enabled sales and delivery teams to quickly find relevant information while preparing proposals, contracts, and customer engagements.
Industry:

Information Technology Services

Location:

United Kingdom

Technologies
React.js
Nest.js
AWS ECS
AWS Step Functions
AWS Kendra
AWS RDS PostgreSQL
AWS Bedrock
AWS Amplify
01

About the Client

Our client is a global IT services and consulting provider delivering managed IT services, cloud transformation, AI solutions, and digital transformation programs to enterprise organizations. With complex sales cycles, large service contracts, and extensive internal documentation, employees required faster access to proposals, pricing information, and project knowledge.

Knowledge Access Transformation with RAG and AWS | Crunch-IS Case Study
02

Challenge

Managers responsible for contract preparation faced fragmented access to information. Critical data was spread across different platforms: documents in SharePoint, contract drafts in S3, and deal histories in Salesforce.

This led to:

  • time-consuming manual searches across platforms
  • inconsistent and error-prone contract data
  • slower contract turnaround times and reduced operational agility

The client needed a centralized, intelligent knowledge platform capable of retrieving, understanding, and contextualizing contract-related data from diverse sources.

03

Solution We Delivered

Crunch-IS developed a Retrieval-Augmented Generation (RAG) system designed to unify and simplify enterprise knowledge access.

At its core, the solution integrates AWS Kendra as the primary semantic search engine, enriched with LLM capabilities through AWS Bedrock for context-aware querying and summarization.

Data from SharePoint, Salesforce, and S3 is continuously synchronized through AWS Step Functions, ensuring all sources remain up to date and searchable.

The user-facing interface, built with React.js and Nest.js, enables managers to use natural language queries – retrieving relevant documents, summaries, and key data points instantly.

Image Case Study | Crunch-IS
04

Implementation Approach

To ensure performance, scalability, and security, we deployed the solution on a cloud-native AWS architecture:

  • AWS ECS – handled containerized deployment of microservices for efficient scaling.
  • AWS Step Functions – orchestrated automated ETL workflows for continuous data ingestion.
  • AWS RDS (PostgreSQL) – ensured reliable data persistence and structured metadata management.
  • AWS Amplify – streamlined CI/CD and deployment for the user-facing app.

This architecture provided real-time data synchronization, secure access controls, and a flexible foundation for future expansion – such as integrating additional enterprise knowledge systems.

05

Client’s Results

The new system transformed how managers accessed and used information:

  • 60% faster contract preparation – managers could instantly find the right data across multiple platforms.
  • Unified access – one centralized knowledge base replaced scattered document silos.
  • Improved collaboration – teams across departments accessed consistent, real-time data.
  • Higher win rate – reduced contract turnaround times directly contributed to faster deal closures.

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