Enterprise RAG Chatbot PoC – Secure GenAI Chat with Your Data

Why this matters?

Off-the-shelf models are trained on public internet data. They rarely know your warranty clauses, pricing tables, or clinic protocols—and sending that data to third-party APIs is a non-starter for security teams. Amazon Bedrock’s fully managed generative-AI stack lets you keep IP in-house: models cannot fine-tune themselves on your prompts or documents.

Chaos Gears uses Amazon Bedrock Knowledge Bases, OpenSearch, Titan Embeddings and models like Amazon Nova and Claude to deliver a working RAG chatbot prototype on your data. Critically, no data is used to train or fine-tune models, keeping your intellectual property safe and fully isolated thanks to Bedrock’s secure foundation.

Our PoC includes:

• Parsing and indexing your documents (PDFs, Word, HTML, Confluence, SharePoint, etc.)
• Configuring a Bedrock Knowledge Base with OpenSearch to store your data and keep it fresh
• Building a secure GenAI API with API Gateway and Lambda that you can connect to your front-end
• Optionally deploying a front-end (ReactJS with Cognito, S3, CloudFront)

What we deliver

1. Kick-off & success criteria Together we define target user groups (e.g., customer-service agents, loan officers, clinicians), top 50 questions and measurable KPIs.

2. Data connector setup Secure ingestion pipelines pull from S3, SharePoint, Confluence, or SQL dumps. OCR and structure parsers capture tables, diagrams and scanned PDFs.

3. Knowledge base build We deploy OpenSearch with Titan Embeddings, configure Bedrock Knowledge Bases and seed them with up to 100 000 documents.

4. Chat orchestration layer Lambda functions call Bedrock (Claude 3.7, Claude 4, Nova, or others) with RAG prompts that cite sources, handle follow-ups and optionally trigger downstream agents using Amazon Bedrock Agents.

5. Evaluation & hand-off Using your test set, we measure exact-match and semantic-match scores, estimate monthly run costs and show you how to move forward to production.

Example use cases: Customer service – surface warranty terms, shipment status instructions and upsell options in seconds. Financial advisors – answer MiFID or SEC FAQs directly from policy manuals; generate compliant call notes. Healthcare – guide clinicians to the latest treatment guidelines or drug interactions without violating PHI (data never leaves your VPC). Engineering & chemicals – retrieve MSDS, part specifications, or process diagrams with diagram-aware parsing. Enterprise IT – internal “how-to” bot for onboarding, VPN issues and license queries.

Engagement facts

• Duration: 3–4 weeks.
• All compute in your AWS account; no data leaves your security boundary.
• Foundation for future agents, voice interfaces, or multi-language support (over 100 languages via Bedrock).

Most PoCs complete in 3–4 weeks. After that, the system can be scaled or extended with minimal effort. You pay mostly per query - keeping upkeep low and predictable.