AI Frameworks · aws-samples

generative-ai-use-cases

AWS GenU is a TypeScript application providing pre-built generative AI use cases (chat, RAG, summarization, image generation, agents) integrated with AWS Bedrock and other services. It offers a configurable platform to deploy, test, and operationalize multiple AI features within organizations, with support for custom agents and security controls.

Talk to DEV.co Discuss Implementation

Source: GitHub — github.com/aws-samples/generative-ai-use-cases

1.4k

GitHub stars

431

Forks

TypeScript

Primary language

MIT-0

License (Requires review (not clearly OSI))

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	aws-samples/generative-ai-use-cases
Owner	aws-samples
Primary language	TypeScript
License	MIT-0 — Requires review (not clearly OSI)
Stars	1.4k
Forks	431
Open issues	104
Latest release	v5.4.0 (2026-01-13)
Last updated	2026-07-03
Source	https://github.com/aws-samples/generative-ai-use-cases

What generative-ai-use-cases is

Full-stack TypeScript application (React frontend, Lambda backend, CDK infrastructure) supporting multi-model inference via AWS Bedrock (Claude, Llama, Mistral, Nova, DeepSeek), RAG via Kendra or Knowledge Base, Bedrock Agents, MCP integration, video/image generation, and voice interaction. Deployable via CDK with configurable feature flags and SAML auth.

Quickstart

Get the generative-ai-use-cases source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/aws-samples/generative-ai-use-cases.git2cd generative-ai-use-cases3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

RAG Platform for Enterprise Knowledge

Deploy document-based question answering across PDFs, Word, Excel using Kendra or Knowledge Base with advanced parsing, reranking, and metadata filtering—ideal for contract review, policy Q&A, or technical documentation.

Multi-Model GenAI Testing & Proof-of-Concept

Rapidly prototype and compare outputs from Claude, Llama, Mistral, Nova, and other Bedrock models in a single UI without custom integration code—useful for pilot projects and model selection.

Internal AI Agent Platform

Centralized deployment of custom Bedrock Agents (web search, code interpreter, domain-specific) with built-in SAML, audit trails, and role-based access—suitable for scaling AI assistants across departments.

Implementation considerations

Requires AWS account with Bedrock, Lambda, and optionally Kendra/Knowledge Base provisioned; IAM roles and cost controls must be configured upfront.
TypeScript/Node.js backend assumes familiarity with CDK; non-trivial to customize model parameters, prompt engineering, or multi-tenancy.
Supports feature toggles (hiding use cases, enabling agents, MCP) but heavy customization beyond documented options may diverge from upstream.
Document ingestion for RAG (PDF, Word, Excel) depends on Kendra or Knowledge Base capacity and parsing accuracy; large document sets require testing.
Voice chat, video analysis, and image generation features depend on Bedrock model availability and latency; user experience tied to model response time.

When to avoid it — and what to weigh

Greenfield, non-AWS GenAI Stacks — Tightly coupled to AWS Bedrock; unsuitable if your organization uses Azure OpenAI, Anthropic API, or open-source models outside Bedrock.
Minimal Dependencies / Serverless-First Constraints — Requires CDK deployment, Lambda, Bedrock, optional Kendra/Knowledge Base, RDS/DynamoDB, and SageMaker integration—not a lightweight library.
Highly Custom UI/UX Requirements — Provides opinionated React UI for preset use cases; deep customization of UI flows or branding may require significant refactoring.
Real-Time Streaming or Sub-Second Latency — Lambda cold starts and Bedrock API latency may not meet stringent SLA requirements for high-frequency, low-latency interactions.

License & commercial use

MIT-0 (MIT No Attribution): permissive, no attribution required, no patent grants. Allows commercial use, modification, and distribution without conditions.

MIT-0 is a permissive OSI-compliant license explicitly allowing commercial use. However, this covers only the GenU code; AWS Bedrock model access, Lambda compute, Kendra, and Knowledge Base incur separate AWS usage costs. Verify Bedrock model terms (e.g., Claude, Llama licensing) for your use case.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Strong
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Strong
Assessment confidence	High

Security considerations

Application mentions 'rich security options' and SAML authentication in docs. IAM-based access control via Bedrock and Lambda expected. Consider: Bedrock model data retention policies, Kendra index access control, conversation history encryption at rest/in transit, API authentication mechanisms, and audit logging. No explicit security audit, pen-test results, or vulnerability disclosure process evident. Review AWS security best practices and model-specific data handling before deployment.

Alternatives to consider

LangChain / LangGraph (+ custom UI)

Open-source, multi-cloud agent framework; requires more custom integration but avoids AWS vendor lock-in and pays per model API calls (e.g., OpenAI, Anthropic).

Azure AI Studio / Prompt Flow

Microsoft alternative for RAG, model orchestration, and agent deployment; integrates with Azure Cognitive Search and OpenAI; suitable if your org standardizes on Azure.

Retool / UI5 (+ Bedrock SDK)

Low-code internal tool platforms with Bedrock integration; faster UI customization but less opinionated GenAI use-case structure.

Software development agency

Build on generative-ai-use-cases with DEV.co software developers

Explore AWS GenU for rapid RAG, agent, and multi-model AI integration. Start with CDK deployment and configure security, model selection, and custom agents for your organization.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

generative-ai GenerativeAIExamples generative_ai_project

Related on DEV.co

Explore the category and the services that help you build with it.

AI Frameworks AI Development Cloud Deployment Enterprise Software Talk to DEV.co

generative-ai-use-cases FAQ

Do I need to know TypeScript to use GenU?

No for basic deployment (CDK and configs); yes if you customize backend logic, add new use cases, or modify prompt templates. Deployment and UI usage require no TypeScript.

Can I use GenU with models outside AWS Bedrock?

Not natively. GenU is built for Bedrock. MCP integration allows external data sources, but model inference is Bedrock-only. Custom changes required otherwise.

What is the cost structure?

GenU itself is free (MIT-0). AWS charges apply: Bedrock model inference, Lambda compute, Kendra/Knowledge Base indexing, RDS/DynamoDB, and data transfer. Request-dependent; budget $100–1000/mo for modest usage.

Is GenU production-ready?

Yes, it provides audit trails, SAML auth, and role-based controls. However, review security posture (data retention, encryption), performance under load, and backup/disaster recovery for your SLAs.

Software developers & web developers for hire

DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If generative-ai-use-cases is part of your ai frameworks roadmap, our team can implement, customize, migrate, and maintain it.

Ready to Deploy GenAI Use Cases?

Explore AWS GenU for rapid RAG, agent, and multi-model AI integration. Start with CDK deployment and configure security, model selection, and custom agents for your organization.

Talk to DEV.co Schedule a Consultation