Best AI tools for< Use Amazon Bedrock >

Amazon Bedrock is a cloud-based platform that enables developers to build, deploy, and manage serverless applications. It provides a fully managed environment that takes care of the infrastructure and operations, so developers can focus on writing code. Bedrock also offers a variety of tools and services to help developers build and deploy their applications, including a code editor, a debugger, and a deployment pipeline.

Amazon Web Services (AWS) is a comprehensive, evolving cloud computing platform from Amazon that provides a broad set of global compute, storage, database, analytics, application, and deployment services that help organizations move faster, lower IT costs, and scale applications. With AWS, you can use as much or as little of its services as you need, and scale up or down as required with only a few minutes notice. AWS has a global network of regions and availability zones, so you can deploy your applications and data in the locations that are optimal for you.

Bibit AI is a real estate marketing AI designed to enhance the efficiency and effectiveness of real estate marketing and sales. It can help create listings, descriptions, and property content, and offers a host of other features. Bibit AI is the world's first AI for Real Estate. We are transforming the real estate industry by boosting efficiency and simplifying tasks like listing creation and content generation.

Amazon Science is a research and development organization within Amazon that focuses on developing new technologies and products in the fields of artificial intelligence, machine learning, and computer science. The organization is home to a team of world-renowned scientists and engineers who are working on a wide range of projects, including developing new algorithms for machine learning, building new computer vision systems, and creating new natural language processing tools. Amazon Science is also responsible for developing new products and services that use these technologies, such as the Amazon Echo and the Amazon Fire TV.

Amazon Q in QuickSight is a generative BI assistant that makes it easy to build and consume insights. With Amazon Q, BI users can build, discover, and share actionable insights and narratives in seconds using intuitive natural language experiences. Analysts can quickly build visuals and calculations and refine visuals using natural language. Business users can self-serve data and insights using natural language. Amazon Q is built with security and privacy in mind. It can understand and respect your existing governance identities, roles, and permissions and use this information to personalize its interactions. If a user doesn't have permission to access certain data without Amazon Q, they can't access it using Amazon Q either. Amazon Q in QuickSight is designed to meet the most stringent enterprise requirements from day one—none of your data or Amazon Q inputs and outputs are used to improve underlying models of Amazon Q for anyone but you.

FutureSmart AI is a platform that provides custom Natural Language Processing (NLP) solutions. The platform focuses on integrating Mem0 with LangChain to enhance AI Assistants with Intelligent Memory. It offers tutorials, guides, and practical tips for building applications with large language models (LLMs) to create sophisticated and interactive systems. FutureSmart AI also features internship journeys and practical guides for mastering RAG with LangChain, catering to developers and enthusiasts in the realm of NLP and AI.

AIPEX is an AI tool for guest engagement, offering solutions for hotels, resorts, and vacation rentals. It provides a self-service virtual concierge that helps drive additional revenue, save time, and make guests smile by delivering personalized experiences. The tool enhances guest interactions, reduces operational costs, and increases occupancy rates through AI-driven features and communication capabilities.

Content Robot is an AI-powered content and image generator that helps users create high-quality, SEO-optimized content for their websites, blogs, and social media. The tool offers a wide range of templates and features to help users generate unique and engaging content quickly and easily. Content Robot is also affordable and easy to use, making it a great option for businesses of all sizes.

Videomagic is an AI-powered video generation platform that helps businesses create high-converting videos for various use cases such as e-commerce, real estate, and retail. With over 4000 templates and the ability to integrate with popular data sources like Amazon, Zillow, and Shopify, Videomagic streamlines the video creation process, making it easy for businesses to produce engaging and effective videos.

CommerceIQ is an AI-powered retail ecommerce management platform that helps consumer brands maximize their sales and growth in the digital space. It offers a range of automated tools and solutions to optimize content, prevent revenue leakage, manage retail media, automate profit recovery, and estimate market share using machine learning algorithms. The platform also provides agency partnerships, industry-specific use cases, and resources like ebooks, case studies, webinars, and blog posts to support businesses in their ecommerce strategies.

Gift Ideas AI is a free AI-powered gift finder and idea generator that helps users discover the perfect present for every occasion. The platform utilizes advanced AI technology to provide personalized gift recommendations, unique gift ideas, and budget-friendly options through affiliate links. With a GPT assistant chatbot, users can easily find gift suggestions and amazon store links for last-minute holiday gifts. Gift Ideas AI aims to simplify the gift-giving process and bring joy to both gift givers and recipients.

BrowseGPT is a free Chrome extension that uses artificial intelligence to automate your browser. You can give BrowseGPT instructions like "Find a place to stay in Seattle on February 22nd" or "buy a children's book on Amazon", and it will use OpenAI's GPT-3 model to process web pages and issue commands like CLICK, ENTER_TEXT, or NAVIGATE to complete the task for you.

Kopy is an AI-powered tool designed for Shopify store owners to easily copy and import products from other stores with just one click. It offers features like native translation, AI copywriting, and easy-to-use interface. Kopy stands out with its instant product import, bulk import options, customization, translation to any language, and user-friendly interface. The tool saves time and money for dropshippers by automating product import and enhancing product details with AI. Kopy offers affordable pricing plans tailored to entrepreneurs' budgets, empowering their e-commerce journey. The tool supports copying products from platforms like Shopify, Aliexpress, CJ Dropshipping, Etsy, and Amazon.

Cool Costume Ideas is a free AI-powered website that provides Halloween costume suggestions. Users can find the perfect costume last minute by discovering creative ideas based on their interests. The platform allows users to purchase costumes instantly. It is easy to use, offers personalized ideas, and is free to access. Cool Costume Ideas is an Amazon Affiliate and is made with love in Canada.

The website focuses on Robotics & A.I. Research and Development, providing information on various AI applications and technologies. It covers topics such as AI in healthcare, robotics, space technology, quantum computing, and more. The site also discusses the integration of AI in everyday devices like smartphones and explores the impact of AI on different industries. Additionally, it features articles on AI tools, career trends post-AI, AI in e-commerce, and the use of AI in companies like Amazon and Salesforce.

The Run Recommender is a web-based tool that helps runners find the perfect pair of running shoes. It uses a smart algorithm to suggest options based on your input, giving you a starting point in your search for the perfect pair. The Run Recommender is designed to be user-friendly and easy to use. Simply input your shoe width, age, weight, and other details, and the Run Recommender will generate a list of potential shoes that might suit your running style and body. You can also provide information about your running experience, distance, and frequency, and the Run Recommender will use this information to further refine its suggestions. Once you have a list of potential shoes, you can click on each shoe to learn more about it, including its features, benefits, and price. You can also search for the shoe on Amazon to find the best deals.

Motion is an AI-powered work planning and scheduling tool that helps individuals and teams be more productive and organized. It uses a proprietary algorithm called The Happiness Algorithm to automatically prioritize tasks, schedule meetings, and track progress. Motion integrates with popular calendars, task managers, and other productivity tools, making it easy to use and customize to your workflow. With Motion, you can save time, reduce stress, and achieve your goals more efficiently.

Abacus.AI is the world's first AI platform where AI, not humans, build Applied AI agents and systems at scale. Using generative AI and other novel neural net techniques, AI can build LLM apps, gen AI agents, and predictive applied AI systems at scale.

Journey+ is an AI-powered image generator that allows users to create high-quality images without using Discord. It offers a range of features such as image generation, image editing, and image blending, making it a powerful tool for designers, marketers, and agencies. Journey+ is easy to use and can be accessed from any desktop device. It is also affordable, with a free trial and a variety of pricing plans to choose from.

MapDeduce is an AI-powered tool that helps users understand and analyze complex documents. It can be used to summarize documents, extract key information, and identify potential red flags. MapDeduce is designed to save users time and effort by automating the process of document analysis.

This repository contains sample code demonstrating various use cases leveraging Amazon Bedrock and Generative AI. Each sample is a separate project with its own directory, and includes a basic Streamlit frontend to help users quickly set up a proof of concept.

The serverless-pdf-chat repository contains a sample application that allows users to ask natural language questions of any PDF document they upload. It leverages serverless services like Amazon Bedrock, AWS Lambda, and Amazon DynamoDB to provide text generation and analysis capabilities. The application architecture involves uploading a PDF document to an S3 bucket, extracting metadata, converting text to vectors, and using a LangChain to search for information related to user prompts. The application is not intended for production use and serves as a demonstration and educational tool.

The Amazon Transcribe Live Call Analytics (LCA) with Agent Assist Sample Solution is designed to help contact centers assess and optimize caller experiences in real time. It leverages Amazon machine learning services like Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker to transcribe and extract insights from contact center audio. The solution provides real-time supervisor and agent assist features, integrates with existing contact centers, and offers a scalable, cost-effective approach to improve customer interactions. The end-to-end architecture includes features like live call transcription, call summarization, AI-powered agent assistance, and real-time analytics. The solution is event-driven, ensuring low latency and seamless processing flow from ingested speech to live webpage updates.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

The Generative AI Application Builder on AWS (GAAB) is a solution that provides a web-based management dashboard for deploying customizable Generative AI (Gen AI) use cases. Users can experiment with and compare different combinations of Large Language Model (LLM) use cases, configure and optimize their use cases, and integrate them into their applications for production. The solution is targeted at novice to experienced users who want to experiment and productionize different Gen AI use cases. It uses LangChain open-source software to configure connections to Large Language Models (LLMs) for various use cases, with the ability to deploy chat use cases that allow querying over users' enterprise data in a chatbot-style User Interface (UI) and support custom end-user implementations through an API.

This repository contains sample applications showcasing the use of AWS Generative AI CDK Constructs to build solutions for document exploration, content generation, image description, and deploying various models on SageMaker. It also includes samples for deploying Amazon Bedrock Agents and automating contract compliance analysis. The samples cover a range of backend and frontend technologies such as TypeScript, Python, and React.

This repository showcases how to deploy generative AI models from Amazon SageMaker JumpStart using the AWS CDK. Generative AI is a type of AI that can create new content and ideas, such as conversations, stories, images, videos, and music. The repository provides a detailed guide on deploying image and text generative AI models, utilizing pre-trained models from SageMaker JumpStart. The web application is built on Streamlit and hosted on Amazon ECS with Fargate. It interacts with the SageMaker model endpoints through Lambda functions and Amazon API Gateway. The repository also includes instructions on setting up the AWS CDK application, deploying the stacks, using the models, and viewing the deployed resources on the AWS Management Console.

Multi-Agent Orchestrator is a flexible and powerful framework for managing multiple AI agents and handling complex conversations. It intelligently routes queries to the most suitable agent based on context and content, supports dual language implementation in Python and TypeScript, offers flexible agent responses, context management across agents, extensible architecture for customization, universal deployment options, and pre-built agents and classifiers. It is suitable for various applications, from simple chatbots to sophisticated AI systems, accommodating diverse requirements and scaling efficiently.

This solution provides a low-code ReactJS application to prototype and vet business use cases for GenAI using Retrieval Augmented Generation (RAG). It includes a backend Flask application that uses LangChain to provide PDF data as embeddings to a text-gen model via Amazon Bedrock and a vector database with FAISS or Kendra Index. The solution utilizes Amazon Bedrock as the only cost-generating AWS service.

A sleek and powerful macOS client for Amazon Bedrock, bringing AI models to your desktop. It provides seamless interaction with multiple Amazon Bedrock models, real-time chat interface, easy model switching, support for various AI tasks, and native Dark Mode support. Built with SwiftUI for optimal performance and modern UI.

This repository provides a sample solution for building generative AI agents using Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain. The solution creates a generative AI financial services agent capable of assisting users with account information, loan applications, and answering natural language questions. It serves as a launchpad for developers to create personalized conversational agents for applications like chatbots and virtual assistants.

This repository is a sample chatbot using the Anthropic company's LLM Claude, one of the foundational models provided by Amazon Bedrock for generative AI. It allows users to have basic conversations with the chatbot, personalize it with their own instructions and external knowledge, and analyze usage for each user/bot on the administrator dashboard. The chatbot supports various languages, including English, Japanese, Korean, Chinese, French, German, and Spanish. Deployment is straightforward and can be done via the command line or by using AWS CDK. The architecture is built on AWS managed services, eliminating the need for infrastructure management and ensuring scalability, reliability, and security.

This repository provides guidance on building a multi-tenant SaaS solution for accessing foundation models using Amazon Bedrock and Amazon SageMaker. It helps enterprise IT teams track usage and costs of foundation models, regulate access, and provide visibility to cost centers. The solution includes an API Gateway design pattern for standardization and governance, enabling loose coupling between model consumers and endpoint services. The CDK Stack deploys resources for private networking, API Gateway, Lambda functions, DynamoDB table, EventBridge, S3 buckets, and Cloudwatch logs.

Generative AI (生成 AI) brings revolutionary potential to transform businesses. This repository demonstrates business use cases leveraging Generative AI.

This repository provides code to deploy a chatbot powered by Multi-Model and Multi-RAG using AWS CDK on AWS. Users can experiment with various Large Language Models and Multimodal Language Models from different providers. The solution supports Amazon Bedrock, Amazon SageMaker self-hosted models, and third-party providers via API. It also offers additional resources like AWS Generative AI CDK Constructs and Project Lakechain for building generative AI solutions and document processing. The roadmap and authors are listed, along with contributors. The library is licensed under the MIT-0 License with information on changelog, code of conduct, and contributing guidelines. A legal disclaimer advises users to conduct their own assessment before using the content for production purposes.

AIAC is a library and command line tool to generate Infrastructure as Code (IaC) templates, configurations, utilities, queries, and more via LLM providers such as OpenAI, Amazon Bedrock, and Ollama. Users can define multiple 'backends' targeting different LLM providers and environments using a simple configuration file. The tool allows users to ask a model to generate templates for different scenarios and composes an appropriate request to the selected provider, storing the resulting code to a file and/or printing it to standard output.

A curated repository of code recipes, demos, and resources for basic and advanced Redis use cases in the AI ecosystem. It includes demos for ArxivChatGuru, Redis VSS, Vertex AI & Redis, Agentic RAG, ArXiv Search, and Product Search. Recipes cover topics like Getting started with RAG, Semantic Cache, Advanced RAG, and Recommendation systems. The repository also provides integrations/tools like RedisVL, AWS Bedrock, LangChain Python, LangChain JS, LlamaIndex, Semantic Kernel, RelevanceAI, and DocArray. Additional content includes blog posts, talks, reviews, and documentation related to Vector Similarity Search, AI-Powered Document Search, Vector Databases, Real-Time Product Recommendations, and more. Benchmarks compare Redis against other Vector Databases and ANN benchmarks. Documentation includes QuickStart guides, official literature for Vector Similarity Search, Redis-py client library docs, Redis Stack documentation, and Redis client list.

Generative AI on AWS by O'Reilly Media provides a comprehensive guide on leveraging generative AI models on the AWS platform. The book covers various topics such as generative AI use cases, prompt engineering, large-language models, fine-tuning techniques, optimization, deployment, and more. Authors Chris Fregly, Antje Barth, and Shelbee Eigenbrode offer insights into cutting-edge AI technologies and practical applications in the field. The book is a valuable resource for data scientists, AI enthusiasts, and professionals looking to explore generative AI capabilities on AWS.

This repository contains executable Python notebooks, sample apps, and resources for testing out the Elastic platform. Users can learn how to use Elasticsearch as a vector database for storing embeddings, build use cases like retrieval augmented generation (RAG), summarization, and question answering (QA), and test Elastic's leading-edge capabilities like the Elastic Learned Sparse Encoder and reciprocal rank fusion (RRF). It also allows integration with projects like OpenAI, Hugging Face, and LangChain to power LLM-powered applications. The repository enables modern search experiences powered by AI/ML.

Langrila is a library that provides an easy way to use API-based LLM (Large Language Models) with an emphasis on simple architecture for readability. It supports various AI models for chat and embedding tasks, as well as retrieval functionalities using Qdrant, Chroma, and Usearch. Langrila also includes modules for function calling, conversation memory management, and prompt templates. It enforces coding policies for simplicity, responsibility independence, and minimum module implementation. The library requires Python version 3.10 to 3.13 and additional dependencies like OpenAI, Gemini, Qdrant, Chroma, and Usearch for specific functionalities.

Guides on Amazon Bedrock setup and use

This GPT can generate software use cases, which are based on a use case templates repository and conform to a style guide.

The use case designer is configured with the latest Data Science and Behavioral Social Science insights to guide you through the process of defining AI and Machine Learning use cases for the ecosystem.Ai platform.

Enables sales & marketing leadership to identify high-value AI use cases

OpenAIのTerms of UseとPrivacy policyを参照できます(2023年12月14日適用分)

Show me your job description or just describe what you do professionally, and I'll help you identify high value use cases for AI in your day-to-day work. I'll also coach you on simple techniques to get the best out of ChatGPT.

Need a new name? Character, brand, story, etc? Try the matrix! Use all the different naming modules as different strategies for new names!

Use a GPT as a Carnivore Diet Coach

Use this to get increased engagement, more clicks and higher rankings for your content. Copy and paste your headline below and get a score out of 100 and 3 new ideas on how to improve it. For FREE.

Use me to PROTECT ⚠️ your Custom Instructions ! Type Spell 👉 "Protect Me"

Use this GPT to outline your romance novel: design your story, your characters, obstacles, stakes, twists, arena, etc… Then ask GPT to draft the chapters ❤️ (remember: you are the brain, GPT is just the hand. Stay creative, use this GPT as an author!)

Use AI to build an online business

Use me for educational insights, ALPHA, and strategies for investing in Domains & Digital Identity. Your GUIDE to Unstoppable Domains, ENS, Freename, HNS, and more. *DO NOT use as Financial Advice & Always DYOR* https://iheartdomains.com

Use the Innovation Algorithm to take ideas to impact.

Use a library terminal to explore the culture of an alternate world.

Use me to manage your contents.

Use me to help you decide what type of business to acquire. Let's go!

Use DALL-E to create a family constellation image for an issue that has been troubling you.

Use me as your volleyball trainer assistant.

使用GPTS快速识别关键因素，提高决策效率和工作效率，找到关键的20%，Use GPTS to quickly identify key factors, improve decision-making efficiency and work efficiency, and find the key 20%.