Best AI tools for< Build Vector Database >
20 - AI tool Sites
![Singlebase Screenshot](/screenshots/singlebase.cloud.jpg)
Singlebase
Singlebase.cloud is an AI-powered platform that serves as an alternative to Firebase and Supabase. It offers a comprehensive suite of tools and services to facilitate faster development and deployment through a unified API. The platform includes features such as Vector Database, NoSQL Database, Vector Embeddings, Generative AI, RAG, Knowledge Base, File storage, and Authentication, catering to a wide range of development needs.
![BotX Screenshot](/screenshots/botx.cloud.jpg)
BotX
BotX is a no-code AI platform that enables users to automate and deploy generative AI workflows, chatbots, RAGs, and multi-agent solutions. With production-ready AI systems, users can increase productivity, build AI agents and chatbots, automate workflows, create or process documents, and connect models effortlessly. The platform offers a range of models and fine-tuning options, seamless integration of advanced models, and enterprise-grade results with grounded responses. Users can protect their data with various deployment options and enjoy dedicated support, integrations-ready solutions, and tailor-made solutions for enterprises and SMEs.
![Web Transpose Screenshot](/screenshots/webtranspose.com.jpg)
Web Transpose
Web Transpose is an AI-powered web scraping and web crawling API that allows users to transform any website into structured data. By utilizing artificial intelligence, Web Transpose can instantly build web scrapers for any website, enabling users to extract valuable information efficiently and accurately. The tool is designed for production use, offering low latency and effective proxy handling. Web Transpose learns the structure of the target website, reducing latency and preventing hallucinations commonly associated with traditional web scraping methods. Users can query any website like an API and build products quickly using the scraped data.
![Pinecone Screenshot](/screenshots/www.pinecone.io.jpg)
Pinecone
Pinecone is a vector database that helps power AI for the world's best companies. It is a serverless database that lets you deliver remarkable GenAI applications faster, at up to 50x lower cost. Pinecone is easy to use and can be integrated with your favorite cloud provider, data sources, models, frameworks, and more.
![Infrabase.ai Screenshot](/screenshots/infrabase.ai.jpg)
Infrabase.ai
Infrabase.ai is a directory of AI infrastructure products that helps users discover and explore a wide range of tools for building world-class AI products. The platform offers a comprehensive directory of products in categories such as Vector databases, Prompt engineering, Observability & Analytics, Inference APIs, Frameworks & Stacks, Fine-tuning, Audio, and Agents. Users can find tools for tasks like data storage, model development, performance monitoring, and more, making it a valuable resource for AI projects.
![Weaviate Screenshot](/screenshots/weaviate.io.jpg)
Weaviate
Weaviate is an AI-native database designed to bring intuitive AI-native applications to life with less hallucination, data leakage, and vendor lock-in. It offers features like Hybrid Search, Retrieval-Augmented Generation, Generative Feedback Loops, and Cost-performance optimization. Weaviate empowers developers to build AI-native applications with flexible, reliable, open-source foundations, tailored AI infrastructure patterns, and over 1M monthly downloads. The platform is known for its best-in-class hybrid search, integrations with major LLMs, and ease of deployment.
![Pinecone Screenshot](/screenshots/hypercube.ai.jpg)
Pinecone
Pinecone is a vector database designed to help power AI applications for various companies. It offers a serverless platform that enables users to build knowledgeable AI applications quickly and cost-effectively. With Pinecone, users can perform low-latency vector searches for tasks such as search, recommendation, detection, and more. The platform is scalable, secure, and cloud-native, making it suitable for a wide range of AI projects.
![Context Data Screenshot](/screenshots/contextdata.ai.jpg)
Context Data
Context Data is an enterprise data platform designed for Generative AI applications. It enables organizations to build AI apps without the need to manage vector databases, pipelines, and infrastructure. The platform empowers AI teams to create mission-critical applications by simplifying the process of building and managing complex workflows. Context Data also provides real-time data processing capabilities and seamless vector data processing. It offers features such as data catalog ontology, semantic transformations, and the ability to connect to major vector databases. The platform is ideal for industries like financial services, healthcare, real estate, and shipping & supply chain.
![Pinecone Screenshot](/screenshots/pinecone.io.jpg)
Pinecone
Pinecone is a vector database designed to build knowledgeable AI applications. It offers a serverless platform with high capacity and low cost, enabling users to perform low-latency vector search for various AI tasks. Pinecone is easy to start and scale, allowing users to create an account, upload vector embeddings, and retrieve relevant data quickly. The platform combines vector search with metadata filters and keyword boosting for better application performance. Pinecone is secure, reliable, and cloud-native, making it suitable for powering mission-critical AI applications.
![Langtrace AI Screenshot](/screenshots/langtrace.ai.jpg)
Langtrace AI
Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.
![SingleStore Screenshot](/screenshots/singlestore.com.jpg)
SingleStore
SingleStore is a real-time data platform designed for apps, analytics, and gen AI. It offers faster hybrid vector + full-text search, fast-scaling integrations, and a free tier. SingleStore can read, write, and reason on petabyte-scale data in milliseconds. It supports streaming ingestion, high concurrency, first-class vector support, record lookups, and more.
![SvectorDB Screenshot](/screenshots/svectordb.com.jpg)
SvectorDB
SvectorDB is a vector database built from the ground up for serverless applications. It is designed to be highly scalable, performant, and easy to use. SvectorDB can be used for a variety of applications, including recommendation engines, document search, and image search.
![VectorMind Screenshot](/screenshots/vectormind.io.jpg)
VectorMind
VectorMind is a generative AI platform that empowers users to create stunning vector graphic assets in seconds. With its state-of-the-art AI engine, users can generate high-quality, memorable designs by simply entering text descriptions. VectorMind offers a wide range of features, including a prompt template library, discoverable graphic collections, and various download options. It is perfect for hobbyists, professionals, and small teams looking to leverage advanced AI design tools.
![Superlinked Screenshot](/screenshots/superlinked.com.jpg)
Superlinked
Superlinked is a compute framework for your information retrieval and feature engineering systems, focused on turning complex data into vector embeddings. Vectors power most of what you already do online - hailing a cab, finding a funny video, getting a date, scrolling through a feed or paying with a tap. And yet, building production systems powered by vectors is still too hard! Our goal is to help enterprises put vectors at the center of their data & compute infrastructure, to build smarter and more reliable software.
![Vellum AI Screenshot](/screenshots/vellum.ai.jpg)
Vellum AI
Vellum AI is an AI platform that supports using Microsoft Azure hosted OpenAI models. It offers tools for prompt engineering, semantic search, prompt chaining, evaluations, and monitoring. Vellum enables users to build AI systems with features like workflow automation, document analysis, fine-tuning, Q&A over documents, intent classification, summarization, vector search, chatbots, blog generation, sentiment analysis, and more. The platform is backed by top VCs and founders of well-known companies, providing a complete solution for building LLM-powered applications.
![Trieve Screenshot](/screenshots/summary.arguflow.gg.jpg)
Trieve
Trieve is an AI-first infrastructure API that offers a comprehensive solution for search, recommendations, and RAG (retrieval-augmented generation). It combines advanced language models with tools for fine-tuning ranking and relevance, providing users with an all-in-one platform for enhancing search experiences across various categories. Trieve supports semantic vector search, full-text search using BM25 & SPLADE models, and hybrid search capabilities. The platform also enables users to tune and boost search results, manage ingestion and analytics effortlessly, and build unfair competitive advantages through search, discovery, and RAG experiences.
![Gista Screenshot](/screenshots/gista.co.jpg)
Gista
Gista is an AI-powered conversion agent that helps businesses turn more website visitors into leads. It is equipped with knowledge about your products and services and can offer value props, build an email list, and more. Gista is easy to set up and use, and it integrates with your favorite platforms.
![deepset Screenshot](/screenshots/deepset.ai.jpg)
deepset
deepset is an AI platform that offers enterprise-level products and solutions for AI teams. It provides deepset Cloud, a platform built with Haystack, enabling fast and accurate prototyping, building, and launching of advanced AI applications. The platform streamlines the AI application development lifecycle, offering processes, tools, and expertise to move from prototype to production efficiently. With deepset Cloud, users can optimize solution accuracy, performance, and cost, and deploy AI applications at any scale with one click. The platform also allows users to explore new models and configurations without limits, extending their team with access to world-class AI engineers for guidance and support.
![scikit-learn Screenshot](/screenshots/scikit-learn.org.jpg)
scikit-learn
Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
![Vectorize Screenshot](/screenshots/vectorize.io.jpg)
Vectorize
Vectorize is a fast, accurate, and production-ready AI tool that helps users turn unstructured data into optimized vector search indexes. It leverages Large Language Models (LLMs) to create copilots and enhance customer experiences by extracting natural language from various sources. With built-in support for top AI platforms and a variety of embedding models and chunking strategies, Vectorize enables users to deploy real-time vector pipelines for accurate search results. The tool also offers out-of-the-box connectors to popular knowledge repositories and collaboration platforms, making it easy to transform knowledge into AI-generated content.
20 - Open Source AI Tools
![curate-gpt Screenshot](/screenshots_githubs/monarch-initiative-curate-gpt.jpg)
curate-gpt
CurateGPT is a prototype web application and framework for performing general purpose AI-guided curation and curation-related operations over collections of objects. It allows users to load JSON, YAML, or CSV data, build vector database indexes for ontologies, and interact with various data sources like GitHub, Google Drives, Google Sheets, and more. The tool supports ontology curation, knowledge base querying, term autocompletion, and all-by-all comparisons for objects in a collection.
![marqo Screenshot](/screenshots_githubs/marqo-ai-marqo.jpg)
marqo
Marqo is more than a vector database, it's an end-to-end vector search engine for both text and images. Vector generation, storage and retrieval are handled out of the box through a single API. No need to bring your own embeddings.
![NeoGPT Screenshot](/screenshots_githubs/neokd-NeoGPT.jpg)
NeoGPT
NeoGPT is an AI assistant that transforms your local workspace into a powerhouse of productivity from your CLI. With features like code interpretation, multi-RAG support, vision models, and LLM integration, NeoGPT redefines how you work and create. It supports executing code seamlessly, multiple RAG techniques, vision models, and interacting with various language models. Users can run the CLI to start using NeoGPT and access features like Code Interpreter, building vector database, running Streamlit UI, and changing LLM models. The tool also offers magic commands for chat sessions, such as resetting chat history, saving conversations, exporting settings, and more. Join the NeoGPT community to experience a new era of efficiency and contribute to its evolution.
![vectordb-recipes Screenshot](/screenshots_githubs/lancedb-vectordb-recipes.jpg)
vectordb-recipes
This repository contains examples, applications, starter code, & tutorials to help you kickstart your GenAI projects. * These are built using LanceDB, a free, open-source, serverless vectorDB that **requires no setup**. * It **integrates into python data ecosystem** so you can simply start using these in your existing data pipelines in pandas, arrow, pydantic etc. * LanceDB has **native Typescript SDK** using which you can **run vector search** in serverless functions! This repository is divided into 3 sections: - Examples - Get right into the code with minimal introduction, aimed at getting you from an idea to PoC within minutes! - Applications - Ready to use Python and web apps using applied LLMs, VectorDB and GenAI tools - Tutorials - A curated list of tutorials, blogs, Colabs and courses to get you started with GenAI in greater depth.
![MyScaleDB Screenshot](/screenshots_githubs/myscale-MyScaleDB.jpg)
MyScaleDB
MyScaleDB is a SQL vector database optimized for AI applications, enabling developers to manage and process massive volumes of data efficiently. It offers fast and powerful vector search, filtered search, and SQL-vector join queries, making it fully SQL-compatible. MyScaleDB provides unmatched performance and scalability by leveraging cutting-edge OLAP database architecture and advanced vector algorithms. It is production-ready for AI applications, supporting structured data, text, vector, JSON, geospatial, and time-series data. MyScale Cloud offers fully-managed MyScaleDB with premium features on billion-scale data, making it cost-effective and simpler to use compared to specialized vector databases. Built on top of ClickHouse, MyScaleDB combines structured and vector search efficiently, ensuring high accuracy and performance in filtered search operations.
![myscaledb Screenshot](/screenshots_githubs/myscale-myscaledb.jpg)
myscaledb
MyScaleDB is a SQL vector database designed for scalable AI applications, enabling developers to efficiently manage and process massive volumes of data using familiar SQL. It offers fast and efficient vector search, filtered search, and SQL-vector join queries. MyScaleDB is fully SQL-compatible and production-ready for AI applications, providing unmatched performance and scalability through cutting-edge OLAP architecture and advanced vector algorithms. Built on top of ClickHouse, it combines structured and vectorized data management for high accuracy and speed in filtered searches.
![chromem-go Screenshot](/screenshots_githubs/philippgille-chromem-go.jpg)
chromem-go
chromem-go is an embeddable vector database for Go with a Chroma-like interface and zero third-party dependencies. It enables retrieval augmented generation (RAG) and similar embeddings-based features in Go apps without the need for a separate database. The focus is on simplicity and performance for common use cases, allowing querying of documents with minimal memory allocations. The project is in beta and may introduce breaking changes before v1.0.0.
![txtai Screenshot](/screenshots_githubs/neuml-txtai.jpg)
txtai
Txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. It combines vector indexes, graph networks, and relational databases to enable vector search with SQL, topic modeling, retrieval augmented generation, and more. Txtai can stand alone or serve as a knowledge source for large language models (LLMs). Key features include vector search with SQL, object storage, topic modeling, graph analysis, multimodal indexing, embedding creation for various data types, pipelines powered by language models, workflows to connect pipelines, and support for Python, JavaScript, Java, Rust, and Go. Txtai is open-source under the Apache 2.0 license.
![elasticsearch-labs Screenshot](/screenshots_githubs/elastic-elasticsearch-labs.jpg)
elasticsearch-labs
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.
![kdbai-samples Screenshot](/screenshots_githubs/KxSystems-kdbai-samples.jpg)
kdbai-samples
KDB.AI is a time-based vector database that allows developers to build scalable, reliable, and real-time applications by providing advanced search, recommendation, and personalization for Generative AI applications. It supports multiple index types, distance metrics, top-N and metadata filtered retrieval, as well as Python and REST interfaces. The repository contains samples demonstrating various use-cases such as temporal similarity search, document search, image search, recommendation systems, sentiment analysis, and more. KDB.AI integrates with platforms like ChatGPT, Langchain, and LlamaIndex. The setup steps require Unix terminal, Python 3.8+, and pip installed. Users can install necessary Python packages and run Jupyter notebooks to interact with the samples.
![vector-search-class-notes Screenshot](/screenshots_githubs/edoliberty-vector-search-class-notes.jpg)
vector-search-class-notes
The 'vector-search-class-notes' repository contains class materials for a course on Long Term Memory in AI, focusing on vector search and databases. The course covers theoretical foundations and practical implementation of vector search applications, algorithms, and systems. It explores the intersection of Artificial Intelligence and Database Management Systems, with topics including text embeddings, image embeddings, low dimensional vector search, dimensionality reduction, approximate nearest neighbor search, clustering, quantization, and graph-based indexes. The repository also includes information on the course syllabus, project details, selected literature, and contributions from industry experts in the field.
![llm-zoomcamp Screenshot](/screenshots_githubs/DataTalksClub-llm-zoomcamp.jpg)
llm-zoomcamp
LLM Zoomcamp is a free online course focusing on real-life applications of Large Language Models (LLMs). Over 10 weeks, participants will learn to build an AI bot capable of answering questions based on a knowledge base. The course covers topics such as LLMs, RAG, open-source LLMs, vector databases, orchestration, monitoring, and advanced RAG systems. Pre-requisites include comfort with programming, Python, and the command line, with no prior exposure to AI or ML required. The course features a pre-course workshop and is led by instructors Alexey Grigorev and Magdalena Kuhn, with support from sponsors and partners.
![Large-Language-Model-Notebooks-Course Screenshot](/screenshots_githubs/peremartra-Large-Language-Model-Notebooks-Course.jpg)
Large-Language-Model-Notebooks-Course
This practical free hands-on course focuses on Large Language models and their applications, providing a hands-on experience using models from OpenAI and the Hugging Face library. The course is divided into three major sections: Techniques and Libraries, Projects, and Enterprise Solutions. It covers topics such as Chatbots, Code Generation, Vector databases, LangChain, Fine Tuning, PEFT Fine Tuning, Soft Prompt tuning, LoRA, QLoRA, Evaluate Models, Knowledge Distillation, and more. Each section contains chapters with lessons supported by notebooks and articles. The course aims to help users build projects and explore enterprise solutions using Large Language Models.
![MetaAgent Screenshot](/screenshots_githubs/ZhihaoAIRobotic-MetaAgent.jpg)
MetaAgent
MetaAgent is a multi-agent collaboration platform designed to build, manage, and deploy multi-modal AI agents without the need for coding. Users can easily create AI agents by editing a yml file or using the provided UI. The platform supports features such as building LLM-based AI agents, multi-modal interactions with users using texts, audios, images, and videos, creating a company of agents for complex tasks like drawing comics, vector database and knowledge embeddings, and upcoming features like UI for creating and using AI agents, fine-tuning, and RLHF. The tool simplifies the process of creating and deploying AI agents for various tasks.
![TinyLLM Screenshot](/screenshots_githubs/jasonacox-TinyLLM.jpg)
TinyLLM
TinyLLM is a project that helps build a small locally hosted language model with a web interface using consumer-grade hardware. It supports multiple language models, builds a local OpenAI API web service, and serves a Chatbot web interface with customizable prompts. The project requires specific hardware and software configurations for optimal performance. Users can run a local language model using inference servers like vLLM, llama-cpp-python, and Ollama. The Chatbot feature allows users to interact with the language model through a web-based interface, supporting features like summarizing websites, displaying news headlines, stock prices, weather conditions, and using vector databases for queries.
![serverless-chat-langchainjs Screenshot](/screenshots_githubs/Azure-Samples-serverless-chat-langchainjs.jpg)
serverless-chat-langchainjs
This sample shows how to build a serverless chat experience with Retrieval-Augmented Generation using LangChain.js and Azure. The application is hosted on Azure Static Web Apps and Azure Functions, with Azure Cosmos DB for MongoDB vCore as the vector database. You can use it as a starting point for building more complex AI applications.
![superlinked Screenshot](/screenshots_githubs/superlinked-superlinked.jpg)
superlinked
Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.
![rag-web-ui Screenshot](/screenshots_githubs/rag-web-ui-rag-web-ui.jpg)
rag-web-ui
RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology. It helps enterprises and individuals build intelligent Q&A systems based on their own knowledge bases. By combining document retrieval and large language models, it delivers accurate and reliable knowledge-based question-answering services. The system is designed with features like intelligent document management, advanced dialogue engine, and a robust architecture. It supports multiple document formats, async document processing, multi-turn contextual dialogue, and reference citations in conversations. The architecture includes a backend stack with Python FastAPI, MySQL + ChromaDB, MinIO, Langchain, JWT + OAuth2 for authentication, and a frontend stack with Next.js, TypeScript, Tailwind CSS, Shadcn/UI, and Vercel AI SDK for AI integration. Performance optimization includes incremental document processing, streaming responses, vector database performance tuning, and distributed task processing. The project is licensed under the Apache-2.0 License and is intended for learning and sharing RAG knowledge only, not for commercial purposes.
![superduperdb Screenshot](/screenshots_githubs/SuperDuperDB-superduperdb.jpg)
superduperdb
SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.
20 - OpenAI Gpts
![Build a Brand Screenshot](/screenshots_gpts/g-ac8fkSk7r.jpg)
Build a Brand
Unique custom images based on your input. Just type ideas and the brand image is created.
![Beam Eye Tracker Extension Copilot Screenshot](/screenshots_gpts/g-D48Iu2zY3.jpg)
Beam Eye Tracker Extension Copilot
Build extensions using the Eyeware Beam eye tracking SDK
![Business Model Canvas Strategist Screenshot](/screenshots_gpts/g-lM6dmUVQm.jpg)
Business Model Canvas Strategist
Business Model Canvas Creator - Build and evaluate your business model
![League Champion Builder GPT Screenshot](/screenshots_gpts/g-3CURsOhEw.jpg)
League Champion Builder GPT
Build your own League of Legends Style Champion with Abilities, Back Story and Splash Art
![RenovaTecno Screenshot](/screenshots_gpts/g-g6dFw7dcN.jpg)
RenovaTecno
Your tech buddy helping you refurbish or build a PC from scratch, tailored to your needs, budget, and language.
![Gradle Expert Screenshot](/screenshots_gpts/g-3VN8IyOdc.jpg)
Gradle Expert
Your expert in Gradle build configuration, offering clear, practical advice.
![XRPL GPT Screenshot](/screenshots_gpts/g-Sjy2xMl6f.jpg)
XRPL GPT
Build on the XRP Ledger with assistance from this GPT trained on extensive documentation and code samples.