Best AI tools for< Manage Data Indexing >
20 - AI tool Sites
Encord
Encord is a leading data development platform designed for computer vision and multimodal AI teams. It offers a comprehensive suite of tools to manage, clean, and curate data, streamline labeling and workflow management, and evaluate AI model performance. With features like data indexing, annotation, and active model evaluation, Encord empowers users to accelerate their AI data workflows and build robust models efficiently.
Ranked
Ranked is an affordable SEO service that offers white label solutions for businesses and agencies. They provide human-written blog content, managed optimization, genuine backlinks, and leading SEO software. Their services are fully managed and structured for intent and engagement. Ranked utilizes AI engines for analysis, research, and outreach to deliver data-driven work and improve in-house productivity. However, they do not use AI for writing content due to inconsistent indexing on Google.
Ragie
Ragie is a fully managed RAG-as-a-Service platform designed for developers. It offers easy-to-use APIs and SDKs to help developers get started quickly, with advanced features like LLM re-ranking, summary index, entity extraction, flexible filtering, and hybrid semantic and keyword search. Ragie allows users to connect directly to popular data sources like Google Drive, Notion, Confluence, and more, ensuring accurate and reliable information delivery. The platform is led by Craft Ventures and offers seamless data connectivity through connectors. Ragie simplifies the process of data ingestion, chunking, indexing, and retrieval, making it a valuable tool for AI applications.
KERV Solutions
KERV is an AI-powered video and creative technology company that offers ad performance solutions, publisher revenue opportunities, in-show monetization solutions, and data and measurement services. Their patented image recognition and product correlation technology enable deeper relationships between publishers, brands, and consumers. KERV's AI technology makes any video explorable and shoppable with unrivaled speed and precision, delivering real business outcomes. They provide intelligent video solutions, active attention indexing, greater speed and precision, 1st party data insights, and brand safety measures.
500 supabaseUrl
500 supabaseUrl is a cloud-based database service that provides a fully managed, scalable, and secure way to store and manage data. It is designed to be easy to use, with a simple and intuitive interface that makes it easy to create, manage, and query databases. 500 supabaseUrl is also highly scalable, so it can handle even the most demanding workloads. And because it is fully managed, you don't have to worry about the underlying infrastructure or maintenance tasks.
One Data
One Data is an AI-powered data product builder that offers a comprehensive solution for building, managing, and sharing data products. It bridges the gap between IT and business by providing AI-powered workflows, lifecycle management, data quality assurance, and data governance features. The platform enables users to easily create, access, and share data products with automated processes and quality alerts. One Data is trusted by enterprises and aims to streamline data product management and accessibility through Data Mesh or Data Fabric approaches, enhancing efficiency in logistics and supply chains. The application is designed to accelerate business impact with reliable data products and support cost reduction initiatives with advanced analytics and collaboration for innovative business models.
Metaflow
Metaflow is an open-source framework for building and managing real-life ML, AI, and data science projects. It makes it easy to use any Python libraries for models and business logic, deploy workflows to production with a single command, track and store variables inside the flow automatically for easy experiment tracking and debugging, and create robust workflows in plain Python. Metaflow is used by hundreds of companies, including Netflix, 23andMe, and Realtor.com.
Dot Group Data Advisory
Dot Group is an AI-powered data advisory and solutions platform that specializes in effective data management. They offer services to help businesses maximize the potential of their data estate, turning complex challenges into profitable opportunities using AI technologies. With a focus on data strategy, data engineering, and data transport, Dot Group provides innovative solutions to drive better profitability for their clients.
Columns
Columns is an AI tool designed to automate data storytelling. It helps users in creating compelling narratives and visualizations from their data without the need for manual intervention. With Columns, users can easily transform raw data into engaging stories, making data analysis more accessible and impactful. The tool offers a user-friendly interface and a range of customization options to tailor the storytelling process to individual needs.
Walter Shields Data Academy
Walter Shields Data Academy is an AI-powered platform offering premium training in SQL, Python, and Excel. With over 200,000 learners, it provides curated courses from bestselling books and LinkedIn Learning. The academy aims to revolutionize data expertise and empower individuals to excel in data analysis and AI technologies.
MineOS
MineOS is an automation-driven platform that focuses on privacy, security, and compliance. It offers a comprehensive suite of tools and solutions to help businesses manage their data privacy needs efficiently. By leveraging AI and special discovery methods, MineOS adapts unique data processes to universal privacy standards seamlessly. The platform provides features such as data mapping, AI governance, DSR automations, consent management, and security & compliance solutions to ensure data visibility and governance. MineOS is recognized as the industry's #1 rated data governance platform, offering cost-effective control of data systems and centralizing data subject request handling.
DVC
DVC is an open-source platform for managing machine learning data and experiments. It provides a unified interface for working with data from various sources, including local files, cloud storage, and databases. DVC also includes tools for versioning data and experiments, tracking metrics, and automating compute resources. DVC is designed to make it easy for data scientists and machine learning engineers to collaborate on projects and share their work with others.
RIDO Protocol
RIDO Protocol is a decentralized data protocol that allows users to extract value from their personal data in Web2 and Web3. It provides users with a variety of features, including programmable data generation, programmable access control, and cross-application data sharing. RIDO also has a data marketplace where users can list or offer their data information and ownership. Additionally, RIDO has a DataFi protocol which promotes the flowing of data information and value.
Velotix
Velotix is an AI-powered data security platform that offers groundbreaking visual data security solutions to help organizations discover, visualize, and use their data securely and compliantly. The platform provides features such as data discovery, permission discovery, self-serve data access, policy-based access control, AI recommendations, and automated policy management. Velotix aims to empower enterprises with smart and compliant data access controls, ensuring data integrity and compliance. The platform helps organizations gain data visibility, control access, and enforce policy compliance, ultimately enhancing data security and governance.
OneTrust
OneTrust is a Trust Intelligence Cloud Solutions platform that leverages data and artificial intelligence to drive trusted innovation across privacy, security, and ethics initiatives. It offers a comprehensive suite of solutions for privacy management, data discovery, security, consent and preferences, AI governance, technology risk and compliance, compliance automation, third-party risk, and ethics program management. With over 14,000 customers worldwide, OneTrust helps organizations manage risk, ensure compliance, and build trust through responsible data and AI usage.
Superjoin
Superjoin is an AI-powered tool that allows users to automatically pull data from various tools into Google Sheets without the need for writing any code. It offers features like one-click connectors, auto-refresh schedules, data preview, and the ability to send report screenshots to Slack and Email. Superjoin is loved by thousands of users across hundreds of companies for its efficiency in automating workflows and data management.
SID
SID is a data ingestion, storage, and retrieval pipeline that provides real-time context for AI applications. It connects to various data sources, handles authentication and permission flows, and keeps information up-to-date. SID's API allows developers to retrieve the right piece of data for a given task, enabling them to build AI apps that are fast, accurate, and scalable. With SID, developers can focus on building their products and leave the data management to SID.
Keep AI
Keep AI is an innovative platform that enables businesses to automate data entry and receipt storage by leveraging AI technology. By sending receipts to Keep AI via email, organizations can eliminate manual data entry tasks and benefit from reliable automation, human-assisted accuracy, seamless data output, secure cloud storage, and efficient integration. The platform has received positive reviews from various businesses, highlighting its efficiency and time-saving capabilities.
DagsHub
DagsHub is an open source data science collaboration platform that helps AI teams build better models and manage data projects. It provides a central location for data, code, experiments, and models, making it easy for teams to collaborate and track their progress. DagsHub also integrates with a variety of popular data science tools and frameworks, making it a powerful tool for data scientists and machine learning engineers.
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.
20 - Open Source AI Tools
GraphRAG-Local-UI
GraphRAG Local with Interactive UI is an adaptation of Microsoft's GraphRAG, tailored to support local models and featuring a comprehensive interactive user interface. It allows users to leverage local models for LLM and embeddings, visualize knowledge graphs in 2D or 3D, manage files, settings, and queries, and explore indexing outputs. The tool aims to be cost-effective by eliminating dependency on costly cloud-based models and offers flexible querying options for global, local, and direct chat queries.
cognita
Cognita is an open-source framework to organize your RAG codebase along with a frontend to play around with different RAG customizations. It provides a simple way to organize your codebase so that it becomes easy to test it locally while also being able to deploy it in a production ready environment. The key issues that arise while productionizing RAG system from a Jupyter Notebook are: 1. **Chunking and Embedding Job** : The chunking and embedding code usually needs to be abstracted out and deployed as a job. Sometimes the job will need to run on a schedule or be trigerred via an event to keep the data updated. 2. **Query Service** : The code that generates the answer from the query needs to be wrapped up in a api server like FastAPI and should be deployed as a service. This service should be able to handle multiple queries at the same time and also autoscale with higher traffic. 3. **LLM / Embedding Model Deployment** : Often times, if we are using open-source models, we load the model in the Jupyter notebook. This will need to be hosted as a separate service in production and model will need to be called as an API. 4. **Vector DB deployment** : Most testing happens on vector DBs in memory or on disk. However, in production, the DBs need to be deployed in a more scalable and reliable way. Cognita makes it really easy to customize and experiment everything about a RAG system and still be able to deploy it in a good way. It also ships with a UI that makes it easier to try out different RAG configurations and see the results in real time. You can use it locally or with/without using any Truefoundry components. However, using Truefoundry components makes it easier to test different models and deploy the system in a scalable way. Cognita allows you to host multiple RAG systems using one app. ### Advantages of using Cognita are: 1. A central reusable repository of parsers, loaders, embedders and retrievers. 2. Ability for non-technical users to play with UI - Upload documents and perform QnA using modules built by the development team. 3. Fully API driven - which allows integration with other systems. > If you use Cognita with Truefoundry AI Gateway, you can get logging, metrics and feedback mechanism for your user queries. ### Features: 1. Support for multiple document retrievers that use `Similarity Search`, `Query Decompostion`, `Document Reranking`, etc 2. Support for SOTA OpenSource embeddings and reranking from `mixedbread-ai` 3. Support for using LLMs using `Ollama` 4. Support for incremental indexing that ingests entire documents in batches (reduces compute burden), keeps track of already indexed documents and prevents re-indexing of those docs.
azure-search-openai-demo
This sample demonstrates a few approaches for creating ChatGPT-like experiences over your own data using the Retrieval Augmented Generation pattern. It uses Azure OpenAI Service to access a GPT model (gpt-35-turbo), and Azure AI Search for data indexing and retrieval. The repo includes sample data so it's ready to try end to end. In this sample application we use a fictitious company called Contoso Electronics, and the experience allows its employees to ask questions about the benefits, internal policies, as well as job descriptions and roles.
pgvecto.rs
pgvecto.rs is a Postgres extension written in Rust that provides vector similarity search functions. It offers ultra-low-latency, high-precision vector search capabilities, including sparse vector search and full-text search. With complete SQL support, async indexing, and easy data management, it simplifies data handling. The extension supports various data types like FP16/INT8, binary vectors, and Matryoshka embeddings. It ensures system performance with production-ready features, high availability, and resource efficiency. Security and permissions are managed through easy access control. The tool allows users to create tables with vector columns, insert vector data, and calculate distances between vectors using different operators. It also supports half-precision floating-point numbers for better performance and memory usage optimization.
LangChain-Udemy-Course
LangChain-Udemy-Course is a comprehensive course directory focusing on LangChain, a framework for generative AI applications. The course covers various aspects such as OpenAI API usage, prompt templates, Chains exploration, callback functions, memory techniques, RAG implementation, autonomous agents, hybrid search, LangSmith utilization, microservice architecture, and LangChain Expression Language. Learners gain theoretical knowledge and practical insights to understand and apply LangChain effectively in generative AI scenarios.
cosdata
Cosdata is a cutting-edge AI data platform designed to power the next generation search pipelines. It features immutability, version control, and excels in semantic search, structured knowledge graphs, hybrid search capabilities, real-time search at scale, and ML pipeline integration. The platform is customizable, scalable, efficient, enterprise-grade, easy to use, and can manage multi-modal data. It offers high performance, indexing, low latency, and high requests per second. Cosdata is designed to meet the demands of modern search applications, empowering businesses to harness the full potential of their data.
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.
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.
Nucleoid
Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.
videodb-python
VideoDB Python SDK allows you to interact with the VideoDB serverless database. Manage videos as intelligent data, not files. It's scalable, cost-efficient & optimized for AI applications and LLM integration. The SDK provides functionalities for uploading videos, viewing videos, streaming specific sections of videos, searching inside a video, searching inside multiple videos in a collection, adding subtitles to a video, generating thumbnails, and more. It also offers features like indexing videos by spoken words, semantic indexing, and future indexing options for scenes, faces, and specific domains like sports. The SDK aims to simplify video management and enhance AI applications with video data.
redbox
Redbox is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License. Security measures are in place to ensure user data privacy and considerations are being made to make the core-api secure.
wikipedia-semantic-search
This repository showcases a project that indexes millions of Wikipedia articles using Upstash Vector. It includes a semantic search engine and a RAG chatbot SDK. The project involves preparing and embedding Wikipedia articles, indexing vectors, building a semantic search engine, and implementing a RAG chatbot. Key features include indexing over 144 million vectors, multilingual support, cross-lingual semantic search, and a RAG chatbot. Technologies used include Upstash Vector, Upstash Redis, Upstash RAG Chat SDK, SentenceTransformers, and Meta-Llama-3-8B-Instruct for LLM provider.
redbox-copilot
Redbox Copilot is a retrieval augmented generation (RAG) app that uses GenAI to chat with and summarise civil service documents. It increases organisational memory by indexing documents and can summarise reports read months ago, supplement them with current work, and produce a first draft that lets civil servants focus on what they do best. The project uses a microservice architecture with each microservice running in its own container defined by a Dockerfile. Dependencies are managed using Python Poetry. Contributions are welcome, and the project is licensed under the MIT License.
free-for-life
A massive list including a huge amount of products and services that are completely free! β Star on GitHub β’ π€ Contribute # Table of Contents * APIs, Data & ML * Artificial Intelligence * BaaS * Code Editors * Code Generation * DNS * Databases * Design & UI * Domains * Email * Font * For Students * Forms * Linux Distributions * Messaging & Streaming * PaaS * Payments & Billing * SSL
second-brain-agent
The Second Brain AI Agent Project is a tool designed to empower personal knowledge management by automatically indexing markdown files and links, providing a smart search engine powered by OpenAI, integrating seamlessly with different note-taking methods, and enhancing productivity by accessing information efficiently. The system is built on LangChain framework and ChromaDB vector store, utilizing a pipeline to process markdown files and extract text and links for indexing. It employs a Retrieval-augmented generation (RAG) process to provide context for asking questions to the large language model. The tool is beneficial for professionals, students, researchers, and creatives looking to streamline workflows, improve study sessions, delve deep into research, and organize thoughts and ideas effortlessly.
SuperKnowa
SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.
20 - OpenAI Gpts
π Data Privacy for PI & Security Firms π
Private Investigators and Security Firms, given the nature of their work, handle highly sensitive information and must maintain strict confidentiality and data privacy standards.
π Data Privacy for Watch & Jewelry Designers π
Watchmakers and Jewelry Designers, high-end businesses dealing with valuable items and personal details of clients, making data privacy and security paramount.
π Data Privacy for Event Management π
Data Privacy for Event Management and Ticketing Services handle personal data such as names, contact details, and payment information for event registrations and ticket purchases.
DataKitchen DataOps and Data Observability GPT
A specialist in DataOps and Data Observability, aiding in data management and monitoring.
Data Governance Advisor
Ensures data accuracy, consistency, and security across organization.
π Data Privacy for Home Inspection & Appraisal π
Home Inspection and Appraisal Services have access to personal property and related information, requiring them to be vigilant about data privacy.
π Data Privacy for Freelancers & Independents π
Freelancers and Independent Consultants, individuals in these roles often handle client data, project specifics, and personal contact information, requiring them to be vigilant about data privacy.
π Data Privacy for Architecture & Construction π
Architecture and Construction Firms handle sensitive project data, client information, and architectural plans, necessitating strict data privacy measures.
π Data Privacy for Real Estate Agencies π
Real Estate Agencies and Brokers deal with personal data of clients, including financial information and preferences, requiring careful handling and protection of such data.
π Data Privacy for Spa & Beauty Salons π
Spa and Beauty Salons collect Customer inforation, including personal details and treatment records, necessitating a high level of confidentiality and data protection.
Data Engineer Consultant
Guides in data engineering tasks with a focus on practical solutions.
Data Architect
Database Developer assisting with SQL/NoSQL, architecture, and optimization.
Snowflake Copilot
Your personal Snowflake assistant and copilot with a focus on efficient, secure, and scalable data warehousing. Trained with the latest knowledge and docs.