Best AI tools for< Build Data Infrastructure >

Qubinets is a cloud data environment solutions platform that provides building blocks for building big data, AI, web, and mobile environments. It is an open-source, no lock-in, secured, and private platform that can be used on any cloud, including AWS, Digital Ocean, Google Cloud, and Microsoft Azure. Qubinets makes it easy to plan, build, and run data environments, and it streamlines and saves time and money by reducing the grunt work in setup and provisioning.

Cognee is an AI application that helps users build deterministic AI memory by perfecting exceptional AI apps with intelligent data management. It acts as a semantic memory layer, uncovering hidden connections within data and infusing it with company-specific language and principles. Cognee offers data ingestion and enrichment services, resulting in relevant data retrievals and lower infrastructure costs. The application is suitable for various industries, including customer engagement, EduTech, company onboarding, recruitment, marketing, and tourism.

Labelbox is a data factory platform that empowers AI teams to manage data labeling, train models, and create better data with internet scale RLHF platform. It offers an all-in-one solution comprising tooling and services powered by a global community of domain experts. Labelbox operates a global data labeling infrastructure and operations for AI workloads, providing expert human network for data labeling in various domains. The platform also includes AI-assisted alignment for maximum efficiency, data curation, model training, and labeling services. Customers achieve breakthroughs with high-quality data through Labelbox.

Looker is a business intelligence platform that offers embedded analytics and AI-powered BI solutions. Leveraging Google's AI-led innovation, Looker delivers intelligent BI by combining foundational AI, cloud-first infrastructure, industry-leading APIs, and a flexible semantic layer. It allows users to build custom data experiences, transform data into integrated experiences, and create deeply integrated dashboards. Looker also provides a universal semantic modeling layer for unified, trusted data sources and offers self-service analytics capabilities through Looker and Looker Studio. Additionally, Looker features Gemini, an AI-powered analytics assistant that accelerates analytical workflows and offers a collaborative and conversational user experience.

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.

Granica AI is a Training Data Platform designed to make data safe for use with AI while keeping it cost-efficient. It offers state-of-the-art accuracy, cost-efficient data optimization, data visibility insights, and cloud cost savings. The platform helps in protecting data privacy, optimizing data costs, and gaining data visibility for AI teams to achieve big results while minimizing privacy risk.

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.

Cerebium is a serverless AI infrastructure platform that allows teams to build, test, and deploy AI applications quickly and efficiently. With a focus on speed, performance, and cost optimization, Cerebium offers a range of features and tools to simplify the development and deployment of AI projects. The platform ensures high reliability, security, and compliance while providing real-time logging, cost tracking, and observability tools. Cerebium also offers GPU variety and effortless autoscaling to meet the diverse needs of developers and businesses.

WhiteBridge is an AI-powered online reputation management tool that helps individuals and businesses transform scattered online data into a coherent narrative of their digital identity. By finding, verifying, and structuring information about someone into insightful reports, WhiteBridge enables users to safeguard their reputation, understand prospects, prepare for pitches, hire wisely, and verify authenticity. The tool offers real-time validation, background analysis, and access to over 100 public data APIs to provide unmatched quality of information. WhiteBridge is designed for recruiters, sales reps, business owners, and privacy-conscious individuals to streamline background checks, build better connections, verify information, and safeguard personal data.

Sensay is a platform that specializes in creating digital AI Replicas, offering cutting-edge cloning technology to simplify the process of developing humanlike AI Replicas. These Replicas are designed to preserve and share wisdom, catering to various needs such as dementia care, custom solutions, education, and fan engagement. Sensay ensures the creation of personalized Replicas that mimic individual personalities for realistic interactions, with a focus on continuous learning and enhancing interaction quality over time. The platform also delves into ethical and philosophical implications, emphasizing privacy protection, consent, and the exploration of identity concepts.

Monterey AI is an AI-powered insights platform that helps businesses understand their customers' needs and build better products. It aggregates, triages, and analyzes user feedback, tickets, conversations, surveys, and transcripts to provide businesses with real-time insights into what their customers are saying and what they want. Monterey AI is used by businesses of all sizes, from startups to Fortune 20 companies, to improve their product development process and build better products that meet the needs of their customers.

Google Cloud is a suite of cloud computing services that runs on the same infrastructure as Google. Its services include computing, storage, networking, databases, machine learning, and more. Google Cloud is designed to make it easy for businesses to develop and deploy applications in the cloud. It offers a variety of tools and services to help businesses with everything from building and deploying applications to managing their infrastructure. Google Cloud is also committed to sustainability, and it has a number of programs in place to reduce its environmental impact.

DataRobot is a leading provider of AI cloud platforms. It offers a range of AI tools and services to help businesses build, deploy, and manage AI models. DataRobot's platform is designed to make AI accessible to businesses of all sizes, regardless of their level of AI expertise. DataRobot's platform includes a variety of features to help businesses build and deploy AI models, including: * A drag-and-drop interface that makes it easy to build AI models, even for users with no coding experience. * A library of pre-built AI models that can be used to solve common business problems. * A set of tools to help businesses monitor and manage their AI models. * A team of AI experts who can provide support and guidance to businesses using the platform.

Baseten is a machine learning infrastructure that provides a unified platform for data scientists and engineers to build, train, and deploy machine learning models. It offers a range of features to simplify the ML lifecycle, including data preparation, model training, and deployment. Baseten also provides a marketplace of pre-built models and components that can be used to accelerate the development of ML applications.

Domino Data Lab is an enterprise AI platform that enables users to build, deploy, and manage AI models across any environment. It fosters collaboration, establishes best practices, and ensures governance while reducing costs. The platform provides access to a broad ecosystem of open source and commercial tools, and infrastructure, allowing users to accelerate and scale AI impact. Domino serves as a central hub for AI operations and knowledge, offering integrated workflows, automation, and hybrid multicloud capabilities. It helps users optimize compute utilization, enforce compliance, and centralize knowledge across teams.

Neurochain AI is a decentralized AI-as-a-Service (DeAIAS) network that provides an innovative solution for building, launching, and using AI-powered decentralized applications (dApps). It offers a community-driven approach to AI development, incentivizing contributors with $NCN rewards. The platform aims to address challenges in the centralized AI landscape by democratizing AI development and leveraging global computing resources. Neurochain AI also features a community-powered content generation engine and is developing its own independent blockchain. The team behind Neurochain AI includes experienced professionals in infrastructure, cryptography, computer science, and AI research.

Outspeed is a platform for Realtime Voice and Video AI applications, providing networking and inference infrastructure to build fast, real-time voice and video AI apps. It offers tools for intelligence across industries, including Voice AI, Streaming Avatars, Visual Intelligence, Meeting Copilot, and the ability to build custom multimodal AI solutions. Outspeed is designed by engineers from Google and MIT, offering robust streaming infrastructure, low-latency inference, instant deployment, and enterprise-ready compliance with regulations such as SOC2, GDPR, and HIPAA.

Evervault provides developers with world-class infrastructure to solve complex data security and compliance problems in days, not months. It offers four simple primitives: Relay, Functions, UI Components, and Enclaves. These primitives can be used to build a variety of data security and compliance solutions, such as PCI DSS compliance, HIPAA compliance, and GDPR compliance. Evervault is secure by default, fundamentally configurable, and ultra-low latency. It is also compliant with PCI DSS, HIPAA, GDPR, and SOC2.

Backend.AI is an enterprise-scale cluster backend for AI frameworks that offers scalability, GPU virtualization, HPC optimization, and DGX-Ready software products. It provides a fast and efficient way to build, train, and serve AI models of any type and size, with flexible infrastructure options. Backend.AI aims to optimize backend resources, reduce costs, and simplify deployment for AI developers and researchers. The platform integrates seamlessly with existing tools and offers fractional GPU usage and pay-as-you-play model to maximize resource utilization.

Cargo is a revenue operations platform that helps businesses grow their revenue by providing them with the tools they need to segment, enrich, score, and assign leads, as well as automate their revenue operations. Cargo is designed to be easy to use, even for non-technical users, and it can be integrated with a variety of other business tools. With Cargo, businesses can improve their sales performance, increase their efficiency, and make better decisions about their revenue operations.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

DB-GPT is an open source AI native data app development framework with AWEL(Agentic Workflow Expression Language) and agents. It aims to build infrastructure in the field of large models, through the development of multiple technical capabilities such as multi-model management (SMMF), Text2SQL effect optimization, RAG framework and optimization, Multi-Agents framework collaboration, AWEL (agent workflow orchestration), etc. Which makes large model applications with data simpler and more convenient.

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.

superduper.io is a Python framework that integrates AI models, APIs, and vector search engines directly with existing databases. It allows hosting of models, streaming inference, and scalable model training/fine-tuning. Key features include integration of AI with data infrastructure, inference via change-data-capture, scalable model training, model chaining, simple Python interface, Python-first approach, working with difficult data types, feature storing, and vector search capabilities. The tool enables users to turn their existing databases into centralized repositories for managing AI model inputs and outputs, as well as conducting vector searches without the need for specialized databases.

Metaflow is a user-friendly library designed to assist scientists and engineers in developing and managing real-world data science projects. Initially created at Netflix, Metaflow aimed to enhance the productivity of data scientists working on diverse projects ranging from traditional statistics to cutting-edge deep learning. For further information, refer to Metaflow's website and documentation.

Lance is a modern columnar data format optimized for ML workflows and datasets. It offers high-performance random access, vector search, zero-copy automatic versioning, and ecosystem integrations with Apache Arrow, Pandas, Polars, and DuckDB. Lance is designed to address the challenges of the ML development cycle, providing a unified data format for collection, exploration, analytics, feature engineering, training, evaluation, deployment, and monitoring. It aims to reduce data silos and streamline the ML development process.

VulcanSQL is an Analytical Data API Framework for AI agents and data apps. It aims to help data professionals deliver RESTful APIs from databases, data warehouses or data lakes much easier and secure. It turns your SQL into APIs in no time!

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

VectorETL is a lightweight ETL framework designed to assist Data & AI engineers in processing data for AI applications quickly. It streamlines the conversion of diverse data sources into vector embeddings and storage in various vector databases. The framework supports multiple data sources, embedding models, and vector database targets, simplifying the creation and management of vector search systems for semantic search, recommendation systems, and other vector-based operations.

LakeSoul is a cloud-native Lakehouse framework that supports scalable metadata management, ACID transactions, efficient and flexible upsert operation, schema evolution, and unified streaming & batch processing. It supports multiple computing engines like Spark, Flink, Presto, and PyTorch, and computing modes such as batch, stream, MPP, and AI. LakeSoul scales metadata management and achieves ACID control by using PostgreSQL. It provides features like automatic compaction, table lifecycle maintenance, redundant data cleaning, and permission isolation for metadata.

The Oracle Cloud Infrastructure Data Science and AI services Examples repository provides demos, tutorials, and code examples showcasing various features of the OCI Data Science service and AI services. It offers tools for data scientists to develop and deploy machine learning models efficiently, with features like Accelerated Data Science SDK, distributed training, batch processing, and machine learning pipelines. Whether you're a beginner or an experienced practitioner, OCI Data Science Services provide the resources needed to build, train, and deploy models easily.

A Python package that helps Data and Analytics engineers render dbt projects in Apache Airflow DAGs. It enables teams to automatically render their dbt projects in a granular level, creating individual Airflow tasks for every model, seed, snapshot, and test within the dbt project. This allows for full control at the task-level, improving visibility and management of data models within the team.

Notes on AI state of the art, with a focus on generative and large language models. These are the "raw materials" for the https://lspace.swyx.io/ newsletter. This repo used to be called https://github.com/sw-yx/prompt-eng, but was renamed because Prompt Engineering is Overhyped. This is now an AI Engineering notes repo.

Guides in data engineering tasks with a focus on practical solutions.

I'm a Python and PyTorch expert with knowledge of ML infrastructure requirements ready to help you build and scale your ML projects.

Expert in Azure's latest services, including Application Insights, API Management, and more.

A Data Engineer assistant offering advice on data pipelines and data-related tasks.

Optimizes data systems and designs new data architectures.

Meet Tech Guru, your go-to AI for data engineering, coding expertise, and graph databases. Combining humor, reliability, and approachability to simplify tech with a personal touch.

I'm here to make your Streamlit apps go viral!

Build beautiful forms and surveys for free. Analyze the submission data to uncover insights.

A Pokémon competitive build expert, sourcing data from Smogon for single and double battles.

Data science co-pilot specializing in statistical modeling and machine learning.

A friendly data science coach offering practical, useful, and accurate advice.

Salam mən Alas Academy-nin Data Analitika üzrə Süni İntellekt mentoruyam. Mənə istənilən sualı verə bilərsiniz :)

I'm Richard, your engaging and recommendable data science expert.

Evolves with user interactions in data science.

Guides strategic data management to drive business insights.

Leading Big Data Analytics tool, blending advanced technology with OpenAI's expertise.

Helps build prospective career materials

This GPT lets you build PCRE Regular Expressions (for use the RegExp constructor).

I create React apps with Fireproof.

Friendly, professional data analysis expert.