MindsDB is an open-source tool that integrates various artificial intelligence (AI) models with traditional databases or other data management systems, enabling easy creation and deployment of new AI-based solutions. With its intuitive interface and broad compatibility with popular data sources, MindsDB facilitates the implementation of advanced machine learning models without requiring deep technical knowledge. The only prerequisite is familiarity with the syntax of popular SQL.

Furthermore, MindsDB can be used for sales forecasting, fraud detection, customer sentiment analysis, and product offer personalization, making it a versatile tool for various industries. By automating ML processes and easily integrating with existing systems, MindsDB significantly speeds up and simplifies AI deployment in business.

If you are interested in artificial intelligence, also check out our articles on OpenAI API and how the largest brands in the world use AI.

Basic information about MindsDB

MindsDB was founded by Jorge Torres and Adam Carrigan in 2017. In 2023, after six years of operation, the company's value was estimated at $160 million! In 2024, MindsDB was listed as one of the most innovative companies in the AI industry by Fast Company.

How does MindsDB work?

MindsDB works by integrating AI with existing data sources, such as MySQL, PostgreSQL, MariaDB, ClickHouse, or Elasticsearch. This allows users to create, train, and deploy machine learning (ML) models without leaving their favorite database tools and SQL language. Users can work directly on the data stored in these databases.

Source: MindsDB

Key features of MindsDB

• Simple interface: MindsDB offers a simple interface that allows users to train models directly from SQL or through other tools, such as Jupyter Notebooks.
• Automated learning process: MindsDB automatically handles many technical aspects of model building, such as feature selection, data preprocessing, and model evaluation.
• Real-time predictions: With integration with databases, users can make real-time predictions that are integrated with their existing database systems.
• Support for various data types: MindsDB supports a variety of data types, including numerical, text, and time series data.

Here are some of the main benefits of using MindsDB:

• Unified AI deployment and management: MindsDB integrates directly with the database, data warehouse, or data stream. This eliminates the need to build and maintain complex data pipelines or separate AI/ML deployment systems.
• Automated AI workflows: MindsDB automates the entire AI workflow, executing it based on time or event triggers. There is no need to create custom automation logic to get predictions, move data, or (re)train models.
• Turning every developer into an AI engineer: MindsDB allows developers to leverage common SQL skills, speeding up AI deployment in teams and departments. As a result, every developer becomes an AI engineer.
• Increased scalability and performance: Whether using a private cloud or a managed MindsDB service, this tool allows for efficient processing of large AI/ML workloads. MindsDB can scale to meet your needs, ensuring optimal performance and speed.

Source: MindsDB

Implementation example - Domuso

MindsDB publishes interesting case studies on its website. One of them, Domuso, precisely calculates the savings achieved by a MindsDB user after implementing the platform.

Domuso is a modern financial platform offering payment processing solutions for multi-family properties. To improve its services, it implemented a Machine Learning (ML) project with the help of MindsDB. MindsDB enabled quick and easy deployment of the ML project, eliminating the need to build new pipelines each time. Thanks to AutoML, forecasts were developed and deployed into production by the existing Domuso team. The new ML features introduced by Domuso increased customer numbers and user conversion.

As a result, Domuso was able to accurately predict whether a rent payment would be returned due to insufficient funds, reducing chargebacks by $95,000 within two months. Annual savings from using ML amounted to $500,000.

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