If you want to automate the flow of data from many sources to an AI application, Airbyte is worth a look. It's an open-source data integration service geared for data engineers, AI engineers and analytics engineers. It can move data from more than 300 structured and unstructured sources to many destinations, with features like a Connector Builder for custom connectors, Extract Unstructured Data and Automated Schema Evolution. Airbyte can be deployed in a variety of ways and has strong security controls, so it's good for large-scale and small-scale data integration projects.
Another option is Morph, an AI-powered data assistant that helps you manage data and analyze it. It can pull data from multiple sources, analyze it without any programming, and then send the results to whatever platform you want. Morph can query, visualize and report data, and connect to a range of SQL databases. It has tiered pricing options, including a free tier and a Pro tier, so it should be useful for small businesses and larger enterprises.
If you want a more direct way to connect AI applications to data, Unbody is another option. It automates the flow from data sources to AI applications, supporting multiple AI models and different data formats. Unbody has features like a private AI assistant, AI-native content API and secure data handling, which means you can easily add AI abilities to a project with a single line of code. Unbody has tiered pricing options for different customers and projects.
Last, Dataloop is designed to accelerate AI application development by combining data curation, model management, pipeline orchestration and human feedback. It can handle large amounts of unstructured data from a variety of sources, automated preprocessing and strong security controls. Dataloop is designed to help teams work together, speed up development and provide a full suite of tools for deploying and managing AI models. It can handle a variety of unstructured data types and integrates with popular cloud computing platforms.