Question: I'm looking for a solution that enables me to create custom data models and enrich my data for AI and analytics applications.

If you want to build your own data models and enrich your data for AI and analytics, Gretel Navigator is a good choice. The platform lets you generate, edit and amplify tabular data from scratch, which is useful for training foundation models, fine-tuning large language models, creating evaluation datasets and more. Its real-time inference API and SDK let you easily integrate it into data services, so it's good for improving data quality and reducing costs.

Another good choice is Dataloop, an AI development platform that handles data curation, model management, pipeline orchestration and human feedback. It can be used to manage and deploy AI models, automate data preprocessing and handle unstructured data like images, videos and text. It can speed up development while maintaining high security, which is important for AI app development.

If you want to make AI useful for business, Dataiku offers a full-featured platform for data preparation, machine learning, MLOps, collaboration and governance. It's good for different teams and industries, letting you build, deploy and operate machine learning models securely and efficiently. Dataiku is a Leader in the Gartner Magic Quadrant for Data Science & ML Platforms, so you can trust it to deliver good AI and analytics results.

Last, MOSTLY AI offers a synthetic data generation platform powered by GenAI that lets companies generate and explore tabular data without having to write code. It has a natural language interface for data exploration and analysis, and it's designed for enterprise customers with strong security and compliance certifications. It's good for data sharing, AI/ML development, self-service analytics and testing & QA, with pricing that scales to suit different needs.