If you're looking for a way to automate data extraction and automate model deployment for quicker AI adoption, Vue.ai is a good option. This enterprise AI platform is geared for fast deployment, with tools like AI-led Rapid Rollouts for automated data extraction and model selection, and Perfectly Landed Implementation for standardized data and model deployment. It's geared for retail, finance and insurance, with tools for KYC data extraction, product tagging and customer data taxonomy creation.
Another good option is Dataloop, which handles data curation, model management, pipeline orchestration and human feedback to speed up AI application development. It includes automated preprocessing and embeddings for unstructured data, advanced model management and pipeline orchestration for visualizing and automating workflows. Dataloop supports a variety of data types, including images, videos and text, and is designed to improve collaboration and speed up development, with strong security controls that meet major standards.
DataRobot AI Platform also offers a broad foundation for building and deploying AI solutions quickly. It converges generative and predictive workflows, ensuring fast innovation and deep ecosystem integration with multiple cloud environments. The platform is a leader in the Gartner Magic Quadrant for Data Science and Machine Learning Platforms, with features that help you deploy 75% faster and achieve 2.7X higher analytics productivity.
For a no-code approach, Obviously AI offers a platform that automates data science workflows so you can build and deploy machine learning models without heavy coding. It supports a variety of use cases like classification, regression and time series forecasting, and integrates with tools like Zapier, Airtable and Salesforce. This platform's automated model monitoring and real-time API integration make it a good option for improving decision-making across different business functions.