InfuseAI
- 2 profiles
- 3 categories
All Products & Services
PrimeHub is a on-premise machine learning platform that enables AI/ML teams to focus on their true productivity in a collaborative environment. PrimeHub helps administrators manage hardware resources, access control, group quota, datasets and more.
PipeRider is a light-weight data reliability toolkit using warehouse-native profiling so you can have a full understanding of your data. PipeRider will make your life easier by: * Building a data profile so you can easily understand your data * Creating test suggestions based on the profiling * Comparing data profile reports, so you track changes over time ** Made for the modern data team** For data engineers: ⚡ 2 min install & set-up 😌 Non-intrusive & open-source: install and use locally 💸 Fast & cheap: 100M rows & 8 columns (or 50M & 16 columns) takes only 18s to profile 📒 Cloud DataWarehouse native & auto-config for dbt For data analysts: * Never waste time on analyzing wrong data: collects various metadata metrics such as freshness, uniqueness, distribution... check all metrics * Communicate easily your data expectations by showing the report * Zero-config dbt integration
InfuseAI Reviews
Verified User in Information Technology and Services
One of the emerging solution for MLOps
Alfredo G.
IT Consultant at OracleA tool that manages data in a technological way
Verified User in Accounting
About
What is InfuseAI?
InfuseAI is a technology company specializing in MLOps solutions, aimed at streamlining and enhancing machine learning operations for organizations. Through its flagship platform, PrimeHub, InfuseAI offers tools that support data scientists and IT teams in managing their machine learning workflows efficiently—from experimentation to deployment and scaling. The platform is designed to be user-friendly, allowing integration with various data and computing environments, thereby promoting collaboration and productivity. InfuseAI caters to industries looking to leverage artificial intelligence effectively by providing robust support for the end-to-end machine learning lifecycle.
