Build, deploy, and scale production ML systems with Hopsworks. The Feature Store and MLOps platform for real-time AI, trusted by leading teams.
Hopsworks AI is praised for its robust feature set, particularly in managing machine learning models and large-scale data workflows, which is often highlighted in user discussions. However, there are limited explicit user reviews available, making it difficult to identify common complaints or pricing sentiment. Its overall reputation appears positive, especially among users emphasizing its innovative capabilities and ease of integration within existing tech stacks. Given the repetitive nature of social mentions, it's clear the platform generates focused interest, notably within the AI development community.
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Hopsworks AI is praised for its robust feature set, particularly in managing machine learning models and large-scale data workflows, which is often highlighted in user discussions. However, there are limited explicit user reviews available, making it difficult to identify common complaints or pricing sentiment. Its overall reputation appears positive, especially among users emphasizing its innovative capabilities and ease of integration within existing tech stacks. Given the repetitive nature of social mentions, it's clear the platform generates focused interest, notably within the AI development community.
Features
Use Cases
Industry
information technology & services
Employees
37
Funding Stage
Venture (Round not Specified)
Total Funding
$13.5M
2
npm packages
Pricing found: $0
Repository Audit Available
Deep analysis of logicalclocks/hopsworks — architecture, costs, security, dependencies & more
Yes, Hopsworks offers a free tier. Pricing found: $0
Key features include: Feature Store, AI Lakehouse, MLOps Platform, From Modern Data Stack to the Coding Data Stack (CDS): Hopsworks 5.0, Built for Quality, Instant Data, Infinite Compute., Real-time AI, Feature Freshness.
Hopsworks is commonly used for: Instant Data, Infinite Compute..
Hopsworks integrates with: Apache Kafka, Apache Spark, TensorFlow, PyTorch, Kubernetes, Airflow, Jupyter Notebooks, S3, BigQuery, Snowflake.

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