Weaviate supercharges their data engineers with Superblocks

About Weaviate

Weaviate is an open-source, AI-native vector database. It lets users store data as vectors—enabling fast, semantic search and retrieval of unstructured information such as text, images, and more. 

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By leveraging machine learning models, Weaviate’s vector-based approach allows for highly relevant and context-aware search results, making it ideal for tasks like recommendation systems, Retrieval Augmented Generation (RAG) applications, and natural language search.

Weaviate and Superblocks 

Weaviate’s data engineering team specializes in analytics and data manipulation, frequently using Python, Matlab, and Jupyter alongside Google BigQuery. Seeking a way to build full-stack applications without taking on an entirely new skill set, they began exploring low-code platforms.

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After receiving a recommendation from a sales engineer who had successfully used Superblocks at Rockset, the team evaluated the platform and ultimately chose it for its robust capabilities and the simplicity of its App Builder. With Superblocks, they can quickly build sophisticated data applications that leverage Weaviate’s vector search and RAG functionalities for both internal and sales demo use cases. Just as importantly, Superblocks’ low learning curve allows anyone on the team to adopt the platform without needing front-end web development skills.

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Looking forward 

Weaviate’s Data and Solutions Engineering teams plan to use Superblocks to drive key initiatives and enhance day-to-day operations across the organization. For example:

• Streamlining sales operations with custom dashboards that integrate intent data, customer information, HubSpot, Slack, and more.
• Accelerating cross-functional efforts by centralizing tracking and visibility for large, multi-team projects—such as migrating existing customers to the latest licensing models.
• Minimizing infrastructure costs with DevOps-focused dashboards that monitor usage and spending, enabling informed cost-reduction decisions.
• Saving engineering time by removing the need to learn new tools or technologies; instead, engineers can build everything directly within Superblocks.

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