Superlinked
Overview of Superlinked
What is Superlinked?
Superlinked is a Python framework and cloud infrastructure designed for AI engineers. It helps in building high-performance search and recommendation applications by combining structured and unstructured data.
Key Features:
- Multi-modal Vectors: Combine text, images, and structured metadata into multi-modal vectors to fully describe entities in their complex context.
- Multi-objective Queries: Smoothly navigate the trade-off between multiple competing objectives like relevance, freshness, and popularity.
- Infrastructure as Code: Manage the compute layer between your data infrastructure and vector database through a simple Python SDK.
Use Cases:
- RAG (Retrieval Augmented Generation): Combine semantic relevance and document freshness to retrieve optimal document chunks.
- Semantic Search: Enhance search capabilities by understanding the context and meaning of queries.
- Recommendations: Improve recommendation systems by leveraging vector embeddings.
- Analytics: Perform advanced data analysis using vector representations.
How to use Superlinked?
- Experiment: Describe and load your data, construct indices, and run queries in-memory within a Python notebook.
- Deploy: Deploy your code on your computer or a cloud VM and connect it to your Vector DB.
- Use: Push entities to the auto-generated ingestion API and execute queries with query text and weight parameters using the auto-generated query API.
Why is Superlinked important?
Superlinked offers a reliable and efficient vector compute solution that puts vectors into production, making it easier to implement complex data-driven applications. It simplifies the process of combining different types of data (text, images, metadata) into unified vector representations, allowing for more effective semantic search, recommendations, and analytics.
Where can I use Superlinked?
Superlinked can be used in various industries and applications, including:
- E-commerce recommendation systems
- Enterprise retrieval and analytics
- RAG systems with LLMs
Best way to get started with Superlinked?
Start by exploring the documentation and examples provided on the Superlinked website and GitHub repository. The Python SDK allows you to experiment locally and then deploy your code to a cloud environment for production use.
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