Simplify Vector Storage, Retrieval, & Embedding Operations
We are thrilled to announce a new addition to the Qwak platform, the Qwak Vector Store, your end-to-end solution for vector database and embedding needs.
What is Qwak Vector Store?
Qwak Vector Store simplifies your vector storage, retrieval, and embedding operations.
At Qwak, we enable data science teams to focus on what they do best by eliminating the burden of infrastructure management. We handle everything for you, from scaling and data ingestion to embedding model deployment.
With just a simple click, you can effortlessly deploy any embedding model and begin ingesting data into vectors.
Read more about building production grade vector search in our blog post.
Real-World Use Cases
Vector databases have been mainly used for similarity search, in cases such as finding product recommendations.
The rise of Large Language Models (LLMs) have brought vector stores into the spotlight, particularly for Retrieval-Augmented Generation (RAG) use cases.
RAG helps improve conversational interfaces and achieve quality responses from LLMs. By ingesting your own data in to Qwak Vector Store you can add context-relevant information to user queries for more accurate and relevant LLM responses.
Why Use Qwak Vector Store?
Effortless Vector Storage: Say goodbye to the complexities of managing vector data by easily generating embedding, ingesting data and searching at any scale.
Bring Your Own Model: Use any custom embedding models for data ingestion and retrieval.
Managed Data Ingestion: Connect any data source and configure vector ingestion data pipelines, periodically updating and refreshing data by your needs.
Get Started with Qwak Vector Store Today
We believe that managing vector data should be accessible and straightforward.
That's why we're excited to invite you to explore the Qwak Vector Store for yourself.