Search…
⌃K
🍽

Baseplate (YC W23)

Backend-as-a-Service for LLM Apps
Baseplate is a backend optimized for LLM apps. Teams use our multimodal context database to build rich user experiences with LLMs. All from an interface as simple as a spreadsheet.
That means you don't have to maintain and manage separate databases for your vectors and regular data anymore!
Hybrid database for your regular data and your embeddings
Using Baseplate, a team can deploy a chat GPT app that responds with domain-specific information from documents, thumbnails, links, images, and more. (Who knows, maybe the next GPT model is multimodal too
🤫
)
​
Why would we need this?
In most applications, LLMs need to be connected to an ever changing set of data. It’s simple enough to parse and embed a few PDF’s. However, managing this data is tedious when you’re working with large, multimodal datasets that consistently need to be updated, re-indexed, and replaced.
Plus you’re likely managing multiple databases - one for vectors, and one for your other data. This gets painful really fast.
​
Key Features:
  1. 1.
    A flexible hybrid database. A single dataset in Baseplate can contain
    • Embeddings
    • Text
    • Code
    • Documents
    • Images
    • Links
  2. 2.
    Database management
    • Utilities for updating and managing vectors in bulk
    • Organize and segment your data intuitively
    • Work in the UI or programmatically via API
  3. 3.
    Smart Search
    • Choose an embedding model for your use case
    • Use keyword, semantic, or hybrid search based on your use case
    • Vector ranking based on more than just cosine similarity
      • Human Feedback, Last Updated, Last Accessed, etc.
  4. 4.
    Endpoints
    • Build, test, and deploy LLMs via API endpoints
    • Unlimited queries
    • Built-in utilities for human feedback, logging, & caching

​

​
Last modified 9d ago