Baseplate is a backend optimization platform that enables seamless integration of various data types, including documents and images, into LLM applications through a unified hybrid database. It ensures real-time data synchronization and high-performance retrieval workflows, allowing teams to build and deploy AI applications efficiently without the risk of stale data.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Building applications with Large Language Models (LLMs) requires integrating diverse data types, such as documents and images, which can be complex and lead to data synchronization issues. Traditional methods often result in stale data and inefficient retrieval workflows, hindering the performance and scalability of AI applications.
Solution
Baseplate offers a backend platform that simplifies the integration of various data types into LLM applications through a unified hybrid database. The platform provides tools for embedding, storing, and versioning data, ensuring real-time synchronization and up-to-date information. Baseplate enables high-performance retrieval workflows without requiring additional engineering effort, allowing teams to connect data via UI or API, configure hybrid search with custom embeddings, and prompt any LLM with data from the database. The platform also facilitates the deployment of applications with features for collecting logs and human feedback.
Target Audience
Baseplate is designed for AI product teams and developers looking to streamline the integration of data into LLM applications and improve the performance of their AI-powered products.
Features
- Unified hybrid database for embedding and storing documents, images, and other data types
- Real-time data synchronization and version control to prevent stale data issues
- Configurable hybrid search with custom embeddings optimized for various data domains
- UI and API for connecting data sources and managing data pipelines
- App Builder for connecting search results to LLM prompts
- Endpoints for deploying applications and collecting logs and feedback
- Multimodal LLM responses with relevant thumbnails, links, and sources