Tool Information
Baseplate is an AI tool that provides a backend for LLM (Language Model) apps, allowing users to embed and store documents, images, and other types of data. It offers high-performance retrieval workflows, ensuring accurate results regardless of the size, type, or domain of the data being searched. Baseplate simplifies the management of vectors, documents, and other data by offering an easy-to-use UI and API that handle embedding, storage, and version control, ensuring that data is always up-to-date and in sync. The tool introduces a unified hybrid database that enables users to store all the data in the same table as the images, links, and text that make their LLM App great. Designed to help teams build AI apps, Baseplate connects to data through an API and UI, making the process of wiring together a backend a simple one. Users can configure hybrid search with custom embeddings tuned for their data, and the tool allows them to prompt any LLM using data from their database. Baseplate's Multimodal LLM Responses APIs allow users to respond to their users with relevant and reliable thumbnails, links, sources, and more. Baseplate simplifies LLM Ops and helps level up AI products. The tool offers a free trial period as well as customer support through Discord and Twitter. Baseplate is recommended for data-centric businesses involved in storing and managing a vast amount of documents and data.
F.A.Q (19)
Baseplate is an AI tool that serves as a backend for Language Model (LLM) apps. It allows users to store and manage various types of data such as documents and images.
Baseplate offers a range of data management services. It provides a unified hybrid database where users can store and embed all their data, including images, links, and text. The tool takes care of embedding, storage, and version control, to keep the data always in-sync and up-to-date. It simplifies the management of vectors and documents via an easy-to-use UI and API.
Baseplate ensures accurate data search results through high-performance retrieval workflows and hybrid search with custom embeddings. These are tuned for individual user data, providing accurate results irrespective of the type, size, or domain of data being searched.
Baseplate simplifies the process of wiring together a backend by connecting to data through API and UI. It manages the embedding, storage, and version control, which allows user data to always remain synced and updated. It also has an App Builder feature that connects search results to a prompt.
Yes, you can store images and links in Baseplate's unified hybrid database. The database enables users to embed and store all their data in the same table as the images, links, and text.
Baseplate would be most beneficial for data-centric businesses or teams building AI apps, especially those involved in storing and managing a large amount of data and documents.
Yes, there is a free trial option for Baseplate as indicated on their website.
Baseplate handles customer support via Discord and Twitter platforms.
Baseplate’s Multimodal LLM Responses API is useful because it enables users to respond to their users with relevant and reliable thumbnails, links, sources, and more. This enhances user experience and interaction with the respective AI products by providing meaningful and context-appropriate responses.
On their website, it indicates you can store any type of document on Baseplate, but no specific types of documents are mentioned.
Yes, Baseplate does provide version control for stored data. It manages the embedding, storage, and version control so that the data is always synchronized and up-to-date.
Customers speak highly of Baseplate. According to two testimonials on their website, CEOs of companies using Baseplate praise it for aiding in delivering an excellent product experience and for simplifying backend management, respectively.
Baseplate's vector database management works by allowing users to edit their vectors either through the UI or programmatically. Versioning of data is provided to ensure that there's no stale data or duplicates.
Yes, Baseplate can be used for building AI apps. It was, in fact, designed for this purpose, providing a platform for teams to connect their data, configure a hybrid search, prompt any LLM with data from their database, and deploy their app.
In Baseplate, hybrid search works with custom embeddings that are tuned specifically for the user's data. This allows the search to return accurate results regardless of the type, size, or domain of the data being searched.
To connect your data to Baseplate, you can use either the UI or API offered by the tool. Baseplate handles all embedding, storage, and version control, keeping your data in sync and up-to-date.
The process to deploy an app with Baseplate involves a few clicks. You can collect logs, human feedback, and more using Baseplate Endpoints.
Baseplate's UI and API simplify data embedding and storage by taking care of these aspects along with version control. This ensures your data is always in-sync and up-to-date without the need for constant manual checks or updates.
Yes, Baseplate allows to prompt any LLM with data from the database. Connect search results to a prompt can be done through the App Builder feature.
Pros and Cons
Pros
- High-performance retrieval workflows
- Unified hybrid database
- Easy management of vectors
- API for connecting data
- UI for configuring data
- Version control feature
- Supports text
- images
- documents
- Simplified backend wiring
- Hybrid search with custom embeddings
- Prompt LLM with database data
- Facilitates app deployment
- Collects logs
- feedback via Endpoints
- Vector DB management like spreadsheet
- Versioning prevents stale data
- Multimodal LLM Responses APIs
- Free trial period offered
- Customer support via Discord
- Recommended for data-centric businesses
Cons
- Requires extensive backend knowledge
- Possible over-complication for smaller projects
- Limited customer support channels
- Specifically designed for LLM apps
- No offline mode
- Limited UI customization options
- Unified database may present data confusion
- Potential for stale data issues
- May not suit non-data-centric businesses
- No explicit support for non-English languages
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