About Lantern

Lantern provides an open-source Postgres vector database and toolkit that enables developers to build production-ready AI applications with integrated vector and text search capabilities. It addresses the challenges of scaling database performance and search efficiency by allowing seamless indexing and embedding generation directly within Postgres.

```xml <problem> Building AI applications that require vector and text search capabilities often involves integrating separate vector databases or search engines with existing Postgres databases, creating complexity and hindering scalability. Managing indexing and embedding generation outside of Postgres can also lead to performance bottlenecks and increased operational overhead. </problem> <solution> Lantern provides an open-source Postgres extension and cloud service that enables developers to build production-ready AI applications directly within Postgres. The extension facilitates vector and text search, eliminating the need for separate systems. Lantern allows seamless indexing and embedding generation within Postgres, simplifying AI workflows and improving performance. It supports hybrid search, combining vector search and BM25 text search for enhanced results. </solution> <features> - Vector search with pgvector, supporting binary, scalar, and product compression - BM25 text search for relevant results, surpassing default Postgres full-text search - Hybrid search combining vector and text search using RRF - Serverless indexing for scalability without compromising database performance - Embedding generation and LLM integrations directly within Postgres using SQL - Support for over 20 embedding models and LLMs, including OpenAI and Cohere - Automatic vector and LLM column generation based on existing data - Integrations with SQL and ORMs like Sequelize, Knex, and Django </features> <target_audience> Lantern targets developers and companies building AI applications that require vector and text search capabilities, particularly those already using Postgres. </target_audience> <revenue_model> Lantern offers a free tier and a production tier starting at $44 per month, with increased compute, storage, automatic backups, point-in-time recovery, asynchronous tasks, and priority support. </revenue_model> ```

What does Lantern do?

Where is Lantern located?

Lantern is based in San Francisco, United States.

When was Lantern founded?

Lantern was founded in 2023.

How much funding has Lantern raised?

Lantern has raised 500000.

Location

San Francisco, United States

Founded

2023

Funding

500000

Employees

3 employees

Major Investors

Y Combinator, Eight Capital

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Lantern

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Executive Summary

lantern.dev 700+

Crunchbase

Founded 2023 – San Francisco, United States

Funding

Estimated Funding

$500K+

Major Investors

Y Combinator, Eight Capital

Team (<5)

No team information available.

Company Description

Problem

Building AI applications that require vector and text search capabilities often involves integrating separate vector databases or search engines with existing Postgres databases, creating complexity and hindering scalability. Managing indexing and embedding generation outside of Postgres can also lead to performance bottlenecks and increased operational overhead.

Solution

Lantern provides an open-source Postgres extension and cloud service that enables developers to build production-ready AI applications directly within Postgres. The extension facilitates vector and text search, eliminating the need for separate systems. Lantern allows seamless indexing and embedding generation within Postgres, simplifying AI workflows and improving performance. It supports hybrid search, combining vector search and BM25 text search for enhanced results.

Features

Vector search with pgvector, supporting binary, scalar, and product compression

BM25 text search for relevant results, surpassing default Postgres full-text search

Hybrid search combining vector and text search using RRF

Serverless indexing for scalability without compromising database performance

Embedding generation and LLM integrations directly within Postgres using SQL

Support for over 20 embedding models and LLMs, including OpenAI and Cohere

Automatic vector and LLM column generation based on existing data

Integrations with SQL and ORMs like Sequelize, Knex, and Django

Target Audience

Lantern targets developers and companies building AI applications that require vector and text search capabilities, particularly those already using Postgres.

Revenue Model

Lantern offers a free tier and a production tier starting at $44 per month, with increased compute, storage, automatic backups, point-in-time recovery, asynchronous tasks, and priority support.