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What is Weaviate?

Weaviate is an open-source, AI-native database that helps organizations build and ship AI applications on a single, scalable foundation. It stores data objects alongside the vector embeddings produced by your chosen machine learning models and scales smoothly to billions of records. Teams can supply their own vectors or use Weaviate's built-in vectorization, then query their data through vector, keyword, and hybrid search to surface the most relevant results, even with complex filters. By integrating with leading large language models, Weaviate makes it straightforward to build retrieval-augmented generation, grounded question answering, and intelligent search over proprietary data. Beyond core retrieval, Weaviate offers a growing platform: the Query Agent converts natural-language questions into precise, cited queries; Engram provides managed memory that lets AI agents retain context over time; and Weaviate Embeddings handles vectorization as a managed service. Organizations can self-host under an open-source license or adopt fully managed Weaviate Cloud on AWS, GCP, or Azure, with SOC 2 Type II compliance, multi-tenancy, replication, and role-based access control. From semantic search and recommendations to agentic automation, Weaviate turns business data into AI-powered products.

What is Superlinked?

Incorporate semantic relevance with user feedback to efficiently pinpoint the most valuable document segments within your retrieval-augmented generation framework. Furthermore, combine semantic relevance with the recency of documents in your search engine, recognizing that newer information can often be more accurate. Develop a dynamic, customized e-commerce product feed that leverages user vectors derived from interactions with SKU embeddings. Investigate and categorize behavioral clusters of your customers using a vector index stored in your data warehouse. Carefully structure and import your data, utilize spaces for building your indices, and perform queries—all executed within a Python notebook to keep the entire process in-memory, ensuring both efficiency and speed. This methodology not only streamlines data retrieval but also significantly enhances user experience through personalized recommendations, ultimately leading to improved customer satisfaction. By continuously refining these processes, you can maintain a competitive edge in the evolving digital landscape.

Media

Media

Integrations Supported

AWS Marketplace
Azure Marketplace
Boomi
Composio
Confluent
Context Data
Databricks
Dynamiq
Firecrawl
FriendliAI
Gemini CLI
GitHub
GitHub Copilot
Haystack
LangChain
LlamaIndex
Mistral AI
OpenAI
Snowflake
n8n

API Availability

Has API

API Availability

Pricing Information

Free
Open source (free); free Weaviate Cloud tier; paid Cloud plans from $45/mo.
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Weaviate

Date Founded

2019

Company Location

The Netherlands

Company Website

weaviate.io

Company Facts

Organization Name

Superlinked

Date Founded

2021

Company Location

United States

Company Website

superlinked.com

Categories and Features

AI Memory Layers

Not specified

Context Engineering

Not specified

Vector Databases

Not specified

Categories and Features

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