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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 CMEM Cloud?

CMEM Cloud functions as the connective synchronization layer for claude-mem, facilitating universal memory access for AI agents through a private MCP link. The open-source framework of claude-mem captures notes while agents execute tasks, and CMEM Cloud mirrors this local memory, granting agents the ability to retrieve it smoothly across various sessions, devices, editors, and MCP-compatible clients. This cutting-edge system removes the necessity for users to constantly reiterate context, transfer previous notes, or begin anew, as it automatically logs key decisions, bug fixes, dead ends, environmental observations, architectural choices, and other structured insights in real-time. These important insights are stored in a temporal database, enabling searches based on meaning through vector recall, and can be accessed via a private MCP endpoint that any compatible agent can use for reading and writing purposes. The process begins with the setup of the local engine, followed by the activation of a secondary model that autonomously generates structured notes, syncing the local database with CMEM Cloud, and ultimately allowing for memory recall from any location. This method not only boosts efficiency but also cultivates a more collaborative atmosphere among agents, as they can share insights with ease and contribute to a more cohesive working environment. As a result, agents can work more effectively together, leveraging shared knowledge to enhance their collective performance.

Media

Media

Integrations Supported

Claude Code
Cursor
Gemini CLI
Model Context Protocol (MCP)
Agno
Amazon SageMaker
Astro by Astronomer
Boomi
Contextual AI
DSPy
Databricks
GitHub Copilot
Google Cloud Marketplace
Hugging Face
Mistral AI
Ollama
Replicate
Snowflake
Superlinked
Tadata

Integrations Supported

Claude Code
Cursor
Gemini CLI
Model Context Protocol (MCP)

API Availability

Has API

API Availability

Has API

Pricing Information

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

Pricing Information

Free
Free Version

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

Company Facts

Organization Name

Weaviate

Date Founded

2019

Company Location

The Netherlands

Company Website

weaviate.io

Company Facts

Organization Name

cmem.ai

Company Location

United States

Company Website

cmem.ai/

Categories and Features

AI Memory Layers

Not specified

Context Engineering

Not specified

Vector Databases

Not specified

Categories and Features

Agentic AI

Not specified

AI Memory Layers

Not specified

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