Evidence tier Source Confirmed · 2 captures on record
What the publisher says
As described on Microsoft Marketplace.
Mem0 is an open-source memory layer for AI agents and AI applications, designed to provide persistent, long-term memory across conversations and workflows. Mem0 enables AI assistants, chatbots, copilots, and autonomous agents to remember user preferences, historical interactions, facts, and contextual information, creating personalized and context-aware experiences over time. It integrates with leading LLM providers, embedding models, vector databases, and AI frameworks, making it suitable for both development and enterprise AI deployments.
Key Features of Mem0:
Show the rest of the publisher’s description (34 more lines)
- Open-source memory platform for AI agents, copilots, chatbots, and AI assistants.
- Provides persistent long-term memory across conversations, sessions, and interactions.
- Supports integration with OpenAI, Azure OpenAI, Anthropic, Ollama, and other LLM providers.
- Compatible with vector databases including Qdrant, ChromaDB, Pinecone, Milvus, and other supported backends.
- Stores and retrieves user preferences, conversation history, and contextual knowledge.
- Enhances AI personalization by enabling agents to remember important user information over time.
- Supports semantic search and memory retrieval using vector embeddings.
- Designed for customer support agents, AI assistants, knowledge management, and enterprise automation.
- Flexible integration through Python SDKs, APIs, and AI application frameworks.
- Supports local and cloud-based deployments with configurable LLM and embedding providers.
- Compatible with OpenAI, Azure AI, Ollama, and self-hosted AI infrastructure.
- Deployable on Ubuntu, Docker, Kubernetes, Azure Virtual Machines, and other cloud environments.
Mem0 Usage:
$ sudo su
$ cd /opt
$ source mem0-env/bin/activate
# Check Mem0 Version
$ pip show mem0ai
# Verify Installation
$ python -c "import mem0; print('Mem0 installed successfully')"
# Start Python Shell
$ python3
# Test Mem0 Import
>>> from mem0 import Memory
m = Memory()
print("OK")
# Verify Ollama Models (Optional)
$ ollama list
# Display Package Information
$ pip show mem0ai
# Upgrade Mem0
$ pip install --upgrade mem0ai
Disclaimer:
Mem0 is an open-source project developed and maintained by the Mem0 community and contributors. Mem0 and related trademarks belong to their respective owners. This software is not affiliated with, endorsed by, or sponsored by any AI model provider, cloud platform, operating system vendor, or third-party service mentioned for compatibility, integration, or deployment purposes.
Agent build and provenance
See the full provenance
The layer-by-layer build, the evidence behind each claim, the risk basis and the cross-marketplace links are open to any account. Some rows are disclosed, some the source leaves Unknown; a free account shows you which.
Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment · as of 2026-08-29
Reconciled on 9/3/2026
Sources
Publisher resources
1 linkLinked repositories
Unknown means this listing does not publish a repository. It is not a statement that the code is closed, and a linked repository is not a claim that the publisher wrote it: the registry computes that relationship privately and does not publish it.
Evidence risk is the share of the build you cannot see before you deploy, not a security rating. Sign in to see the layer-by-layer basis for this band.

