1
langchain
Shares tags: ai
AI Tool
Supermemory Review
Supermemory is a context infrastructure platform for AI agents, providing user profiles, memory graph, retrieval, extractors, and connectors.
1Supermemory raised $3 million in Seed funding in October 2025.
2The Model Context Protocol (MCP) server received a major update to version 4.0 on December 30, 2025.
3Reported a 37.4% mean improvement and 41.4% median improvement in latency over Mem0 in user tests.
4Offers a freemium pricing model with a Pro Tier available at $29 per month.
⚡
Supermemory at a Glance
🏢
About Supermemory
Pricing Plans
Free Tier
Free / monthly
- • Basic features
- • Limited API access
Pro Tier
$29/mo / monthly
- • Full API access
- • Advanced features
- • Priority support
Leadership
Investors
Google Ventures, Susa Ventures
</>Embed "Featured on Stork" Badge▼
<a href="https://www.stork.ai/en/supermemory" target="_blank" rel="noopener noreferrer"><img src="https://www.stork.ai/api/badge/supermemory?style=dark" alt="Supermemory - Featured on Stork.ai" height="36" /></a>
[](https://www.stork.ai/en/supermemory)
overview
What is Supermemory?
Supermemory is an AI memory layer and context engineering platform developed by Dhravya Shah that enables developers and enterprises to provide AI agents with persistent, scalable, and contextual memory. It handles the ingestion of raw data, transforms it into vector embeddings, and makes them retrievable through semantic search queries. The platform functions as an external brain for AI, addressing the 'digital amnesia' problem in AI applications by allowing agents to retain and leverage information across sessions and interactions. It supports various data sources and is compatible with major Large Language Models (LLMs), offering an API for integration.
quick facts
Quick Facts
| Attribute | Value |
|---|---|
| Developer | Dhravya Shah |
| Business Model | Freemium |
| Pricing | Freemium starting at $0 |
| Platforms | Web, API |
| API Available | Yes |
| Integrations | Zapier, Slack, LangGraph, OpenAI Agents SDK, CrewAI, Agno, Mastra, LangChain, Claude Code, ViaSocket |
| Founded | 2025 |
| HQ | Mumbai, India |
| Funding | Seed, $3 million |
| Team Size | 10-50 |
features
Key Features of Supermemory
Supermemory provides a comprehensive suite of features designed to enhance AI agent capabilities through advanced memory and context management. These features are exposed via an API, allowing developers to integrate persistent memory into their AI applications. The platform includes open-source components for flexibility and control over data.
- 1Context engineering platform for AI agents
- 2Enterprise-grade API support
- 3Developer plugins for various AI frameworks
- 4Personal memory application for individual use
- 5Open-source components for customization
- 6Advanced retrieval capabilities for semantic search
- 7Memory graph for structured information storage
- 8Low-latency retrieval of contextual data
- 9Support for ingestion of documents, chat histories, and user profiles
- 10Vector embedding transformation and distributed database indexing
use cases
Who Should Use Supermemory?
Supermemory targets developers, teams building AI agents, and enterprises seeking to implement persistent and contextual memory into their AI applications. Its architecture supports a range of applications requiring continuous information retention and real-time data access for enhanced AI performance.
- 1Developers and Teams building AI agents/applications: For giving AI agents continuous memory across sessions and building context-aware applications.
- 2Educational platforms: For adapting educational content to learner progress in real time and creating AI tutors.
- 3Healthcare companies: For securely enriching and retrieving patient data, ensuring compliance with privacy policies.
- 4Customer support teams: For building chatbots that remember past interactions, providing more relevant and personalized responses.
- 5Enterprises: For building internal knowledge bases accessible through AI agents and maintaining consistent brand voice in content generation.
pricing
Supermemory Pricing & Plans
Supermemory operates on a freemium business model, offering a free tier for initial exploration and a paid Pro tier for more extensive usage. The pricing structure is designed to accommodate both individual developers and larger teams or enterprises requiring advanced features and higher capacity.
- 1Free Tier: Free
- 2Pro Tier: $29/month
competitors
Supermemory vs Competitors
Supermemory positions itself as a universal memory API that simplifies the infrastructure complexity of AI memory, offering an all-in-one solution for Retrieval Augmented Generation (RAG), memory, and extraction. It aims to provide a more stable and performant alternative to building in-house solutions or using certain existing memory layers.
1
Mem0↗
Mem0 is a universal, self-improving AI memory layer for LLM applications, offering multi-level memory scopes and hybrid retrieval through a multi-store architecture.
Similar to Supermemory in providing an AI memory layer, Mem0 focuses heavily on personalization and adaptive updates across user, session, and agent levels, utilizing a multi-store architecture for comprehensive memory management. It offers both a managed platform and an open-source option for self-hosting.
2
Zep↗
Zep is a context engineering and long-term memory platform specifically optimized for conversational AI, focusing on extracting facts, summarizing conversations, and providing efficient context retrieval through semantic and temporal search.
While both offer memory for AI agents, Zep is particularly tailored for conversational AI applications, emphasizing chat history summarization and structured fact extraction, whereas Supermemory is described more broadly as a context engineering platform. Zep also leverages temporal knowledge graphs to organize memories and relationships.
3
LlamaIndex↗
LlamaIndex serves as a versatile data framework that connects custom data sources and formats to LLMs, enabling agents to remember and reason over structured information and documents by combining chat history with document context.
Supermemory focuses on an AI memory layer and context engineering, while LlamaIndex provides a broader data orchestration framework for integrating diverse data sources with LLMs, making it a comprehensive solution for knowledge-intensive agents. It offers both high-level APIs for quick integration and lower-level APIs for extensive customization.
4
LangChain↗
LangChain is a comprehensive open-source orchestration framework for building LLM-powered applications, offering a highly flexible memory component with various types and storage options that integrate natively with its broader ecosystem.
Supermemory is a dedicated memory and context engineering platform, whereas LangChain provides memory as a component within a larger framework for agent development, offering more extensive orchestration capabilities alongside its memory features. LangChain's ecosystem includes tools like LangGraph for agent workflows and LangSmith for observability.
5
Cognee↗
Cognee is an open-source AI memory engine and knowledge graph layer that structures, connects, and retrieves information with precision by building knowledge graphs from unstructured data, allowing agents to reason over relationships.
Supermemory provides an AI memory layer and context engineering, while Cognee specifically leverages knowledge graphs to give agents a dynamic, queryable understanding of interconnected data, which is a more structured approach to memory than simple retrieval. Cognee offers a freemium model with developer and enterprise plans.
❓
Frequently Asked Questions
+What is Supermemory?
Supermemory is an AI memory layer and context engineering platform developed by Dhravya Shah that enables developers and enterprises to provide AI agents with persistent, scalable, and contextual memory. It handles the ingestion of raw data, transforms it into vector embeddings, and makes them retrievable through semantic search queries.
+Is Supermemory free?
Yes, Supermemory offers a Free Tier. Additionally, a Pro Tier is available for $29 per month, providing expanded capabilities for users requiring more extensive features.
+What are the main features of Supermemory?
Key features of Supermemory include its context engineering platform, enterprise API support, developer plugins, a personal memory app, open-source components, advanced retrieval capabilities, a memory graph, and low-latency semantic search queries. It also supports ingestion of various data types and transformation into vector embeddings.
+Who should use Supermemory?
Supermemory is designed for developers, teams building AI agents and applications, enterprises, educational platforms, healthcare companies, and customer support teams. It is particularly useful for scenarios requiring continuous memory across AI agent sessions, building internal knowledge bases, adapting educational content, and securely managing patient data.
+How does Supermemory compare to alternatives?
Supermemory differentiates itself from competitors like Mem0 by offering reported better stability and lower latency. Compared to Zep, Supermemory provides a broader context engineering platform, while Zep focuses on conversational AI. Unlike LlamaIndex and LangChain, which are broader data orchestration or agent frameworks, Supermemory specializes as a dedicated AI memory layer and context engineering API. Against Cognee, Supermemory offers a general memory layer, whereas Cognee leverages knowledge graphs for structured data understanding.