Mem0
Mem0 is a drop-in memory layer for AI agents and applications. It captures, updates and retrieves context so conversations persist across sessions and across agents, through Python and Node SDKs, a command-line tool and a REST API.
What is Mem0?
Mem0 is memory infrastructure for AI agents and applications, published by Embedchain, Inc. (trading as Mem0), a United States company founded by Taranjeet Singh and Deshraj Yadav. It addresses a narrow but expensive problem: large language models start from nothing at every session, so users re-paste the same context and agents repeat mistakes they were corrected on yesterday. The company calls this digital amnesia.
The service works in three movements the homepage labels Add, Learn and Retrieve. Mem0 extracts facts from an interaction, categorises them, updates them when contradictory information arrives, and surfaces only the relevant ones when the agent needs them. The underlying algorithm is described as single-pass hierarchical distillation with multi-signal retrieval. The published figures are specific: 92.5 on LoCoMo and 94.4 on LongMemEval, with additional runs on BEAM at 1M and 10M. The LoCoMo breakdown covers 1,540 questions across five categories, scoring 94.6 on single-hop, 95.4 on multi-hop and 92.5 on temporal recall. Mem0 also claims roughly 6,900 tokens per retrieval call against more than 25,000 for a full-context approach.
The product exists in two forms: an open-source project on GitHub, showing 62,590 stars, and a managed platform. Developers reach it through Python and Node SDKs, a REST API, a terminal CLI and an MCP server. A companion product, OpenMemory, brings the same layer to coding agents, working with Cursor, VS Code, Claude and any MCP-compatible tool, tagging memories by type and by project. Thirty-one named integrations cover agent frameworks such as LangChain, LangGraph, CrewAI and LlamaIndex, cloud services including AWS Bedrock, voice stacks like ElevenLabs and LiveKit, and no-code routes through n8n and Zapier.
The enterprise side stresses governance: SOC 2, HIPAA readiness, BYOK and zero-trust, portable deployment on Kubernetes, private cloud or air-gapped infrastructure behind the same API, and auditability of every read and write. Adoption figures quoted on the site range from 90,000 to 160,000 developers depending on the page, alongside 486 research citations.
What it does
- Store memories extracted from a conversation with a single add call
- Retrieve the memories relevant to the current interaction with a search call
- Compress conversation history automatically into compact memories to cut tokens and latency
- Link entities across memories with graph memory so mentions of the same person or concept connect
- Consolidate memories with Dream to keep accuracy from drifting as volume grows
- Attach memory to a coding agent through the MCP server or a ready-made plugin
- Audit every memory read and write, with a record of what was served, to whom and when
When to use Mem0 / When not to
A quick filter to help you decide if Mem0 is the right fit.
When to use Mem0
- Developers shipping AI agents to production who need context to survive between sessions
- Engineering teams paying to resend the same context on every call and looking to cut token spend and latency
- Product teams building personalised assistants for customer support, healthcare, education, e-commerce or sales
- Developers working with coding agents such as Cursor, VS Code, Claude Code or Codex, through OpenMemory and MCP
- Enterprise teams that require on-premise, private-cloud or air-gapped deployment with SSO and audit logs
When not to use Mem0
- Non-technical users looking for a ready-made assistant: an API key and code are required
- Anyone who needs a mobile app, since no iOS or Android application is offered
- Teams that cannot accept a perpetual, irrevocable licence over their content, which is what the free plan grants
- Organisations with a strict data-residency requirement, as no EU region or hosting location choice is published
- Small budgets that need graph memory, Dream consolidation or advanced analytics, all reserved for the Pro tier at USD 249 per month
How to use Mem0
A typical end-to-end flow, from setup to results.
- Create an account and collect an API key from the Mem0 dashboard
- Install the SDK with pip install mem0ai for Python, or the equivalent Node package
- Instantiate MemoryClient with the API key, read from an environment variable rather than hard-coded
- Send a first interaction with client.add, passing a list of role and content messages and a user identifier
- Read the context back with client.search, using a natural-language query and the same user identifier
- Wire the calls into the agent loop, adding after each exchange and searching before each response
- For terminal work, install the CLI with npm install -g @mem0/cli, then run mem0 init, mem0 add and mem0 search
- For a coding agent, install the plugin for Claude Code, Codex, OpenCode or Antigravity, or configure the MCP server
- For a no-code path, use the n8n community node, the Zapier app or the Dify plugin instead of writing code
- Track usage, projects, analytics and billing from the web dashboard as volume grows
Pros & Cons
Pros
- Benchmark results published in detail, category by category, with the methodology behind each score
- Quantified efficiency claim of roughly 6,900 tokens per retrieval call against more than 25,000 for full context
- Integration advertised in three lines of code, with no change to the existing pipeline
- Open-source core with a heavily followed public repository, alongside the managed platform
- Thirty-one named integrations covering agent frameworks, coding agents, voice pipelines and cloud services
- Permanent free tier for evaluation, plus a startup programme offering three months of the Pro plan
- Paid-plan content contractually excluded from model training, with SOC 2 Type I, HIPAA readiness, a BAA and a DPA
Cons
- On the free plan, the licence granted to Mem0 over customer content is perpetual, irrevocable and covers model training
- SOC 2 Type I only, not Type II, and the Trust Center could not be consulted to verify the scope
- No subprocessor list published, although the privacy policy names OpenAI, Anthropic, Stripe and Chargebee as examples
- No data-residency option and no EU region: hosting is described only as the United States and other countries
- No postal address for the company anywhere on the site
- A steep gap between Starter at USD 19 and Pro at USD 249 per month, with nothing in between
- Mem0 retains ownership of aggregated and performance data derived from usage, including for paying customers, even after termination
Pricing & Plans
Mem0 operates a freemium model. A permanent free plan, named Hobby, is available without payment and covers 10,000 add requests and 1,000 retrieval requests per month on a single project. The lowest paid entry point is the Starter plan at USD 19 per month. The Pro plan is priced at USD 249 per month and the Enterprise plan is quoted on request. Usage-based pricing is offered on request for traffic that does not map cleanly onto a fixed tier. Self-serve subscriptions renew automatically, monthly or annually, and may be cancelled before the end of the current billing period.
- unlimited end users
- 10
- 000 add requests per month
- 1
- 000 retrieval requests per month
- 1 project
- community support
- unlimited end users
- 50
- 000 add requests per month
- 5
- 000 retrieval requests per month
- 1 project
- community support
- unlimited end users
- 500
- 000 add requests per month
- 50
- 000 retrieval requests per month
- unlimited projects
- multiproject support
- private Slack support
- everything in Pro plus SLA support
- on-premise deployment
- audit logs
- custom integrations and SSO
Data, GDPR & hosting
A consolidated view of how Mem0 handles your data.
GDPR overview
The GDPR commitments are concrete and detailed. The controller is named as Embedchain, Inc. (DBA Mem0) and the privacy policy carries an effective date of 3 August 2026. The company states it is not required to appoint a statutory Data Protection Officer under Article 37 and has not appointed one, directing data-protection questions to privacy@mem0.ai. Article 27 representatives are designated on both sides of the Channel: Instant EU GDPR Representative Ltd. in Dublin for the EU and GDPR Local Ltd. in Brighton for the UK. Legal bases are set out article by article, covering contract, consent, legitimate interests and legal obligation. The full set of data-subject rights is listed, complaints are directed to the ICO or to the local authority via the EDPB, and a Data Processing Addendum governs the data Mem0 handles on behalf of business customers.
Who owns the data?
Under section 5.2 of the terms, the customer keeps all right, title and interest in the content they send to the service. Mem0 keeps ownership of its own technology (5.1) and, more importantly, of two derived assets: aggregated, de-identified data built from customer content (5.3) and performance data collected from usage (5.4). Both belong to Mem0 for every customer, including paying ones, and both survive termination of the contract. Feedback sent to Mem0 is licensed to it perpetually and irrevocably (5.5). Ownership of the raw content therefore stays with the customer, while everything Mem0 derives from it does not.
Reuse rights
What Mem0 may do with customer content depends entirely on the plan. On a paid plan, the licence is narrow: access and use limited to delivering the service and its support, for the duration of the contract only, and the terms state explicitly that paid customer content is not used to train or improve any machine learning or artificial intelligence model. On the free plan the licence is the opposite: worldwide, perpetual, irrevocable and royalty-free, covering reproduction, modification and derivative works for any lawful purpose, model training included. The privacy policy grounds that training on consent, which a free-plan user may withdraw at any time. In both cases Mem0 may build aggregated, de-identified data from the content. Data may also be shared with service providers named in the policy, including the AI providers OpenAI and Anthropic and the payment processors Stripe and Chargebee, as well as with affiliates, advertising partners, professional advisers and authorities. Customers keep their own content and may reuse it freely; they cannot reuse Mem0's technology, aggregated data or performance data.
Data retention & training
Hosting summary
Mem0 states that personal information is stored and processed on cloud infrastructure operated by its hosting and service providers, which it does not name. The only jurisdiction identified is the United States, where the company is headquartered, and the policy adds that some providers and its own operations sit in other countries without listing them, so international transfers are expected. No data-residency choice is offered and no EU region is advertised. Access is limited to authorised personnel and vetted processors bound by data processing agreements. The security measures described include encryption in transit and, where appropriate, at rest, role-based access control on a least-privilege basis, multi-factor authentication where available, network monitoring, regular backups, vulnerability management and incident response procedures. Enterprise customers can move away from the shared platform entirely, with deployment on Kubernetes, private cloud, air-gapped infrastructure or on premise behind the same API, plus bring-your-own-key encryption. The Trust Center that would document the certifications in detail could not be reached at the time of review.
Things to keep in mind
Risks and trade-offs to weigh before adopting Mem0.
- The free plan grants Mem0 a perpetual and irrevocable licence over the content sent to it, model training included, which makes it the wrong place to test confidential or client data
- Protected health information counts as prohibited data until a Business Associate Agreement has been signed, so HIPAA readiness is a precondition to arrange rather than a state to assume
- SOC 2 Type I attests the design of controls at a point in time, not their effectiveness over a period, and the Trust Center could not be consulted to check the scope
- No subprocessor list is published, so the chain of parties touching the data cannot be audited from the outside
- A memory layer accumulates a durable and detailed profile of end users, which raises retention and consent questions that fall on the developer, not on Mem0
- Disputes are governed by California law and settled by arbitration seated in San Francisco, which is costly to pursue from Europe
- Aggregated and performance data derived from usage remain Mem0's property after the contract ends, so leaving the service does not undo everything built from it
Setup & Integrations
Technical difficulty
Low for a developer, out of reach for anyone else. One command installs the SDK, an API key is collected from the dashboard, and a working example needs about ten lines of Python around two methods, add and search. The company advertises integration in three lines of code with no pipeline changes. Coding agents are wired up through a plugin or an MCP server, and no-code routes exist via n8n, Zapier or Dify. Enterprise deployments on Kubernetes, air-gapped infrastructure or with SSO and BYOK require real infrastructure skills.
Deployment
Integrations
Supported languages
Behind Mem0
Fundraising
Social
Resources
All the official URLs gathered for verification and reference.
Alternatives
Tools that compete with or complement Mem0.
Frequently asked questions
What does Mem0 actually do?
Do I need to be a developer to use it?
Is there a free plan, and what does it include?
How much do the paid plans cost?
Will my data be used to train Mem0's models?
Who owns the content I send to Mem0?
Is Mem0 suitable for healthcare or other regulated data?
What can Mem0 integrate with?
Can I host Mem0 myself?
How do I exercise my GDPR rights?
Should you pick Mem0?
Mem0 is infrastructure, not a finished product, and it is worth judging on that basis. For a team already shipping agents, the proposition is unusually concrete: a memory layer added in a few lines of code, benchmark scores published category by category rather than asserted, and a quantified token saving of roughly 6,900 tokens per retrieval call against more than 25,000 for a full-context approach. The thirty-one named integrations and the open-source core lower the cost of trying it, and the free Hobby plan makes evaluation genuinely free rather than a countdown.
The reservations are mostly contractual. Free-plan content is licensed to Mem0 perpetually and irrevocably, model training included, which makes the free tier a poor place to test anything sensitive; the paid tiers reverse that position explicitly. Compliance is advertised as SOC 2 Type I and HIPAA readiness, no subprocessor list is published, and no data-residency option or EU region is offered, which will stop some European buyers before the technical evaluation begins. The jump from USD 19 to USD 249 per month is abrupt, and the features that make the product distinctive, graph memory and Dream consolidation, only appear at the higher price.
The company itself is young: the domain dates from May 2024, USD 24 million was raised in late 2025, and the team is small and based in San Francisco. That is normal for the category and worth weighing against a dependency that sits in the critical path of an agent. The sensible route is the one the pricing suggests: prototype on Hobby with non-sensitive data, move to Starter once the shape of the memory is clear, and read section 5 of the terms carefully before anything confidential is sent.
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