How does Supermemory actually give an AI agent memory?

Supermemory stores memories in a vector-graph database keyed to each user, task or tenant. A purpose-built learner model extracts, merges, infers and forgets information over time, then injects only the relevant memories back into a model's context during a request, so agents retain knowledge across sessions without stuffing entire histories into the prompt.

What do the plans cost and how are credits used?

Every plan includes a monthly credit balance that all calls draw from at the same rates. The Free tier starts with $5 of credits each month. Pro is $19 per month, Max is $100 per month, and Scale is $399 per month for teams and production workloads, with Enterprise pricing quoted for committed-spend and self-hosted deployments.

Does it work with any model or agent framework?

It is model- and harness-agnostic. Because memory lives outside the model provider rather than inside a single prompt, it carries across different models and tools and is delivered through the API, plugins and MCP, so you can switch models without rebuilding your memory layer.

Can I self-host Supermemory?

For organizations with strict data requirements, yes. Supermemory offers self-hosted deployments on Scale and Enterprise tiers, including fully air-gapped setups, and reports SOC 2 Type II certification, HIPAA BAA availability on higher tiers, and GDPR compliance with custom contracts and DPAs.

What is SuperMemory's monthly traffic and growth trend?

SuperMemory currently receives 0 monthly visits, with a month-over-month traffic change of +0 (0.0% growth rate). Its primary source market is Global (— share), including 0 direct visits/mo and 0 organic search visits/mo.

Is SuperMemory free? What is its pricing model?

SuperMemory operates on a Freemium pricing model. Free plan gives $0/month with $5 of credits renewed monthly. Pro is $19/month ($20 credits), Max is $100/month ($130 credits), and Scale is $399/month ($600 credits) for production teams with advanced PDF extraction and self-hosting. Enterprise is custom with air-gapped deployment, SOC 2, HIPAA BAA and SLA. Credits draw from all meters at the same rates, and unchanged content is not re-billed. Supported billing and checkout platforms include: not listed.

SuperMemory — AI Tool Traffic (0/mo), Pricing, API & Alternatives

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About SuperMemory

Continual-learning memory engine

A dedicated learner model extracts, merges, infers and forgets facts, storing each learning in a vector-graph database that understands entities, sources and time.

Real-time context injection

Learnings are injected into the model's context in real time via hooks, so agents recall relevant information without stuffing full histories into the prompt.

Any model, any harness

Memory lives outside any single model provider, so it carries across models and harnesses and is delivered through the API, plugins and MCP.

Deduplicated, usage-based billing

Mandatory memory is only billed once: repeated or unchanged content is not charged again, and the same rates apply on every plan.

Enterprise security and deployment

Air-gapped self-hosting, SOC 2 Type II certification, HIPAA BAA on higher tiers and GDPR compliance, with custom contracts and DPAs available.

Supermemory is a memory and continual-learning layer built for AI agents and applications. Its premise is that raw model intelligence is no longer the bottleneck: models are highly capable but do not learn from live interaction on their own. Supermemory closes that gap by owning the infrastructure for storing what a system has learned and bringing it back to the model at the right moment.

Architecturally, raw data such as chats, URLs and structured content enters Supermemory, where a purpose-built learner model extracts, merges, infers and forgets information. The resulting learnings are stored in a vector-graph database with an understanding of entities, sources and time. When an agent makes a request, the most relevant memories are injected back into the model's context via hooks, rather than relying on embeddings or stuffing whole histories into the prompt.

Because the memory sits outside any single model provider, it travels across models and tool harnesses and is exposed programmatically. Official access is offered through an API, plugins and MCP, so it can be wired into common agent and coding environments. The company targets both individual developers and large organizations, reporting production usage at high scale and offering self-hosted and air-gapped deployments for teams with strict data-residency or compliance needs.

High-Impact Use Cases for SuperMemory

Agent developers

Add long-term memory to an agent

Give an agent persistent recall of past tickets and preferences so it answers with full context instead of starting from zero on every request.

Engineering teams

Keep coding assistants on context

Attach Supermemory through MCP or plugins so coding assistants remember project conventions and past decisions across files and sessions.

Product teams

Personalize support and chat at scale

Store per-user profiles and fact hierarchies in a scoped memory graph so personalized responses stay accurate at scale without reprocessing an entire corpus.

Platform and infra leads

Cut token cost and latency

Reduce prompt size and cost by injecting only relevant memories instead of entire histories, improving latency and token efficiency in high-volume agent loops.

Rank	AI Tool	Monthly Visits	MoM Growth	Direct traffic share	Pricing	Head-to-Head
●	SuperMemory	0	—	—	Freemium	Current
1	Notion	173.44M	+0.1%	78% direct	Freemium	vs Notion
2	Keymate.AI	1.05K	-44.5%	38% direct	Freemium	vs Keymate.AI
3	Hyper: Self-driving Company Brain	9.64K	-1.5%	40% direct	Freemium	vs Hyper: Self-driving Company Brain
4	Cluing	11.23K	-43.1%	40% direct	Freemium	vs Cluing
5	Glean	3.3M	+0.1%	80% direct	Contact for Pricing	vs Glean
6	Liminary	12.25K	-30.4%	40% direct	Freemium	vs Liminary

SuperMemory

Why Choose SuperMemory

Watchouts & Trade-offs

Multi-Angle Perspectives