Rapid memory
for AI agents.

FishMem is the hosted memory platform built on the open-source FishMem engine. A versioned memory API with familiar scopes, first-party SDKs, hybrid graph + vector recall, bi-temporal facts, and scoped API keys — running on the edge, with API keys in minutes.

Get Your API Key Read the Docs

Mem0-style scopes
Hybrid recall
Open-source engine

TypeScript

import { FishMem } from "@fishmem/sdk";

// Get your key at https://fishmem.com
const fishmem = new FishMem({
  apiKey: process.env.FISHMEM_API_KEY,
});

// Remember a conversation
await fishmem.memories.add(
  {
    messages: [
    { role: "user", content: "I'm vegetarian and allergic to nuts." },
    { role: "assistant", content: "Got it — I'll remember that." },
    ],
    user_id: "user123",
  },
  { idempotencyKey: "user123-diet-v1" },
);

// Recall what's relevant
const { results } = await fishmem.memories.search({
  query: "What are my dietary restrictions?",
  user_id: "user123",
});
console.log(results);

Quickstart

Set up in minutes

Two REST calls give your agent long-term memory: add what the user says, then search it back whenever you need it.

Create an API key

Open the dashboard → API Keys, create a key, and copy the secret — it starts with fm_ and is shown once.

Add and search memories

Use the first-party TypeScript or Python SDK, or call the versioned REST API directly. Inferred adds store refined records; search recalls them before the next model call.

Get your API key

import { FishMem } from "@fishmem/sdk";

const fishmem = new FishMem({
  apiKey: process.env.FISHMEM_API_KEY
});

// 1. Add what the user tells you
await fishmem.memories.add(
  {
    messages: [
      { role: "user", content: "I'm vegetarian and allergic to peanuts." }
    ],
    user_id: "alex"
  },
  { idempotencyKey: "alex-diet-v1" }
);

// 2. Recall it before the next model call
const { results } = await fishmem.memories.search({
  query: "What can Alex eat?",
  user_id: "alex"
});

Memory your agents can actually rely on in production.

The goal is not to hoard transcripts. The goal is to extract the facts that matter, keep them current, and return the right ones in well under a second — every turn of the loop.

Hybrid retrieval

Four signals, one ranked recall

request logs

Vector + keywordMatched

Graph diffusionRanked

Temporal validityResolved

Recall That Understands Time and Relationships

Facts are bi-temporal — they know when they were true and what superseded them — and graph recall connects related facts across conversations, so the right memory surfaces even when the words don't match.

Hybrid vector, keyword, graph, and temporal retrieval signals
Facts know when they were true and what superseded them
Superseded facts are versioned and stay queryable, never silently deleted

See how retrieval works

Open-source FishMem engine with hosted operations

OSS

POST /v1/memories

Endpoint

/v1/memories

Auth

API key

Mode

Inferred

Status

201

Familiar API, Explicit FishMem Contract

POST /v1/memories to add and POST /v1/memories/search to recall. FishMem keeps familiar mem0-style scopes while defining its own versioned responses, errors, idempotency, and operation resources.

API keys in minutes, no card required
One-pass inferred adds or explicit verbatim storage
First-party TypeScript and Python SDKs plus OpenAPI 3.1

Read the API docs

Documented migration from mem0

LiveHosted memory platform

Scales automatically and stays fast from every region

Isolated by workspace, exportable via the API — your data stays yours.

Nothing to Operate — Sign Up, Create a Key, Ship

FishMem is memory out of the box. No servers to size, no indexes to babysit, no pipelines to deploy. It scales with you automatically and stays fast from every region.

Live in minutes — sign up, create a key, make your first call
Scales with your traffic automatically, fast from every region
Your data stays isolated, exportable, and deletable at any time

Get your API key Open-source engine

Built on the open-source FishMem engine

OSS

Use cases

Memory that adapts to your domain

The same two endpoints power very different agents. Scope memories per user, agent, or session, and FishMem keeps each domain's facts current as the world changes.

Customer Support

Agents that remember every prior ticket, the customer's preferences, and the promises your team made — so nobody has to repeat themselves.

AI Companions

Relationships that deepen over time. Companions recall months of conversation and know what changed and when — not just what was said.

Coding Agents

Project conventions, past decisions, and hard-won gotchas persist across sessions, so your agent stops re-learning the codebase every morning.

Sales & CRM

Every conversation, objection, and follow-up stays in context. The next call starts where the last one ended, not from a blank page.

Healthcare Assistants

History, allergies, and what helped before — with full change history per fact, so the compliant workflows you build on top stay grounded in accurate, current records.

Education

Tracks what each learner has mastered and where they struggle, so tutoring agents pick up exactly where the student left off.

Built for teams. Designed for control.

No black boxes around your users' memories. Isolation is enforced in the data layer, every change is logged, and your data is exportable on demand.

Get your API key

Isolated

Every workspace's memories are hard-isolated in the data layer — no cross-tenant reads, no shared indexes. API keys are hashed at rest, shown once at creation, and revocable instantly from the dashboard.

Auditable

Every add, update, invalidate, and delete is logged per memory, and the full change history is one API call away. Usage is metered per operation, so you always know what ran and what it cost.

Yours

Export or delete everything via the API at any time. The engine is open source, so there is no lock-in — and self-hosting is always an option.

Start free, upgrade when traffic grows

Prototype on Hobby, then move to monthly Stripe plans with higher included memory operations. Reads are always free.

Get your API key

Hobby

Freeno card required

Get your API key

Credits: 10,000 add requests and 1,000 retrieval requests per month
Best for: Prototyping memory for a single agent or side project
Metering: Full API access from day one: adds, search, and free reads
Support: Community support on GitHub issues and discussions
Platform access: Versioned REST API, first-party SDKs, dashboard, and one workspace
Data ownership: Memories stay workspace-scoped; export or delete them at any time.

Starter

Growth

$79per month

Credits: 200,000 add requests and 20,000 retrieval requests per month
Best for: Teams scaling memory across production users
Metering: Usage analytics, API keys, webhooks, and billing controls
Support: Email support from the engineers who built the engine
Platform access: Multiple projects, hybrid retrieval, graph and temporal recall
Data ownership: Memories stay workspace-scoped; export or delete them at any time.

Pro

$249per month

Credits: 500,000 add requests and 50,000 retrieval requests per month
Best for: Higher-volume apps that need advanced usage visibility
Metering: Advanced analytics and higher included monthly capacity
Support: Private Slack support
Platform access: Unlimited projects with production-ready controls
Data ownership: Memories stay workspace-scoped; export or delete them at any time.

Enterprise

Customannual commitment

Talk to us

Credits: Committed-use credit pricing with volume discounts
Best for: Teams with compliance, scale, or data-residency requirements
Metering: Dedicated capacity, SLAs, and priority on the roadmap
Support: Private channel, onboarding help, and migration assistance
Platform access: Everything in Pro, plus SSO and audit controls
Data ownership: Memories stay workspace-scoped; export or delete them at any time.

Plan	Hobby Freeno card required Get your API key	StarterMost popular $19per month	Growth $79per month	Pro $249per month	Enterprise Customannual commitment Talk to us
Credits	10,000 add requests and 1,000 retrieval requests per month	50,000 add requests and 5,000 retrieval requests per month	200,000 add requests and 20,000 retrieval requests per month	500,000 add requests and 50,000 retrieval requests per month	Committed-use credit pricing with volume discounts
Best for	Prototyping memory for a single agent or side project	Small apps moving from prototype to live traffic	Teams scaling memory across production users	Higher-volume apps that need advanced usage visibility	Teams with compliance, scale, or data-residency requirements
Metering	Full API access from day one: adds, search, and free reads	Operation-level usage and credit balance in the dashboard	Usage analytics, API keys, webhooks, and billing controls	Advanced analytics and higher included monthly capacity	Dedicated capacity, SLAs, and priority on the roadmap
Support	Community support on GitHub issues and discussions	Community support	Email support from the engineers who built the engine	Private Slack support	Private channel, onboarding help, and migration assistance
Platform access	Versioned REST API, first-party SDKs, dashboard, and one workspace	Hosted FishMem API, dashboard, and one workspace	Multiple projects, hybrid retrieval, graph and temporal recall	Unlimited projects with production-ready controls	Everything in Pro, plus SSO and audit controls
Data ownership	Memories stay workspace-scoped; export or delete them at any time.	Memories stay workspace-scoped; export or delete them at any time.	Memories stay workspace-scoped; export or delete them at any time.	Memories stay workspace-scoped; export or delete them at any time.	Memories stay workspace-scoped; export or delete them at any time.

Credits are consumed per API operation: 2 for an inferred add, 1 for an infer=false verbatim add or search, and reads are free. Self-hosting the open-source engine costs nothing.

Built around clear engineering principles.

“Memory infrastructure should be inspectable: request logs, API keys, usage, and billing belong next to the API itself.”

Operational clarity

Platform principle

“A memory store that forgets when facts were true will confidently answer with stale ones. Bi-temporal tracking is not optional.”

Time-aware truth

Data model principle

“Memory sits inside the agent loop, so retrieval latency is a product feature, not an implementation detail.”

Speed as a feature

Performance principle

Frequently asked questions

Quick answers about FishMem, the FishMem engine, and migrating from mem0.

What is FishMem?

FishMem is a hosted memory layer for AI agents. It runs on the open-source FishMem engine, extracts durable facts from conversations, stores them in a bi-temporal knowledge graph, and recalls them with hybrid vector, keyword, temporal, and graph-diffusion retrieval.

How is FishMem different from mem0?

FishMem uses familiar user_id, agent_id, and run_id scopes, but it has its own explicit contract. Default infer=true performs one extraction call and stores only refined records; infer=false stores submitted records verbatim. Recall can add temporal state, provenance, and graph signals, while hosted operations, usage, and billing remain outside MemoryCore.

Can I migrate from mem0 without rewriting my code?

The core add, search, and scope concepts overlap, but FishMem is not a compatibility shim. Response envelopes, update fields, error codes, idempotency, and operation handling differ. Use the migration guide and first-party SDK, then run the documented add-search-update-delete acceptance flow.

How is my data isolated and secured?

Every memory is scoped to a workspace, and isolation is enforced in the data layer — no cross-tenant reads or shared indexes. API keys are shown once at creation and stored as salted hashes, and you can rotate or revoke them from the dashboard. You can export or delete a workspace's memories at any time.

What is the difference between the open source engine and the cloud?

The FishMem engine and self-hosted API/dashboard are open source under Apache-2.0. Cloud runs the same MemoryCore and adds managed storage, tenant and plan enforcement, usage charging, billing, organizations, and operated infrastructure. Memory semantics do not fork between editions.

How does pricing work?

Usage is metered in transparent credits: an inferred add is 2 credits, an infer=false verbatim add is 1, a search is 1, and reads and lists are free. Current plan prices and included capacity are shown on the pricing page and in the dashboard.

Rapid memory for AI agents.

Set up in minutes

Create an API key

Add and search memories

Memory your agents can actually rely on in production.

Recall That Understands Time and Relationships

Familiar API, Explicit FishMem Contract

Nothing to Operate — Sign Up, Create a Key, Ship

Memory that adapts to your domain

Customer Support

AI Companions

Coding Agents

Sales & CRM

Healthcare Assistants

Education

Built for teams. Designed for control.

Isolated

Auditable

Yours

Start free, upgrade when traffic grows

Hobby

Starter

Growth

Pro

Enterprise

Built around clear engineering principles.

Frequently asked questions

Rapid memory
for AI agents.