Databaset

Your AI forgets everything. Give it long-term memory with one API.

Databaset automatically stores, retrieves, and injects relevant user memories into GPT, Claude, Gemini, and any LLM without vector databases, embeddings, chunking, or retrieval pipelines.

Start FreeView Docs

Free tier includes 10,000 memories per month. No credit card required.

OpenAIClaudeGeminiLangChainVercel AI SDKNext.js
Stored memories3 indexed
Building SaaS in Next.js
Prefers PostgreSQL
Dark mode always on

Recall query

"tech stack"

Context for LLM

Waiting for recall…

The problem

Every AI app starts the same way

Teams burn weeks on AI context management before they ship anything users love.

The usual path

Build chatbot · users love it
AI forgets everything
Add Pinecone + embeddings
Tune chunking + retrieval
Maintain infra forever

The shortcut

Or install Databaset and ship memory in minutes.

One user memory API replaces the entire AI context management stack.

await memory.store(...)
const ctx = await memory.recall(...)
reply(ctx)
Start free
Live demo

Try the AI memory API live

Store a few facts, ask a question, and watch Databaset recall relevant context before answering. No signup required.

StoreRecallAnswer
Memories0
0/2000

Stored

  • Loading...
Add a few facts on the left, then ask me anything. I'll recall what matters before I answer.
How it works

Memory that actually sticks

Store once. Recall by meaning weeks later. Your LLM answers with real context, not a blank slate.

  • User

    I use PostgreSQL and prefer dark mode.

  • Databaset

    Semantic index

    Stores the memory with semantic indexing.

  • One week later · User

    Recalled from memory

    What stack should I use?

  • AI answer

    Since you prefer PostgreSQL and dark mode, here is what I would recommend...

Quickstart

Four steps to production memory

Install, store, recall, and inject. A full AI memory API without a vector database project.

1

Install

One package. No other dependencies.

bash
npm install @databaset/sdk
2

Store

Send any text. We handle chunking, embedding, and storage automatically.

javascript
await memory.store(userId, "User prefers dark mode")
3

Recall

Semantic search returns the most relevant memories.

javascript
const context = await memory.recall(userId, userMessage)
4

Use with any AI

Inject context into Claude, GPT-4, Gemini, or any model.

javascript
const reply = await anthropic.messages.create({  system: `You know this about the user: ${context}`,  messages: [{ role: 'user', content: userMessage }]})
SDK

Three lines. Production ready.

Developers do not want another infrastructure project.

Install the SDK, store a memory, recall context, and reply. That is the full AI agent memory loop.

await memory.store(...)const context = await memory.recall(...)reply(context)

That is it.

typescript
import { Memory } from '@databaset/sdk' const memory = new Memory() await memory.store({  userId: 'user_123',  text: 'User prefers dark mode and VS Code',  metadata: { source: 'onboarding' },})
Use cases

AI personalization API for every product

From OpenAI memory-style chatbots to Claude memory copilots, Databaset powers semantic memory across agents and apps.

  • Customer support AI
  • Personal AI assistant
  • Coding agent
  • Healthcare assistant
  • CRM copilot
  • Sales assistant
  • Education app
  • Second brain
  • Email assistant
  • Shopping assistant
  • Internal company AI
  • Knowledge bots
Platform

Everything your AI needs to remember

Long-term memory for LLMs with store, semantic recall, context injection, and a dashboard to observe every user memory.

Store

Save conversations, preferences, documents, notes, and events as persistent memory for AI.

Recall

Find memories by meaning, not keywords. Semantic memory built in.

Inject

Use recalled context with GPT, Claude, Gemini, or any model. AI context management in one call.

Observe

See exactly what your AI remembers and delete anything instantly.

Under the hood

We handle everything behind the scenes

Databaset is a full AI memory API and vector database alternative. Persistent memory for LLMs without the RAG memory plumbing.

  • Chunking
  • Embeddings
  • Vector storage
  • Ranking
  • Metadata
  • Deduplication
  • Context injection

You never configure any of it.

Compare

Stop paying the AI infrastructure tax

Build AI agent memory once with a user memory API. Skip the vector database alternative research loop.

Without Databaset

  • Learn embeddings
  • Configure Pinecone
  • Tune chunk sizes
  • Handle metadata
  • Debug retrieval
  • Rebuild every project

With Databaset

  • One SDK
  • One API
  • One dashboard
  • Production-ready memory

Pricing

Simple, predictable pricing

Start free, grow when you are ready. Plans translate memory limits into real user capacity.

Free

Perfect for side projects and prototypes

$0/month
  • 10,000 memories stored
  • Enough for prototypes and early users
  • 1 app
  • 7 day retention
  • Community support
  • Full API access
Start free, no credit card
Most Popular

Starter

For production apps with real users

$29/month
  • ≈ 100,000 active users worth of memory storage
  • 50,000 recalls per month
  • 10 apps
  • Unlimited retention
  • Email support
  • Dashboard analytics
  • Webhooks
Start Starter

Growth

For teams scaling AI products

$99/month
  • ≈ 1M active users worth of memory storage
  • 500,000 recalls per month
  • Unlimited apps
  • Unlimited retention
  • Priority support
  • Advanced analytics
  • Custom metadata
  • SLA guarantee
Start Growth

Enterprise

Custom limits and dedicated support

Custom
  • Unlimited everything
  • Self-hosted deployment option
  • Dedicated support engineer
  • Custom contract and billing
  • SOC2 compliance
  • HIPAA available
Contact Sales
FAQ

Frequently asked questions

Common questions about AI memory API, OpenAI memory, Claude memory, pricing, and self-hosting.