Why MemoryNode?
Make users feel remembered — memory and context infrastructure for AI products.
Who it is for
Primary: SaaS founders and small AI product teams, especially India-first builders, shipping AI chat or copilot into their product.
Prove the SaaS copilot path first (save → recall → context in Playground). The same API works for other remembered-user products later.
The problem
Your users come back, but your AI does not remember them. They repeat preferences every session. The product feels generic even when the user already told you what matters.
What MemoryNode gives you
| Surface | What you get |
|---|---|
| Proof | Playground — see recall in ~5 minutes, no API key |
| Ship | REST + SDK — remember, prepareContext, injectContext, saveFromTurn |
| Build | MCP for Cursor/Claude — same backend while prototyping |
Lane rule: MCP is for building in Cursor and Claude. SDK/API is for shipping production apps. Same memory, same API key.
Why founders choose it
Fastest path to proof
The first milestone is the recall/context panel filling in Playground — not architecture.
Two lanes, one backend
Ship with SDK/API in production. Use MCP while building in your IDE. One workspace, one API key.
India trust
INR billing through PayU, hard caps, no surprise bills. Built for Indian self-serve founders.
When to use MemoryNode
Use it when:
- your product has or is shipping AI chat or a copilot
- users return across sessions with stable accounts
- you map your app user ID to
owner_id - you want proof before building custom memory infra
What we are not
Not a RAG platform. Not an agent framework. Not a no-code studio. PayU INR only — no international self-serve checkout yet.
Proof to show
- Start here — Playground-first
- Demos — SaaS copilot walkthrough
- Two-call integration — ship path
- Pricing — Trial + Build, PayU INR