Stop re-explaining everything to your AI. getmem gives your agents persistent, intelligent memory — context that actually works.
import getmem mem = getmem.init("gm_your_api_key") # Save what matters mem.add("user_123", "Prefers concise answers in English") # Get the right context, every time context = mem.get("user_123", query=user_message) # Drop it straight into your prompt prompt = f"{context}\n\nUser: {user_message}"
No pipelines, no config files, no vector DB to manage. Import, init, done. Works with any LLM framework.
Doesn't just retrieve chunks — understands what context is actually relevant to each query. Better output quality.
Entities and relationships stored in a graph, not just flat embeddings. Your agent remembers how things connect.
Isolated memory per user ID. Multi-tenant by default. Each user's context stays separate and private.
No monthly minimums. Pay per operation — like Stripe for memory. Scales with you from 0 to millions of users.
Your data stays yours. Delete any user's memory instantly. SOC2 compliant (in progress).
| Feature | getmem.ai | Mem0 | DIY RAG |
|---|---|---|---|
| Lines of code to integrate | 2 | ~15 | 100+ |
| Graph memory | ✓ | ✓ | ✗ |
| Intelligent context selection | ✓ | Partial | ✗ |
| Pay per use | ✓ | ✗ | ✗ |
| Per-user isolation | ✓ | ✓ | Manual |
| Setup time | < 2 min | ~30 min | Days |
getmem integrates in 2 lines of code vs ~15 for Mem0. We charge pay-per-use with no monthly minimums, while Mem0 is subscription-based. We focus on output quality — returning the right context every time, not just the most similar chunks.
Yes — getmem is fully LLM-agnostic. It returns a formatted context string you inject into any prompt, regardless of which model or provider you use. LangChain and LlamaIndex compatible.
Vector DBs are primitives — you still manage embeddings, indexes, and retrieval logic. getmem is a complete memory layer: storage, retrieval, entity resolution, and context selection in one call. Start in 2 minutes instead of days.
Pay-per-use. You're charged per mem.add() and mem.get() call — like Stripe for memory. No monthly minimums, no seats, no tiers to figure out. Scales from zero.
Yes. Memory is isolated per user ID. You can delete any user's memory instantly. We don't train on your data. SOC2 compliance in progress.
We're onboarding early developers now. Drop your email and we'll reach out personally.