🧠 AI Infrastructure · Currently in private beta

The memory layer every AI agent is missing

MemoryEngine gives every AI agent persistent, intelligent memory — across every session, every platform, and every conversation. Two lines of code.

Join the waitlist See how it works

# Your AI agent, before MemoryEngine
user: "I'm building a SaaS in Python"
agent: "Great! What's your name?"   # asks every time

# Your AI agent, after MemoryEngine
from memoryengine import Memory

mem = Memory(api_key="me_live_...")

# Store memory after conversation
mem.add(messages=conversation, user_id="u_123")

# Retrieve context before next conversation
context = mem.get("What do I know about this user?", user_id="u_123")
# → ["Building a Python SaaS", "Targets Indian SMBs", ...]

The Problem

Every AI agent today has amnesia

You build a powerful AI agent. Users interact with it. The session ends. Tomorrow, the agent remembers nothing. Users repeat themselves. Personalisation is impossible. The agent feels like a toy, not a tool.

This is not a model problem. It is a memory infrastructure problem. MemoryEngine solves it at the infrastructure level — not as a feature, but as a universal layer any agent can use.

Without MemoryEngine

With MemoryEngine

Every session starts with zero context

AI remembers everything from every session

User repeats preferences every time

Preferences stored once, applied always

Generic responses for every user

Deeply personalised responses

Each AI tool is isolated

All agents share the same user context

💾

Episodic memory

Every interaction stored, searchable, and retrievable. Your agent knows exactly what was discussed and when.

🎯

Semantic memory

Extracts and stores persistent facts about users — preferences, goals, expertise — ready for every future session.

⚙️

Procedural memory

Learns how things are done — workflows, conventions, and patterns specific to each user or organisation.

🔗

Cross-agent memory

All your AI agents share the same user context. No more repeating yourself to each tool. Coming soon.

🔒

Privacy first

Full user control. View, edit, or delete any memory. On-premise deployment for enterprise. GDPR compliant.

⚡

Framework agnostic

Works with OpenAI, Anthropic, LangChain, AutoGen, LlamaIndex — any model, any agent framework.

How it works

Three steps. Ten lines of code.

Drop MemoryEngine into any existing AI agent without changing your architecture.

Install the SDK

pip install memoryengine — one command, minimal dependencies, works in any Python environment.

Store memories

After each AI conversation, call mem.add(). MemoryEngine extracts and stores relevant facts automatically.

Retrieve context

Before each conversation, call mem.get(). Inject the returned context into your system prompt. Done.

AI remembers everything

Your agent now knows every user's history, preferences, and goals — automatically, forever.