Your AI agent
forgets everything
after every call.
Not anymore.
Add persistent memory to any LLM in one API call. Conversation history, key-value context, and scratchpads — with sub-millisecond reads from Redis. No infra to manage.
# Give your agent memory in 3 lines
import requests
# Store what the user said
requests.post(
"https://api.agenticmemory.ai/v1/memory/{spaceId}/messages",
headers={"Authorization": "Bearer amk_..."},
json={"role": "user", "content": msg}
)
# Recall last 20 turns for context
history = requests.get(
".../{spaceId}/messages?limit=20"
).json()
# Store persistent facts
requests.put(
".../{spaceId}/context/user_prefs",
json={"value": {"lang": "python"}}
)The problem every AI builder hits
LLM APIs are stateless. Every call starts from zero. Your users notice.
After 10-15 turns, older messages get dropped. Your agent "forgets" instructions mid-conversation.
Users re-explain preferences, project context, and prior decisions every new session.
Stuffing full history into every prompt burns tokens. At scale, context = cost.
Redis cluster, backup strategy, schema design, TTL management, tenant isolation… you didn't sign up to build a database.
Three memory primitives. One REST API.
Everything your agent needs to remember — organised, scoped, and fast.
Conversation History
Append messages, read last N turns with sliding window. Role-aware: user, assistant, system, tool.
POST /v1/memory/:spaceId/messages
Key-Value Context
Store and retrieve arbitrary JSON by key. User preferences, task state, learned facts — persistent across sessions.
PUT /v1/memory/:spaceId/context/:key
Scratchpad
Ephemeral working memory for multi-step reasoning. Write intermediate results, clear when done. Most competitors lack this.
PUT /v1/memory/:spaceId/scratchpad
Live in production in 5 minutes
No SDKs required. Pure REST. Works with any language, any LLM provider.
Create a memory space
A namespace for your agent. Scoped, isolated, with configurable TTLs and message limits. One space per agent or per user.
Read & write memory
Simple REST calls. Append messages, set context keys, use the scratchpad. Sub-millisecond reads from Redis, auto-persisted to MongoDB.
Inject into your prompts
Fetch recent history and context, include it in your LLM calls. Your agent now remembers everything.
Built for builders shipping AI products
Whether you're a solo hacker or a team building production agents.
Indie AI hackers
Ship your AI side project with memory in an afternoon. Free tier, no credit card, instant API key.
AI agent startups
Stop rebuilding memory infrastructure. Focus on your agent's logic. We handle persistence, caching, and tenant isolation.
GPU rental users
Already running models on gpusmarket.com? Toggle "Enable Memory" — your Ollama sessions automatically persist.
Product teams
Multi-agent architectures need shared state. Scoped spaces, API key permissions, and usage analytics per agent.
Why agenticmemory.ai
The memory layer that doesn't overcomplicate things.
| Agentic Memory | Mem0 | Zep | DIY Redis | |
|---|---|---|---|---|
| Read latency | <1ms | ~50ms | ~200ms | <1ms |
| Pro plan | $9/mo | $19/mo | Credit-based | $50+/mo infra |
| Setup time | 5 minutes | 15 min | 30 min | Days/weeks |
| Scratchpad | ✓ | ✗ | ✗ | Build it |
| Self-hostable | ✓ Docker | Enterprise only | ✓ | ✓ |
| GPU bundle | ✓ gpusmarket | ✗ | ✗ | ✗ |
| Vendor lock-in | None | Moderate | Low | None |
What people are building
Customer support agents
Remember issue history, past resolutions, and customer preferences across tickets and sessions. No more "can you repeat your account number?"
Coding assistants
Retain project architecture, coding conventions, and prior debugging sessions. Your AI pair programmer actually learns your codebase.
Personal AI companions
Adapt to user preferences, communication style, and life context over weeks and months. Memory turns a chatbot into a relationship.
Multi-agent workflows
Shared memory spaces let specialized agents pass context between research, planning, and execution stages without token overhead.
Enterprise onboarding bots
Long-running processes that span days or weeks need durable state. Memory spaces persist until you delete them.
GPU-powered local LLMs
Running Ollama on a gpusmarket.com rental? Enable memory with one click — your local models get cloud-grade recall.
Engineered for speed
Every read hits Redis first. MongoDB is the durable backup. Your agent never waits.
Messages, context, and scratchpad served from Redis lists and hashes. Sub-millisecond reads at any scale.
Every write syncs to MongoDB in the background. Cache misses fall back to durable storage automatically.
Each memory space is a separate namespace. Scoped API keys with read/write/admin permissions. Rate-limited per key.
<1ms reads
Auto-sync
Simple pricing. Start free.
No credit card required. Upgrade when you need more.
Pro
- 10 memory spaces
- 50,000 messages/month
- Configurable TTLs
- Semantic search
Memory is the next layer of AI infrastructure
The industry is moving from "do agents need memory?" to "which memory layer should I use?"
"Context engineering" is replacing "prompt engineering" as the core discipline of AI development. Memory infrastructure is becoming table stakes.— Industry consensus, 2026
Give your agents a brain
Free tier. No credit card. Live in 5 minutes.