Your AI Keeps Forgetting. Here’s the 5-Minute Fix.

Modern AI agents are clever - but forgetful.
Your chatbot might respond empathetically today and blank on your name tomorrow. That breaks immersion, burns tokens, and frustrates users. Why? Because most AI apps are stateless. They forget everything between sessions.
Recallio fixes that.
With one API call, Recallio adds scoped, persistent memory to any AI app - no vector DBs, no brittle RAG stack. Just memory that works.
Why Memory Matters
- Personalization that sticks: Preferences, quirks, history - retained and scoped per user.
- Consistency across time: Your AI sounds the same tomorrow as it did last month.
- Efficient context injection: Inject what matters. Skip bloated prompts.
- Privacy-first by design: Consent flags, TTLs, audit logs - out of the box.
Minimal Memory Stack (in 60 seconds)
import requests
API_KEY = "YOUR_RECALLIO_API_KEY"
def store_memory(user_id, content, tags=[]):
requests.post("https://api.recallio.ai/memory", json={
"user_id": user_id,
"content": content,
"tags": tags,
"ttl_days": 90,
"consent_flag": True
}, headers={"Authorization": f"Bearer {API_KEY}"})
def recall_memory(user_id, query):
response = requests.post("https://api.recallio.ai/recall", json={
"user_id": user_id,
"query": query,
"summary": True
}, headers={"Authorization": f"Bearer {API_KEY}"})
return response.json()["summary"]
Plug this into any LLM workflow—chatbots, copilots, support bots, agents. It just works.
Drop-In Advantages Over DIY Memory
- Scoped recall: Per user, project, or agent.
- Summarized context: Return compressed, usable memory chunks.
- Graph-mode recall (optional): Memory as structured knowledge.
- Interoperability: Works with OpenRouter, GPT-4, Claude, Mixtral, and more.
Try It Free
Spin up a memory-aware assistant with our API in minutes. No infra. No lock-in. Just context that lasts.
Get started now → https://app.recallio.ai/signup
Onboarding indie AI builders and agent devs today.