How to Add Scoped, Summarized AI Memory Without Touching a Vector DB

Recallio Team

— 2 min read
How to Add Scoped, Summarized AI Memory Without Touching a Vector DB
How to Add Scoped, Summarized AI Memory Without Touching a Vector DB

AI agents are smart. But stateless.
Every session is a blank slate. Every user repeats themselves. Every dev hacks memory storage from scratch.

That’s broken.

Recallio fixes it. Scoped, persistent, queryable memory in seconds - without managing vector DBs or duct-taping LangChain pipelines.

What Makes Recallio Different?

Forget toy memory tools or low-level embedding hacks.

Recallio is:

  • Scoped by default: Per user, agent, project, or workspace. No leaks.
  • Summarized for LLMs: Returns compressed, token-efficient memory.
  • Compliance-ready: TTL, consent, and audit baked in.
  • Cross-platform: Use with Claude, GPT, Mixtral, your own model, or any agent.

This is not “just storage.” It’s memory as a service - engineered for real apps.

Build a Memory-Ready Agent in 90 Seconds

import requests

headers = {"Authorization": "Bearer YOUR_API_KEY"}

# Save memory
requests.post("https://api.recallio.ai/memory", json={
  "user_id": "alex42",
  "content": "Customer prefers emails at 9am, hates Zoom.",
  "ttl_days": 60,
  "tags": ["prefs", "support"],
  "consent_flag": True
}, headers=headers)

# Retrieve summarized recall
res = requests.post("https://api.recallio.ai/recall", json={
  "user_id": "alex42",
  "query": "How should we follow up?",
  "summary": True
}, headers=headers)

print(res.json()["summary"])

Boom. Your agent now remembers preferences, quirks, and history, without holding the entire transcript in RAM.

Use Case 1: Personalized Recall with TTL

requests.post("https://api.recallio.ai/memory", json={
    "user_id": "u789",
    "content": "User prefers PDF invoices sent on Mondays.",
    "tags": ["billing", "preferences"],
    "ttl_days": 30,  # auto-forgets after 30 days
    "consent_flag": True
}, headers=headers)

Use Case 2: Semantic Summary Before LLM Call

res = requests.post("https://api.recallio.ai/recall", json={
    "user_id": "u789",
    "query": "How should I send this month’s invoice?",
    "summary": True
}, headers=headers)

print(res.json()["summary"])  # -> “Prefers PDFs, Mondays, 30-day expiry.”

Use Case 3: Memory Debugging or Manual Review

res = requests.get("https://api.recallio.ai/memory/view", params={
    "user_id": "u789",
    "filter_tags": "billing"
}, headers=headers)

for item in res.json():
    print(item["content"], item["ttl_days"], item["timestamp"])

Use case 4: Graph Memory for Entity Relationships (Advanced)

requests.post("https://api.recallio.ai/graph", json={
    "user_id": "u789",
    "content": "Sarah leads project Apollo. She reports to Mike.",
    "project_id": "apollo"
}, headers=headers)

res = requests.post("https://api.recallio.ai/graph/search", json={
    "user_id": "u789",
    "query": "Who leads Apollo?"
}, headers=headers)

print(res.json()["results"])

requests.post("https://api.recallio.ai/memory", json={
    "user_id": "pm_alex",
    "team_id": "legal",
    "content": "Client requested NDA redline changes on clause 7.",
    "ttl_days": 90,
    "tags": ["contract", "NDA"],
    "consent_flag": True
}, headers=headers)

requests.post("https://api.recallio.ai/recall", json={
    "team_id": "legal",
    "query": "NDA status with client?",
    "summary": True
}, headers=headers)

Memory That Works, With Zero Overhead

With Recallio, you get:

  • Scoped isolation (user, team, agent, project)
  • Optional semantic compression
  • Structured graph-based recall
  • Built-in expiration, audit, and consent flags

No vector DBs. No fragile pipelines. Just memory infrastructure you control.

Recallio replaces:

  • RAG stacks you babysit
  • Vector DBs with zero compliance logic
  • Platform lock-in from OpenAI memory that can’t be queried or audited

It adds:

  • Summarized recall
  • Scoped TTL memory
  • Graph-mode queries (advanced)
  • Zero infra to manage

Build Smarter AI. Start Free.

Recallio is onboarding devs, founders, and agent teams now.
It’s the fastest way to make your AI apps remember, securely and smartly.

Start now at https://app.recallio.ai/signup - plug in memory that just works.

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