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#2“Which deals are at risk this week and why?”
“Has my account usage changed since last quarter?”
“What’s the one setting most customers miss before churn?”
The result: frustrated users, support tickets that don’t go away, and retention that never improves.
Why Current Chatbots Fail
Forget past chats → every conversation resets to zero
Only read static docs → blind to real-time product data
Can’t connect big-picture dots → no reasoning across events or accounts
Can’t explain “what matters most” → users don’t get actionable answers
This is where we saw the gap.
Recallio: A Reasoning + Memory Layer for AI
We built Recallio.ai as the missing context layer for AI assistants, copilots, and agents. Instead of duct-taping RAG pipelines and vector DBs, Recallio gives you scoped, compliant memory + live product data + knowledge base in one API.
Think of it as three layers fused into one:
Memory Layer – every conversation remembered, threaded, searchable, continuous
Live Data Layer – connects to account activity, preferences, real-time state
Knowledge Layer – docs, guides, expertise, all summarized and relevance-ranked
Your AI now answers with the full story, not a guess.
Three Ways to Use It
Upgrade your existing chatbot → add memory + product data reasoning in minutes
Drop-in AI support agent → one script, goes beyond docs, remembers history
Embed via API → scoped memory and recall features inside your product UI
Why It Matters
No repetition → users don’t need to re-explain
Full context → history + real-time product state combined
Smarter outcomes → personalized, proactive guidance
Retention boost → conversations feel continuous and human
And all of it is SOC2/GDPR/HIPAA-ready by default. Scoped memory per user/team/project, with TTL, audit logs, and right-to-forget controls.
What’s Different?
Most “AI memory” projects today stop at retrieval. Recallio adds reasoning.
Works with any LLM → drop-in with 2 API calls
Streamlined Memory → simple, secure, compliant
Graph Memory → uncover deep relationships across people, topics, events
Zero maintenance → no manual RAG tuning, no stale embeddings, no vector DB sprawl
Why We’re Sharing Here
We know HN readers have been burned by hypey chatbot startups. We’re not pitching “AGI assistants for everything.” We’re building a very specific missing piece: contextual, compliant memory + reasoning for SaaS teams shipping AI features fast.
It’s not perfect yet. We’d love to hear what you’d want from a memory/reasoning layer in your own product—especially if you’ve duct-taped your own RAG stack and felt the pain.
Recallio.ai