RobLabs · Your AI That Gets Things Done.
RUBI AI — AI Agent with Memory
Useful memory is more than an endless transcript. RUBI combines explicit owner rules, bounded conversation context and reviewed facts, keeping where information came from separate from what a model merely suggested.
Beyond a conversation
An assistant that forgets every preference forces repeated explanations. An assistant that saves every inference as fact creates a different risk: confident mistakes become permanent. RUBI distinguishes a conversation, a candidate memory and an approved fact. Context can persist without treating generated text as unquestionable knowledge.
Preserve an explicit rule without inventing a fact
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State a rule you want RUBI to apply in future conversations.
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Save the explicit rule under the owner scope.
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Keep researched information as sourced review candidates.
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Use reviewed facts and recent conversation context when answering later requests.
Product presentation
Available controls and recorded evidence
The assistant uses bounded conversation history and curated facts, and explicit rules are saved before the reply. Daily learning collects scoped, sourced research for review. Product knowledge can be shared across assistant channels without importing private school, company or personal records into public context.
Connections and operating conditions
Memory is not a claim that every past message is always available to the model. Records that were never saved cannot be reconstructed as evidence. Research findings are candidates until reviewed, and automated learning does not grant new permissions or activate a tool.
Security and permissions
Memory remains owner-scoped, and research preserves the permissions of its sources. Company and educational records follow their own access rules. Durable context must not become a hidden path for another person’s private data to enter a response.
Privacy policyQuestions about AI Agent with Memory
Does RUBI automatically believe everything it generates?
No. Model output does not automatically curate memory. Explicit rules and sourced candidates have different paths, and reviewed facts remain distinct from suggestions.
Can learning give an agent more permissions?
No. Learning can improve available context, but it cannot change owner policy, approve a new skill or unlock a private account.