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On this page
  • How Memory Retention Works
  • Session-Based Memory vs Long-Term Memory
  • Benefits of Memory Retention in Vult AI
  • Limitations of Memory Retention
  1. Züs Apps
  2. Vult
  3. Vult AI

Memory Retention

PreviousBatch ProcessingNextTechnical Implementation

Last updated 1 month ago

Vult AI incorporates memory retention to enhance user interactions by allowing AI to remember past conversations and user preferences. This feature ensures a more context-aware experience by maintaining a record of previous discussions, user queries, and attached files.

Vult AI uses Mem0 AI, a dedicated memory storage API, to handle user memory. This enables the AI to recall details from previous interactions, making conversations smarter and more personalized over time.

How Memory Retention Works

1. Memory Storage with Mem0 AI

  • Every AI interaction in Vult AI Chat is stored using Mem0 AI, which acts as a retrieval-based memory system.

  • The AI retains important details such as:

    • User queries.

    • AI-generated responses.

    • Any relevant metadata like timestamps

2. Memory Retrieval in Conversations

  • When a user asks a follow-up question, Vult AI searches the stored memory for relevant past conversations.

  • If a match is found, the AI retrieves previous responses and contextually enhances the new response.

  • Example:

    • User: "My name is Jack."

    • AI: "Nice to meet you, Jack."

    • User (later): "What’s my name?"

    • AI: "Your name is Jack."

3. Memory Integration in AI Chat and AI Agent

  • AI Chat:. Unlike traditional AI platforms, VultAI does not store any conversation data on its servers. Instead, when you interact with AI Chat, any essential information is temporarily captured to support more natural, continuous conversations. This session history is stored securely on your own allocation within the Züs decentralized storage network. It does not maintain context across different files.

  • AI Agent: Uses stored memory only within a single processing request and does not maintain context across different files.

  • Batch Processing: Does not leverage memory retention, as each file is processed independently.

Session-Based Memory vs Long-Term Memory

Feature
AI Chat (Home)
AI Agent (All Files)
Batch Processing

Memory Retention

Yes, via Mem0 AI

Yes, Via Mem0 AI

No, processes each request independently

Stored Interactions

Yes, saved in AI Chat Folder

Yes, saved in AI Agent Folder

Batch Folder Within AI Agent

Contextual Awareness

Yes, recalls previous prompts

No, processes only current file

No contextual linking

Benefits of Memory Retention in Vult AI

1. Personalized AI Conversations

  • The AI remembers important user details (e.g., name, project details, or past requests).

  • Follow-up questions feel more natural, as the AI recalls previous responses.

2. Faster and More Relevant Responses

  • Instead of repeating context, users can build upon past interactions, improving efficiency.

  • AI can reference previous discussions instead of starting from scratch.


Limitations of Memory Retention

1. Limited to AI Chat Only

  • The AI retains memory only in conversations and does not remember previous file-based AI Agent interactions.

2. No Cross-Session Memory Sharing

  • If a user starts a new chat session, past memory is not carried over unless explicitly recalled.

3. File Attachments Are Not Memorized

  • While the AI can process attached files, it does not store the file itself in memory.

  • Users must re-upload the file in future sessions if they want the AI to reference it again.

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