Building Cross-Platform AI Memory: Architecture Deep Dive

The AI landscape is fragmented. You might use ChatGPT for coding, Claude for writing, Gemini for research, and Perplexity for quick lookups. Each tool has strengths. But they all share the same weakness: they don’t know who you are.

This isn’t just inconvenient - it’s a fundamental barrier to AI actually being useful. The context you’ve built in one tool doesn’t transfer to another. Your preferences in Claude don’t inform your Gemini experience. It’s like having four assistants who never talk to each other.

We built Haiven to solve this. Here’s how.

The Architecture

Haiven sits as a layer between you and every AI tool you use. It captures memories from your conversations, stores them in a unified system, and surfaces relevant context wherever you need it.

Capture Layer

Memories enter the system through multiple channels:

Browser Extension: Watches your conversations in ChatGPT, Claude, Gemini, and other web-based AIs. Automatically extracts decisions, preferences, facts, and context.

MCP Server: For Claude Desktop and other tools that support the Model Context Protocol, we integrate directly. Your AI assistant can both read from and write to your memory.

API: Direct integration for custom workflows. Build your own capture systems or connect with existing tools.

The key insight: capture should be invisible. You shouldn’t have to manually save memories. The system learns from natural conversation.

Storage Layer

Memories are stored in a structured format with rich metadata:

{
  "content": "Prefers TypeScript over JavaScript for all projects",
  "type": "preference",
  "world": "Work",
  "importance": 0.8,
  "decay_score": 0.95,
  "temporal": {
    "status": "current",
    "confidence": 0.9
  },
  "embedding": [...],
  "created_at": "2024-12-15T10:30:00Z",
  "last_accessed": "2024-12-27T14:15:00Z"
}

Each memory has:

• Content: The actual information
• Type: What kind of memory (preference, fact, decision, goal, etc.)
• World: Life category (Work, Health, Learning, etc.)
• Importance: How significant is this
• Decay score: How fresh is this memory
• Temporal status: Is this current, historical, or scheduled
• Embedding: Vector representation for semantic search

This structure enables sophisticated retrieval. We can find memories by meaning, not just keywords.

Retrieval Layer

When you start a conversation with any AI, Haiven:

1. Analyzes context: What is this conversation about?
2. Searches memories: Which stored memories are relevant?
3. Ranks results: Considers recency, importance, semantic similarity
4. Surfaces context: Provides relevant memories to the AI

This happens in under 500ms. The AI receives your relevant memories before you even notice.

The “Worlds” Model

We organize memories into eight life categories we call “Worlds”:

• Work: Projects, colleagues, decisions
• Personal: Family, home, daily life
• Health: Medical, fitness, wellness
• Learning: Skills, knowledge, education
• Finance: Money, investments, planning
• Relationships: Social connections, communication
• Personal Brand: Public presence, reputation
• Spiritual: Values, meaning, growth

This isn’t just organization - it’s retrieval optimization. When you’re in a work context, work memories surface first. When you’re discussing health, health memories take priority.

Cross-Platform Consistency

The key innovation is that all of this works across platforms.

Tell Claude once that you prefer direct feedback. That preference is stored. When you use ChatGPT later, that preference is surfaced. When you try Gemini next week, it’s there too.

Your AI memory becomes a unified layer that every tool can access. The specific AI doesn’t matter - your context travels with you.

Privacy by Design

Your memories are yours. We built this with several principles:

1. User ownership: You can export or delete your data at any time
2. Selective sharing: You control what each AI tool can access
3. Local options: For sensitive use cases, memories can stay on-device
4. Audit trails: See exactly what’s been accessed and when

The goal is AI that knows you deeply while respecting that this knowledge is yours.

What This Enables

With cross-platform memory, entirely new workflows become possible:

• Start a project in ChatGPT, continue in Claude, finish in Gemini - with full context
• Switch AI tools based on their strengths, not their knowledge of you
• Build expertise over time that compounds across every AI interaction
• Have truly personal AI that understands your full picture

This is what AI should have been from the start: a persistent, knowledgeable partner that grows with you over time.

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Ready for AI that actually knows you? Try Haiven - your memories, across every AI.