Three-Layer Cognition, Continuous Evolution

From knowledge to preferences to logic — layered cognitive understanding makes your agent smarter over time.

Knowledge Layer

Extract domain knowledge graphs from conversation history with automatic entity and concept linking. Supports incremental updates to retain all valuable information.

Preference Layer

Continuously learns your language style, format preferences, and communication rhythm. Full-spectrum personalization from word choice to layout style.

Logic Layer

Memorizes reasoning chains and decision patterns — understanding "why you think that way." Complex problem-solving evolves with interaction depth.

Privacy-Preserving Inference Pipeline

Raw data is sanitized on-device; only minimal inference context reaches the cloud.

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On-device Sanitization PII replacement · context pruning
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Cloud Inference Model routing · smart scheduling
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On-device Restore Context reinjection · memory update

Smart Context Pruning

Relevance-scored dynamic context selection, reducing token usage by 50%

Cognitive Cache

Frequently accessed knowledge cached locally for zero-latency repeated queries

Model Routing

Auto-selects optimal model based on task complexity, balancing cost and quality

Credential Security

JWT auth + local encrypted storage, API keys never transmitted in plaintext

How We Compare

Dimension Traditional AI Assistants ComindX
Data Privacy Cloud-stored On-device first · sanitized transfer
Personalization Depth Session-level Continuous cognitive modeling
Token Efficiency Full context window Smart pruning · 50% reduction
Deployment Flexibility SaaS dependency Self-hosted · multi-channel
Model Freedom Single vendor LiteLLM · any model