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Edge AI & On-Device Memory

Cognee is bringing AI memory to the edge with cognee-RS, our Rust-based SDK designed for resource-constrained devices. Run the full memory pipeline (ingestion, semantic organization, retrieval) directly on-device, sub-100ms recall and data stay local.

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The Edge AI Opportunity

Picture this: Your smart glasses capture a conversation during a run, instantly recall your to-do list, and feed you directions - all offline, with zero data uploaded. Or your smart-home hub analyzes your evening routine, suggests energy optimizations for better sleep, and monitors wellness patterns without sending a single byte to the cloud. This is the future and the promise of edge AI memory.

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cognee-RS: Rust-Powered Memory for Devices

cognee-RS is our experimental Rust SDK. It is a port of cognee’s proven memory architecture to edge devices like phones, smartwatches, glasses, and smart-home hubs. It combines:
  • A lean retrieval engine optimized for constrained resources
  • Support for on-device LLMs
  • Seamless hybrid switching to cloud when needed
  • Full multimodal support (text, images, audio)

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Core Capabilities

Fully Offline Operation Run with Phi-4-class LLMs and local embeddings—no internet required for queries or retrieval. Toggle to hosted models with a single config flag when you have connectivity and need more power. High Accuracy We’re targeting 90%+ answer accuracy, matching our Python SDK. The local semantic layer ensures retrieval fidelity even with smaller models. Graph-aware retrieval boosts accuracy 15-25% through structural cues. Hybrid Execution Route tasks intelligently: local for embeddings, cloud for heavy entity extraction, or split dynamically based on connectivity, battery, and latency requirements. Multimodal Fusion Handles text, images, audio, and sensor data. Real-time fusion from device inputs (mic + camera) creates holistic context that a cloud-only approach can’t match. Resource Orchestration Dynamic scheduling caps memory and CPU usage. Heavy processing doesn’t interrupt core device functions—retrieval stays prioritized while batch ingestion happens during idle time.

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Use Cases: Where Edge Memory Excels

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Personal Voice Assistants

Smart earbuds and wearables that remember your conversations, preferences, and context—without uploading your private discussions to the cloud.
“What did Sarah say about the project deadline during our walk yesterday?”
Local conversation memory enables instant recall. Sync only opt-in summaries, never raw audio.

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Smart Home & Wellness

Baby monitors, vital-sign wearables, and home hubs that analyze patterns locally—complying with GDPR and HIPAA by design.
  • Sleep pattern analysis without cloud dependency
  • Anomaly detection that works during internet outages
  • Behavioral insights that stay on your network
Your health data stays yours.

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Robotics & Autonomous Systems

Drones, robots, and autonomous vehicles need real-time memory access for navigation and decision-making—especially in dead zones. 
Robot enters new environment
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cognee-RS builds local context map
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Real-time retrieval: "Have I seen this obstacle type before?"
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Decision without connectivity delay
No connectivity? No problem. Local context drives decisions.

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Industrial IoT

Factory-floor sensors, offline kiosks, and field equipment often operate in network-constrained environments. Edge AI enables:
  • 24/7 local reasoning without persistent connection
  • Anomaly detection at the source
  • Bandwidth savings—only critical events sync to cloud
  • Continued operation during network outages

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Trade-Offs and Mitigations

Edge isn’t effortless. Smaller models have tighter context windows. Devices have limited compute and battery budgets. Complex reasoning may exceed local capabilities. cognee-RS addresses these constraints:
ChallengeMitigation
Limited context windowGraph-aware retrieval for precision
Complex reasoningHybrid execution—offload when needed
Battery constraintsDynamic scheduling, idle-time processing
Storage limitsSemantic compression, smart eviction
Model sizeSupport for Phi-4 class, upgradeable
cognee-RS is currently experimental. Early conversations with partners are giving promising results.

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The Vision: Memory Everywhere

The future isn’t cloud-only AI. It’s AI that runs where you are: on your phone, your glasses, your watch, your car. AI that remembers your context without uploading your life to someone else’s servers. cognee-RS is how we get there: the same semantic memory layer that powers enterprise deployments, compiled to run on the devices in your pocket. Privacy-first. Real-time. Offline-capable. Memory-enabled.