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Local AI + smart glasses

How local AI can fit between smart glasses, your phone and your own models

Smart glasses are usually constrained by battery, thermals and vendor APIs. A practical local-AI architecture therefore does not require every model to run inside the frames: the glasses can provide an interface, the phone can bridge sensors and commands, and a nearby desktop or self-hosted service can run heavier models. A self-hosted service is one that runs on a computer or server you control.

A practical four-layer architecture

  • Glasses layer: capture or display only the capabilities the specific device exposes.
  • Mobile bridge: normalize device events, permissions and short interactive requests.
  • Local compute: run suitable language, vision or speech models on a phone, desktop or local server.
  • Optional remote compute: use a user-selected cloud provider only when the task exceeds local hardware or the user explicitly prefers it.

Why this can be more private

Local-first design can reduce how much raw personal context needs to leave the user's own devices. It is not automatically private, however: privacy depends on which glasses APIs, model backends, telemetry settings, and cloud services are enabled. CyanBridge makes that data flow an explicit design choice.

Tasks that fit different compute tiers

  • Small text commands, classification and simple retrieval can often fit on mobile or modest local hardware.
  • Vision-language analysis may be more practical on a desktop GPU or efficient multimodal model depending on latency and memory.
  • Long-context personal assistants can combine local retrieval with a local or self-hosted LLM instead of sending the entire archive to every request.
  • Real-time accessibility features require stricter latency and reliability testing than casual assistant prompts.

Related pages

Open source smart glassesOmi, MentraOS, OpenGlass and where CyanBridge fits in the open ecosystem.Ray-Ban Meta alternativePrivacy comparison and why local-first matters for glasses.Buy smart glasses — price & checkout guideSigned quote before payment, shipping, taxes and delivery explained.Qwen and Gemma model selectionCompare model families using hardware, latency, context and tool-use requirements.Visual accessibilityUnderstand useful hands-free visual assistance and Be My Eyes / OOrion workflows.Benchmarks to publishSee the measurements CyanBridge is using to turn local-AI claims into evidence.

Start from the glasses you already own

Choose a device ecosystem and check its current integration status before planning a local-AI workflow.

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