EdgeLens AI helps smart-home and networking OEMs turn routers, cameras, and in-home sensors into on-device AI agents that understand presence, learn daily rhythms, and surface meaningful changes for families and caregivers. Raw video and sensor streams stay local by default.

Three outcomes on one private, on-device layer. Guardian, our first product, delivers Wellness & Care today.
What is happening at home right now?
For OEMs: a reusable context layer across devices, apps, automations, and subscriptions.
Does something unusual indoors need attention?
For OEMs: a differentiated indoor-safety service beyond outdoor and perimeter cameras.
Is a loved one following their normal rhythm?
For OEMs: a premium wellness and caregiver subscription, and a route into AgeTech and care ecosystems.
Awareness and Family Safety run on the same on-device layer as Guardian. EdgeLens is not a security-monitoring, emergency-response, or medical service.
A private, on-device home-awareness layer for aging-in-place. Guardian learns a home’s normal rhythm in days, then surfaces calm, graded signals only when something changes, like routine drift, prolonged inactivity, or an unusually long private-space visit.
Presence, home/away, daily-activity summary, and privacy zones.
Behavioral baseline, meaningful-change & inactivity alerts, caregiver notifications.
On-demand multimodal verification of fall-like events.
EdgeLens Guardian is a home-awareness and wellness product. It is not a medical device or emergency-response system.
We sell to the OEMs who ship the hardware, and we design around the people living with it.
Turn installed routers, gateways, and cameras into premium, privacy-first home-intelligence services spanning awareness, indoor safety, wellness, and care. No cloud video, no new hardware, CPU-first by design.
Designed to help OEMs launch a premium software tier on hardware they already ship, without adding cloud-video infrastructure.
Request the architecture brief →Families and caregivers get quiet peace of mind, knowing a parent is okay without cameras in private spaces, wearables to forget, or a stream of clips to watch.
The hard part isn’t a cloud demo. It’s private, reliable, low-cost inference on devices with tight CPU and memory budgets. EdgeLens is CPU-first by design, with on-demand multimodal verification, so the device’s primary job is never at risk.
Designed to port across router, camera, and hub silicon families via a thin integration layer.
On-device small models can finally run in real time on constrained hardware. IEEE 802.11bf-2025 standardized Wi-Fi sensing. Aging demographics and a caregiver crisis make private home awareness urgent, while rising cloud-AI costs squeeze OEM margins. The teams that embed on-device intelligence in this window will define the category.
EdgeLens AI builds privacy-first, on-device ambient intelligence for the smart home. Our software turns routers, cameras, and in-home sensors into local AI that understands a home’s daily patterns and surfaces meaningful changes, without sending raw home data to the cloud. We sell to smart-home and networking OEMs.
The buyer is smart-home and networking OEMs: router, gateway, camera, and hub makers. The beneficiaries are households, families, and caregivers. Aging-in-place is our initial commercial wedge.
Cloud camera AI streams video off-device, which adds cost, latency, and privacy risk, and it can’t cover private spaces. EdgeLens runs on-device, uses Wi-Fi sensing to cover those spaces, and keeps raw video and sensor streams local by default.
No. Raw video and sensor streams stay local by default. EdgeLens sends derived context, summaries, and authorized caregiver alerts, not raw private home data.
It is designed for CPU-first baseline sensing on constrained home silicon (router, camera, hub families), with optional camera/radar verification where device resources allow.
No. EdgeLens Guardian is a home-awareness and wellness product, not a medical device or emergency-response system.
No. It is designed to run on existing router, gateway, camera, and hub-class hardware where sufficient compute and sensor access are available.
“The next wave of home AI won’t live in the cloud. It will live in the room. We’re putting private, on-device intelligence into every smart home, so it quietly senses what matters, for the people you love.”
Built by a team that has shipped and scaled AI at Amazon, Google, and Apple, reaching millions of homes and cars.
Engaging select smart-home, networking, and AgeTech OEMs for paid design-partner evaluations.