Smart Home —
Distributed AI at the Edge

Caspar.AI’s proprietary sensing technology enables retirement communities to provide enhanced comfort and safety for their residents. Our technology powers features like wellness, resident inactivity and fall detection. 

Privacy

Caspar.AI runs at the edge — does not send sensitive data to the cloud, ensuring privacy.

Reliable & Low-latency

Edge Computing ensures reliability. The AI modules are compiled on your devices for low-latency.

Easy-to-use API

Caspar.AI’s API easily integrates with your buildings IoT platform to enhance their functionality.

Deep Context Al

Caspar.AI learns residents’ preferences and activities using CasparAdapt and CasparSense technology.

Caspar Edge Al Technology

Our compiler produces local and computationally-efficient AI inference models for the building IoT platform to power intelligent applications – ensuring you can check in on your loved ones. It preserves privacy by design and keeps the users’ sensitive data within the home.

CasparSense

CasparSense uses multi-modal sensors within the home to predict user wellness, activities and intents – helping you ensure comfort for residents throughout your properties. Our technology is compatible with voice assistants like Amazon Alexa and Apple. 

CasparAdapt

CasparAdapt is a library of Deep Co-Reinforcement Learning tools that are designed to intelligently adapt and personalize the home to residents. Our technology allows for a screenless UI and thus is easy-to-use for everyone.

Sample Applications

Build Applications with Caspar Al

Caspar.AI’s technology easily integrates with devices such as HVACs, Alexa, Apple, Apple, Somfy and GE to bring cutting-edge smart home Al technology to your building.

Fall detection for seniors

Setup IoT
platform

import casparSense
import iotPlatform
platform = iotPlatform(room="bathroom”)
sensor = ["thermal", "sound", "vision"])
User fall

sense = casparSense(room="bathroom")
prob = sense.fall()
Alert sent

if prob > 0.5:
   platform.alert(method="text")

Personalization and Adaptation
for a more helpful home

Week 1

User goes
to sleep
User controls
home

import casparSense
import iotPlatform
platform = iotPlatform(room="bedroom”)
sensor = ["thermal", "sound", "vision"])

Closes
shades
Turn off
lights

sense = casparSense(room="bedroom")
sense.run()

CasparAdapt learns
preferences

adapt = casparAdapt(room="bedroom")

Week 2

User goes
to sleep
CasparSense
understands
activity

@callback (userAction)
def userActionUpdate():
adapt.learnPrefs(sense.activity, userAction)

Closes
shades
Turn off
lights

@callback (sense.activity)
def automatedBehavior():
platform.takeAction(adapt.getLearnedPrefs(sense.activity))

IoT partners