Company profile
Algorized
People-sensing foundation models for industrial machines and robots.
- Category
- Robotics
- Headquarters
- Campbell, California
- Sells to
- Mixed
- Business model
- Licensing
- Deployment
- Edge
- Pricing
- Not published
- Builds own models
- Yes
- Modalities
- Sensor
What Algorized does
Algorized builds people-sensing foundation models for industrial machines and robots, transforming commodity sensors into Predictive Safety Engines and Human-Machine Interaction Engines. They aim to eliminate the trade-off between human safety and production speed by enabling proactive awareness instead of reactive stops. Algorized develops advanced sensing and perception technologies to protect life, utilizing complex algorithms for wireless sensors to detect human presence, track and position, and monitor vital signs, even through obstacles. Their Edge-AI models are fully responsive to the highest precision of human presence detection and interface seamlessly with people, places, and sensors to monitor well-being and reduce risk of harm. The technology is sustainable and inobtrusive.
Products
- People-Sensing Edge-AI ModelsFoundation models that bring real-time people awareness to machines, enabling secure ranging, positioning, tracking of moving and stationary objects, and behavioral patterns even through obstacles for real-time decision making utilizing existing wireless sensors.
- Human-Machine Interaction EngineAn Edge-AI powered engine that allows machines to sense human intent and adapt in real-time across multiple modalities (Wi-Fi Sensing, UWB, and mmWave).
- Algorized UWB RadarTechnology for detection through obstacles.
Key capabilities
- People-sensing Edge-AI models
- Real-time positioning and tracking
- Presence sensing through obstacles
- Vitals detection (breathing, heart-rate)
- Wireless data communicating sensors (UWB Radar, Wi-Fi)
- Signal data pre- and post-processing
- Algorithms and edge-ML
- Multi-modality sensor fusion
- Secure ranging, positioning, tracking of moving and stationary objects
- Behavioral pattern detection through obstacles
Use cases
- Industrial people safety
- Robotics human-machine interaction
- Automotive in-cabin sensing
- Infrastructure applications
- In-car safety (sensing people presence and vitals detection to reach zero fatalities)
AI approach
Algorized builds people-sensing foundation models and Edge-AI models for industrial machines and robots. They transform commodity sensors into Predictive Safety Engines/Human-Machine Interaction Engines, enabling machines to sense human intent and adapt in real-time. Their technology uses complex algorithms for wireless sensors (UWB Radar, Wi-Fi) to detect human presence, track and position, and monitor vital signs even through obstacles. They focus on real-time decision making and multi-modality sensor fusion.
Tech named: Edge-AI, foundation models, complex algorithms, wireless sensors, UWB Radar, Wi-Fi Sensing, mmWave, edge-ML, Multi-modality sensor fusion
Industries served
- Industrial
- Robotics
- Automotive
- Smart-infrastructure
What it says sets it apart
- Nervous system for Physical AI
- Transforms commodity sensors into Predictive Safety Engines/Human-Machine Interaction Engine
- Eliminates trade-off between human safety and production speed
- Advanced sensing and perception technologies to protect life
- Radical edge-AI models technology interfaces seamlessly with people, places and sensors
- Monitors well-being and reduces risk of harm
- Exceptionally sustainable and entirely inobtrusive solution
- Utilizes complex algorithms for wireless sensors for human presence detection, tracking, positioning, and vital signs monitoring, even through obstacles
- New spatial dimension with secure ranging, positioning, tracking of moving and stationary objects as well as behavioral patterns even through obstacles
Funding rounds we track
Run Ventures, Amazon Industrial Innovation Fund, Acrobator Ventures
From the AI funding tracker — rounds as reported by the linked publications.
This profile was compiled from Algorized's own public pages in July 2026 and reflects what the company states about itself — not an endorsement or an independent audit of those claims. Facts are extracted with AI and filtered by an automated check that drops any named product, customer or certification missing from the source pages. Full method. Something out of date? Tell us.