The world model for real-world data
Newton is the general intelligence layer that the physical world never had. It fuses diverse physical data to uncover patterns of physical behavior no single signal reveals, and generalizes across many use cases — predicting unknown failures, understanding the root cause in plain language, and automating the response.
Newton
WHY A PHYSICAL WORLD MODEL
Newton: a physical world model that learns from sensor data
Physical data is fundamentally different from the text and images of the online world — it needs a model built from the ground up for it. That model is Newton.
LLMs vs. real world
Newton: a physical world model that learns from sensor data
Improve worker safety and boost operational efficiency with safety and machine monitoring agents that use existing sensors to discover anomalies, prevent failures, and optimize equipment performance.
Generalization
Adaptable World Models let machines learn their own behavior and keep adapting
Traditional industrial AI needs a custom model for every machine, site, and use case — slow to build, expensive to maintain. Newton becomes a local world model that reflects how your systems actually run — and keeps evolving as your environment changes.
Deploy anywhere
Run wherever physical work happens
Physical operations run far beyond the walls of any data center. From remote sites and distributed assets to bandwidth-constrained industrial facilities — every second matters and security can't be compromised. Newton brings frontier intelligence to where physical work happens—running seamlessly across cloud, on-premises, and edge infrastructure.
Digital world and LLMs
Trained on 80% of text, 10% image and <5% video
4 modalities: text, video, images and audio.
Each modality treated individually.
Real world
50% physical sensor data, 20% video, <5% text
Hundreds of sensor modalities can be critical for every use case.
Requires fusion of multiple sensor modalities and data streams.
THE MODEL
One model.
Endless real-world applications.
One model.
Endless real-world applications.
01
Start out-of-the-box
Deploy Archetype’s pre-built Physical AI agents for common machine, process, and workforce use cases — all on one world model that connects hundreds of sensor types.
02
Build and deploy your own
Create custom agents on the same world model, programmed in natural language — no retraining per task.
03
Fine-tune to your operations
Adapt with a handful of examples, or fine-tune Newton on your proprietary data, in your own infrastructure.
Newton combines physical sensor data and contextual information into a single embedding space, creating a real-time representation of the physical world that serves as both a physics-based and semantic model of reality.
Newton combines physical sensor data and contextual information into a single embedding space, creating a real-time representation of the physical world that serves as both a physics-based and semantic model of reality.
Newton combines physical sensor data and contextual information into a single embedding space, creating a real-time representation of the physical world that serves as both a physics-based and semantic model of reality.
how it works
How newton sees the physical world
Machine behavior:
//
motion
//
power
//
electrical
//
etc
Time series sensors
Human behavior:
//
presence
//
activity
//
intent
Video
Context:
//
scene description
//
customer prompts
TEXT
_01
Physics World Model
Physically accurate analysis of hundreds of data types out of the box: time-series sensors (motion, power, electrical) and quantitative tasks like trajectory prediction, anomaly detection, and multivariate analysis.
_02
Semantic World Model
Analysis of physical data in natural language, like talking to a human: contextual inputs such as video and text, and human-like descriptions, alerts, and explanations.
Machine behavior:
trajectory prediction
multivariate analysis
anomaly detection
classification
Machine behavior:
//
descriptions
//
alerts
//
explanations
Put Newton to work
Talk with a Physical AI expert and see how to deploy Newton Agents across your use cases, mapped to the outcomes you care about.
blog
The Archetype AI Blog
May 20, 2026
Adaptive World Models: Closing the Operational Intelligence Gap
Explore how Adaptive World Models close the operational intelligence gap in physical industries—helping machines learn their own behavior directly from sensor data, adapt locally to each deployment, and turn complex signals into actionable operational states.
Nov 20, 2025
TimeFusion: Natural-Language Intelligence for Your Sensors
Introducing Newton TimeFusion, Archetype's 2.0B-parameter multimodal model that unifies human language and time-series sensor data using Universal Tokens. This breakthrough creates a "Physical AI" layer, allowing users to have natural conversations with sensors and machines for actionable insights, prediction, and control.
_Schedule a Demo
Put Physical AI to work
Talk with one of our Physical AI experts and learn how to deploy Newton Agents across a wide range of use cases — mapped to the outcomes you care about.
