Physical AI by AI Light

Trust What Machines See.

Protect the visual data behind real-world decisions.

AI Light combines real-time detection with capture-time cryptographic trust, helping cameras, sensors and autonomous systems verify that what they see is authentic and untampered.

The challenge

When the Input Is Compromised, So Is the Decision.

Robots, vehicles and edge AI systems increasingly act on camera and sensor data. A spoofed scene, injected feed or altered frame can mislead the system before a human ever sees the evidence.

Physical AI needs a way to assess the input and verify its source and integrity as data moves from the sensor to the decision engine.

The AI Light approach

Trust From Sensor
to Decision.

Combine signal analysis with cryptographic proof so receiving systems can make decisions with stronger evidence about the data they consume.

01

Capture

A camera or sensor produces real-world data.

02

Seal

SourceSeal binds capture to its source and protects integrity.

03

Analyze

AI detection checks for manipulation, spoofing or anomalous input.

04

Verify

The receiving system checks provenance and integrity.

05

Decide

Applications use the trust signals in their decision workflow.

Capabilities

A Trust Layer for Physical AI.

Trusted Capture

Establish verifiable provenance as visual data enters the system.

Sensor Identity

Bind data to a known device or protected capture environment.

Integrity Checks

Expose unauthorized changes between capture and processing.

Real-Time Detection

Analyze visual input for signs of spoofing, injection or manipulation.

Peer-to-Peer Verification

Let connected components verify data across the device pipeline.

Edge-Ready Integration

Bring trust closer to cameras, processors and embedded systems.

Trust architecture

Protect the Path From Reality to Action.

Verification can travel with the data as it crosses device, processor and application boundaries.

Camera / Sensor
SourceSeal
Detect + Verify
AI Decision System
Two complementary signals

Inspect the Signal. Verify the Source.

AI detection

Does the input show signs of manipulation?

Models analyze the content for synthetic, spoofed or altered visual data.

Cryptographic trust

Can the system verify where it came from?

SourceSeal provides evidence of capture origin and integrity for downstream verification.

Use cases

Built for Machines Operating in the Real World.

01 / MOBILITY

Automotive & ADAS

Strengthen confidence in camera data flowing into driver assistance and vehicle systems.

02 / AUTOMATION

Robotics

Help robots assess the authenticity and integrity of the visual input they rely on.

03 / INDUSTRY

Industrial Vision

Protect inspection and automation workflows that depend on trustworthy image streams.

04 / HARDWARE

Cameras & Sensors

Enable devices to create self-verifiable media at the point of capture.

05 / EDGE

Embedded AI

Connect sensor-level trust to on-device inference and verification.

06 / OEM

Device Platforms

Integrate a trust layer into camera, processor and secure hardware pipelines.

Integration

Designed for the Device Pipeline.

AI Light’s approach spans capture-time protection, edge analysis and downstream verification. Integration paths can include API, SDK and embedded or firmware-level deployment, depending on the device and use case.

Trusted Capture + Real-Time Detection + Cryptographic Integrity

AI Light for Physical AI

Give Machines a Way to Verify What They See.

Explore how AI Light can bring trusted capture and real-time verification to your physical AI system.