ORACLE
Robot X-Ray Vision for Humans
Your robot detects humans through concrete walls, in pitch darkness, in dust storms. Not cameras — WiFi signals. The robot knows someone is standing behind a shelf 20 meters away and pre-brakes two full seconds before a collision could happen. Zero safety incidents. Full-speed operation in shared human-robot spaces.
TOTAL ADDRESSABLE MARKET
$120B
TIER 1 // 02
ROBOT SAFETY IS REACTIVE
Cameras see humans only when they're in the field of view, unoccluded, and well-lit. By the time a camera spots a worker stepping out from behind a pallet rack, the robot is already too close to stop safely. The industry's answer: safety fences and speed limits. Robots in shared spaces crawl at under 1 m/s. That kills throughput.
- <1 m/s
- ROBOT SPEED IN SHARED SPACES
- 0°
- VISION BEHIND WALLS
- REACTIVE
- CURRENT SAFETY PARADIGM
FIVE MODELS. ONE PIPELINE. PROACTIVE SAFETY.
ORACLE inverts the safety paradigm from reactive to proactive. Five integrated models chain WiFi through-wall detection to adaptive fusion to pixel-precise tracking to behavioral mapping to motion prediction. The robot responds to hazards it hasn't seen yet.
MODULE CHAIN:WiFi + LiDAR + RGB → OSIRIS → HARMONIA → AZOTH → LOCI → KAIROS
- 01
OSIRIS
Through-Wall WiFi Detection
WiFi RSSI triangulation detects humans through walls, shelving, and machinery. 15-meter range. 500ms refresh. No wearables — uses existing WiFi infrastructure.
- 02
HARMONIA
Adaptive Sensor Fusion
Decides which sensor to trust moment-by-moment. Sunny warehouse? Camera 0.7, LiDAR 0.3. Dusty dock? LiDAR 0.8, WiFi 0.9. No manual tuning.
- 03
AZOTH
Pixel-Precise Detection
Not just "there's a person" but "forklift operator wearing a hard hat, moving at 1.2 m/s toward aisle 7." Full context when humans are visible.
- 04
LOCI
Behavioral Zone Mapping
Historical behavior maps. "Humans cluster in the break room 12-1pm." "Dock 3 has high foot traffic Tuesdays." Anticipate presence before any sensor fires.
- 05
KAIROS
Motion Prediction
Event-camera data for microsecond motion prediction. Human at 1.5 m/s toward robot path → predict collision in 2.1s → pre-brake NOW, not when visible.
FOR ROBOTICS
The $120B collaborative robotics market is throttled by safety certification. ISO 3691-4 and ISO/TS 15066 assume reactive safety. ORACLE exceeds these standards by being proactive — the robot responds to hazards it hasn't seen yet. This changes the regulatory conversation entirely.
- 01Robots operate at 2+ m/s in shared spaces instead of crawling at 0.5 m/s — 4x throughput
- 0250-robot warehouse gains ~$2M/year in additional productivity
- 03If proactive safety becomes the standard, competitors license or spend 5 years building their own
KEY NUMBERS
- 15M
- THROUGH-WALL DETECTION RANGE
- 2SEC
- PROACTIVE PREDICTION WINDOW
- 2+M/S
- SAFE OPERATION SPEED
- $120B
- ADDRESSABLE MARKET
WHERE THE VALUE IS
| WAREHOUSE AUTOMATION SAFETY | $40B |
|---|---|
| MANUFACTURING COBOT SAFETY | $35B |
| CONSTRUCTION SITE MONITORING | $15B |
| HEALTHCARE ROBOT SAFETY | $10B |
THE MOAT
OSIRIS is proprietary. Through-wall WiFi detection for robotics is published in academic literature but not commercialized. We own this implementation and the integration with multi-modal fusion. Patent territory. If this becomes the safety standard, it becomes a licensing business independent of any specific robot platform.
Proactive safety is the new standard.