// LOADING: CONTINUOUS_IMPROVEMENT

Capture > Coach > Correct

// UPDATE: -61% RISK/MILE

Eradicate Risk

PASSIVE

100% RISK

WAYSENSE

39%

61% ELIMINATED

0

25

50

75

100

RELATIVE INCIDENT FREQUENCY

?

Passive tracking apps fail to improve driver behavior. WaySense succeeds. Through event-triggered video feedback, WaySense reduces incident frequency by over 60%*. Anything else is just surveillance.

*Source: Carney et al., University of Iowa. Effectiveness of event-triggered video feedback.

// GAMIFYING...

Safety Score

0

ANALYZING

BRAKE

FOCUS

SPEED

Gamification that works. Drivers receive a daily safety score. As behaviors like hard braking or speeding are corrected, the score updates in real-time.

// STATUS: LOGGING TRIP...

Trip Receipts

38mph

AVG SPEED

74mph

TOP SPEED

15 mi

DISTANCE

21 m

DURATION

6

EVENTS

TRIP DETAILS. Detailed trip logs provide a second-by-second breakdown of driver performance. Analyze route efficiency, safety incidents, and view integrated video evidence for every alert.

// LOADING: THE FUTURE OF MOBILITY

Deciphering the "Why" Behind the "What"

// ENGINE STATUS: WARMING UP

The Engine

THE ENGINE

INTELLIGO KERNEL v4.2

Core Architecture At the core of FiglioTech is IntelliGo, our next-generation machine learning platform. Designed to enhance driver safety and awareness, IntelliGo leverages state-of-the-art multimodal machine learning models to provide deeper insights into driving habits.

SYSTEM ONLINE: INFERENCE ACTIVE

Behavioral Analysis By capturing and analyzing real-world data from IMU sensors and computer vision inputs, it sets a new standard for understanding and enhancing driver behavior. The system processes telemetry in real-time, identifying risk patterns before they escalate.

System Telemetry

MODEL ARCHITECTURE Transformer (VLLM)

INFERENCE LATENCY < 12ms (Edge)

DATA FUSION 6-DoF + Vision

COMPUTE LOAD Optimized NPU

[ BEHAVIORAL_LABELLING_V1 ]

Maneuver Classification

INTELLIGO ACTIVE

MULTI-SENSOR FUSION

LATERAL G

0.00g

VELOCITY

45 MPH

SYSTEM STATUS

NOMINAL

Deep Vision Baseline

IntelliGo transforms standard telemetry into semantic intelligence. By fusing 6-DoF inertial data with computer vision, the system establishes a dynamic baseline for safe operation.

Anomaly Detection Active

Instant Signal Isolation. The neural engine identifies aggressive maneuvering independent of road geometry, flagging stability loss before standard sensors trigger a warning.

Semantic Context Layer

Beyond raw dynamics, IntelliGo maps environmental intent—distinguishing between necessary evasive actions (avoiding potholes) and erratic driving patterns.

Predictive Threat Modeling

High-frequency inputs trigger instant risk scoring. Rapid acceleration combined with velocity spikes are isolated and tagged as critical safety threats in real-time.