A
Android & Kotlin
Native endpoint collection, on-device protection and intuitive remediation experiences.
Detection architecture
Engineered for confidence and clarity.
A modern security stack combining Android telemetry, machine learning, cloud infrastructure and threat intelligence.
Technology stack
AI
TensorFlow models
Machine-learning classification built around carefully engineered malware indicators.
G
Google Cloud
Cloud-hosted model inference, secure communication and scalable processing.
API
Secure services
Authenticated REST and service communication designed for reliable security decisions.
Processing pipeline
From raw telemetry to a defensible decision.
01 — Intake
Security-relevant signals are collected
ARGUS gathers behavioural events, application metadata and analysis artefacts required for classification.
02 — Normalise
Signals become model-ready features
Data is validated, transformed and prepared for consistent analysis across applications and devices.
03 — Correlate
Multiple detection layers are combined
Static indicators, behaviour and intelligence context are evaluated together rather than in isolation.
04 — Decide
A risk class and confidence are produced
The platform returns a classification and the evidence needed to explain the decision.
05 — Act
Containment and user guidance begin
High-risk applications can be isolated while the user receives clear remediation steps.