STATANLY Multimodal Event Analytics Platform

AI Operating System

Multimodal Event Analytics Platform

A unified enterprise AI platform for creating, training, deploying and managing event analytics scenarios across video, audio, sensors, VMS and enterprise systems.

  • Turns isolated CV modules into a single intelligent event analytics layer
  • Combines Computer Vision, Speech Analytics, LLM, VLM, Generative AI and low-code scenario orchestration
  • Enables users to create new AI scenarios from natural-language task descriptions
Video + Audio Multimodal analytics for events, violations and operations
GenAI + VLM Natural-language scenario creation and dataset preparation
Scenario Engine Low-code rules, workflows and operational automation
Cloud / OnPrem Hybrid architecture for enterprise deployment
STATANLY multimodal event analytics platform core
AI Models Library Ready-made modules for safety, behavior, operations, quality and industry scenarios.
AI Factory Data collection, annotation, synthetic datasets, model training and registry.
Scenario Engine Create complex monitoring and automation logic from reusable AI modules.
VMS / Enterprise Integration Connect cameras, VMS, SCADA, ERP, access control, BI and APIs.
How it works

From Natural Language Task to Deployed AI Scenario

The core idea of the platform is simple: the user describes the monitoring task in natural language — the platform automatically builds the AI pipeline, prepares data, creates the scenario and deploys analytics to cameras and infrastructure.

Natural language AI pipeline creation

The user does not need AI expertise: STATANLY turns a business request like “detect workers without helmets” or “find smoke and fire” into data preparation, model creation, scenario logic and deployment.

Platform components

Core Components of the Platform

STATANLY is not just a set of detectors. It is a full platform layer for creating and operating AI event analytics across enterprise infrastructure.

Multimodal Event Analytics

Video streams, audio, sensors and metadata are processed together to detect events, violations, operational risks and process deviations.

Scenario Engine

Low-code orchestration layer for zones, triggers, rules, schedules, escalation logic, notifications and multi-event scenarios.

AI Factory

Tools for collecting data, annotating datasets, generating synthetic examples, training models and managing model versions.

LLM / VLM Layer

Natural-language task interface and visual-language understanding for converting business intent into AI scenarios and datasets.

Cloud Hub

Centralized management of models, licenses, scenarios, analytics, reporting, multi-site operations and deployment workflows.

On-Prem Runtime

Local AI processing inside the enterprise perimeter with support for GPUs, VMS integration, edge nodes and secure infrastructure.

Architecture

Unified Architecture for Inputs, AI Processing and Outputs

The platform connects existing cameras, microphones, sensors, VMS and enterprise systems into one AI operating layer that generates events, alerts, reports, dashboards and integrations.

STATANLY platform architecture inputs AI processing outputs
AI Factory

Continuous Creation and Improvement of AI Models

AI Factory is the internal loop that allows the platform to create new models, improve existing ones and adapt analytics to specific customer environments, objects and camera angles.

AI Factory

The platform combines real data, synthetic generation, VLM-assisted labeling, model training and feedback loops into a repeatable process for building new AI scenarios faster.

1

Data Collection

Collect examples from cameras, archived events, customer data and controlled test environments.

2

Synthetic Data

Generate rare or hard-to-capture cases to improve robustness and reduce model launch time.

3

VLM Labeling

Use vision-language models for object understanding, pre-labeling and dataset validation.

4

Training

Train and fine-tune AI models for specific events, sites, industries and camera conditions.

5

Model Registry

Store model versions, metrics, scenarios and deployment configurations in one controlled system.

6

Feedback Loop

Use real incidents, false positives and operator validation to improve models continuously.

Example scenarios

Typical AI Scenarios Created on the Platform

The same platform foundation can be used to create simple and complex event analytics scenarios across industrial safety, operations, logistics, retail, HoReCa and infrastructure.

PPE Detection

Detect missing helmets, vests, masks, gloves, glasses and other required protective equipment.

Violation Detection

Detect unsafe behavior, restricted area access, perimeter breaches and policy violations.

Fire & Smoke Detection

Recognize smoke, fire and emergency events in production, warehouses and public spaces.

Phone Usage

Control phone usage and distractions in prohibited industrial or operational zones.

People Counting

Analyze occupancy, customer flow, queues, crowd density and workload across locations.

Process Monitoring

Monitor equipment, production processes, operational bottlenecks and abnormal events.

Deployment

Deployment for Enterprise Infrastructure

STATANLY supports cloud, secure on-premise, edge and hybrid architectures, making it possible to deploy AI analytics across one site, a distributed network or thousands of camera streams.

Cloud Hub

Centralized management of scenarios, models, analytics, licenses, events and multi-site reporting.

On-Prem

Local processing inside the customer infrastructure for data sovereignty and enterprise security requirements.

Edge Runtime

Low-latency AI inference near cameras or sites to reduce traffic and server requirements.

VMS Integration

Connection to existing video systems, IP cameras, RTSP, ONVIF, event streams and metadata.

Platform impact: faster creation of AI scenarios, unified event analytics instead of isolated detectors, continuous model improvement and scalable deployment across enterprise sites and camera networks.