AI Video Intelligence for Cameras Edge-First, Cloud Optional

A privacy-focused AI video analytics platform that works with existing CCTV systems to generate near real-time alerts and insights.

AI runs locally on edge devices by default, with optional cloud GPU inference when required.

Join early access — we're onboarding pilot customers.

Turn Cameras into Intelligence — Quickly

DevsNeom analyzes live video streams to detect events, trigger alerts, and surface actionable insights. By default, only events and metadata are synchronized to the cloud — not raw video.

Connect Your Streams

Works with IP cameras and DVR/NVR systems that expose video streams via industry-standard protocols.

RTSP ONVIF

RTSP — Real-Time Streaming Protocol

ONVIF — Open Network Video Interface

✔ No camera replacement required

✔ No vendor lock-in

Edge-First Processing

Video frames are analyzed locally on on-premise systems to minimize latency and preserve privacy.

Low Latency Flexible Deployment Privacy-aware processing

Near Real-Time Alerts & Analytics

Detected activities are converted into structured events and analytics. Only metadata is sent to the cloud for dashboards and reporting.

Alerts Analytics Event history

Simple Setup

How It Works

From cameras to intelligent insights in four steps

Connect Cameras

Integrate existing IP cameras or DVR/NVR streams using RTSP or ONVIF.

Process with AI

Video frames are analyzed in real time using computer vision models running locally or, when enabled, on secure cloud GPU infrastructure.

View Alerts & Insights

Access dashboards, alerts, and reports through the DevsNeom cloud platform.

Generate Events

Detected activities are converted into structured events and analytics.

Currently developing our initial release focused on real-time detection and alerting, with dashboards and cloud management available from day one.

Initial Focus Industries

Edge AI for Early Use Cases

Designed for environments where privacy, latency, and existing infrastructure matter

Smart City Pilots

Limited-scope deployments for traffic observation, public space monitoring, and safety pilots using existing camera infrastructure.

Pilot areas:

Traffic Flow Observation Congestion Indicators Pedestrian Movement Public Space Activity Incident Awareness Pilot Safety Monitoring

Enterprise Campuses

Access control, visitor tracking, and workplace safety monitoring for corporate environments.

Target sites:

Restricted Area Monitoring Visitor Movement Patterns Perimeter Observation Safety Zone Awareness Unauthorized Presence Detection After-hours Activity

Retail Analytics

Heatmaps, queue management, and inventory tracking without cloud latency.

Target sites:

Footfall Trends Queue Observation Dwell Time Indicators Store Activity Patterns Incident Detection Occupancy Awareness

Warehouses & Logistics

Inventory tracking, forklift safety, and package sorting monitoring for supply chain operations.

Target sites:

Safety Zone Monitoring Forklift Movement Awareness Loading & Unloading Areas Storage Area Activity Operational Flow Visibility

Technology

Technology Foundation

Computer vision models optimized for real-time video analysis.

On-Premise Processing

AI inference can run locally on on-premise systems. Video remains within the customer's network when edge mode is enabled.

Metadata-Only Cloud Sync

Only structured metadata, alerts, and analytics are synced to the cloud for centralized management and reporting — not raw video.

Flexible Deployment

Compatible with standard servers and edge devices. Customers can choose edge-only processing or enable cloud GPU inference based on deployment needs.

Integration Readiness

Designed with a modular architecture that supports event-based outputs and future API integrations as the platform evolves.

Camera Compatibility

Works with IP cameras and DVR/NVR systems exposing RTSP or ONVIF streams

RTSP

Real-Time Streaming Protocol

Industry standard for IP camera streams

ONVIF

Open Network Video Interface

Universal interoperability standard

Deployment Options

Edge AI or Cloud AI — Your Choice

DevsNeom is built to support multiple deployment models without forcing trade-offs.

Edge AI Mode

Run inference locally for privacy-sensitive or low-latency environments. Video never leaves your premises.

Cloud AI Mode

Forward selected frames to cloud GPU infrastructure for managed inference when on-premise resources are limited.

Hybrid Deployments

Mix edge and cloud processing across sites. Deployment mode can be selected per site and adjusted as requirements evolve.

Why Edge AI

Why Edge-First AI?

Our Focus on Privacy and Performance

Real-time Alerts

Run analytics on-device for fast detection
Reduce delay vs cloud round-trips
Act faster on critical events

Lower Bandwidth & Storage Costs

No need to stream full video to the cloud
Sync events and metadata by default
Reduce recurring bandwidth and storage overhead

Privacy by Design

Keep video on-premises when required
Control what leaves the site (events/metadata)
Supports privacy-sensitive deployments

Resilient Operations

Works even if cloud connectivity is down
Automatic event batching and retries
Designed for real-world conditions

About Us

Our Mission

At DevsNeom, we believe intelligent video analytics should be accessible, private, and efficient. Our mission is to democratize edge AI — empowering organizations of all sizes to unlock insights from their video infrastructure without compromising on security or performance.

Our Vision

A world where every camera is a smart sensor, every frame generates value, and privacy is never an afterthought. We're building the future of visual intelligence — one edge device at a time.