Technical Guides & Proof.
Deep-dive architectural deployments, exact VMS configuration steps, and real industrial impact case studies. No fluff, just engineering and operational results.
Technical proof
Everything you need to move from research to a pilot.
Implementation guides, deployment checklists, and real case studies, the proof to scope a pilot without sitting through a generic demo.
Guide format
Each guide answers implementation, latency, integration, and deployment questions with technical specificity.
Commercial fit
Each guide connects technical evaluation directly to a scoped pilot, not generic background reading.
Decision support
Includes a downloadable pilot planning checklist you can use to scope a first deployment.
Milestone XProtect AI Integration Checklist
Step-by-step technical configuration for routing DHI edge analytics into Milestone XProtect alarm and Smart Client workflows over ONVIF.
Genetec Security Center AI Integration Guide
How to add DHI edge safety analytics to a live Genetec Security Center deployment using ONVIF events and the Security Center alarm engine.
Reducing Rail Track Trespass Risk Across 300 Miles of Analog CCTV
A deployment deep-dive on running autonomous video intelligence across active rail corridors without fiber backhaul and without replacing analog CCTV hardware.
Why Cloud AI Cannot Stop a Forklift in Time
An architectural review of the physical latency limits of cloud inference versus edge-native processing, and why momentum makes the difference fatal.
On-Premise Video Analytics: A Data Privacy and Security Guide
How edge-native video analytics keeps footage on premise, narrows the attack surface, and simplifies the privacy and compliance story for IT and Legal.
The Industrial AI Pilot Planning & Implementation Checklist
A technical framework for deploying edge compute on an existing VMS network without disrupting live security operations, with success criteria you can defend.
Warehouse Near-Miss Detection Guide
How warehouse teams can use existing CCTV to detect forklift near misses, aisle conflicts, blocked walkways, and repeat safety hot spots.
Forklift-Pedestrian Safety AI Checklist
A practical checklist for evaluating forklift-pedestrian collision prevention with camera AI, edge inference, VMS alerts, and measurable pilot criteria.
CCTV AI Analytics Guide for Existing Camera Estates
How to evaluate CCTV AI analytics for existing cameras, including stream access, edge processing, VMS workflow, privacy, and pilot metrics.
How to Evaluate Edge AI Safety Platforms
A buyer guide for comparing edge AI safety platforms by latency, camera fit, VMS integration, privacy posture, reliability, and pilot proof.
Best Edge AI Workplace Safety Platforms 2026: Evaluation Criteria
A neutral evaluation framework for choosing edge AI workplace safety platforms in 2026 without relying on vendor rankings or unverified claims.
Best AI CCTV Safety Platforms for Warehouses: What to Evaluate
A warehouse buyer guide for evaluating AI CCTV safety platforms by forklift risk, near-miss capture, fire cues, VMS fit, and operator trust.
On-Premise Video Analytics Buying Guide
A buying guide for evaluating local video analytics, raw-video control, event routing, and privacy review before deployment.
Forklift Safety AI Buyer Guide
How warehouse teams should evaluate forklift-pedestrian detection, blind-corner warning, alert routing, and near-miss review.
Genetec AI Safety Integration Options
A practical overview of ways to route edge AI safety events into Genetec Security Center workflows.
Milestone XProtect AI Safety Integration Options
How to evaluate AI safety alert routing inside Milestone XProtect without replacing the recording workflow.
Edge AI vs Cloud AI for Forklift Safety
Compare local inference and cloud analytics for forklift-pedestrian conflict, blind-corner alerts, and near-miss capture.
AI Fall Detection CCTV vs Wearable Fall Detection
Compare camera-based person-down detection and wearable fall detection by coverage, adoption, privacy, and response workflow.
Track Trespass Detection Using Existing CCTV
How transit and rail teams can evaluate track trespass detection with current station, depot, and corridor cameras.
On-Premise Video Analytics for Privacy-Sensitive Facilities
A privacy review guide for healthcare, public-sector, and enterprise sites evaluating local video analytics.
Why Use-Case Count Is Not Enough in Safety AI
Why buyers should evaluate depth, camera fit, workflow fit, and proof quality instead of choosing by the longest detection list.
DHI vs Cloud Workplace Safety AI
A neutral architecture comparison between DHI's local inference model and cloud-first workplace safety analytics.
Buyer-Stage Comparison Tables for Safety AI
Comparison tables for early research, technical validation, pilot planning, and enterprise rollout decisions.
Where DHI Is Not the Right Fit
A trust-focused guide to situations where DHI may not be the right choice for a site, workflow, or buying team.
Latency Benchmark Template for Edge AI Safety
A template for measuring camera-to-alert latency during an edge AI safety pilot without overstating results.
False-Positive Taxonomy for Safety AI
A practical taxonomy for classifying nuisance alerts by scene, model, threshold, workflow, and review causes.
Existing CCTV Readiness Scorecard
A scorecard for deciding whether current cameras, streams, VMS workflows, and response paths can support a safety AI pilot.
Edge Hardware Capacity Guide
How to think about edge node sizing, camera count, model count, stream quality, and failover for safety AI pilots.
VMS Event Payload Examples
Example safety event fields for routing AI detections into VMS alarms, bookmarks, maps, and review queues.
Milestone Webhook and Alert Example
A plain-language example of how an AI safety event can map into a Milestone XProtect alert workflow.
Genetec Alarm Routing Example
A practical example of mapping edge AI safety events into Genetec Security Center alarms and review flows.
ONVIF Event Mapping Example
How to think about ONVIF event mapping when connecting edge AI detections to existing video workflows.
Security One-Pager for Edge AI Safety
A concise security review summary for local inference, raw-video control, event routing, access control, and auditability.
Deployment Timeline for Edge AI Safety
A sample 30-day timeline for camera review, edge-node setup, VMS routing, pilot review, and rollout decision.
Pilot KPI Worksheet for Safety AI
A worksheet for defining pilot event class, camera scope, response path, success metrics, and review cadence.
Warehouse Near-Miss Benchmark Template
A template for collecting warehouse near-miss events by zone, shift, camera, event type, and review outcome.
Case Study Template for Edge AI Safety
A case study structure for documenting problem, camera estate, deployment model, pilot metrics, review findings, and approved outcomes.
Demo Video Route Structure for Safety AI
A route and metadata checklist for publishing demo videos only after real assets, thumbnails, transcripts, and approvals exist.
AI Search Prompt Tracking Template
A template for tracking how AI search systems describe DHI, cite DHI pages, and compare the brand over time.
Downloadable Safety AI Pilot Documents
A source-document checklist for creating downloadable pilot worksheets, scorecards, and review templates.
Continue Exploring
Review the architecture behind the guides
Move from written guidance into the underlying edge deployment, latency, and integration model.
Compare AI monitoring with manual review
Use the comparison page when the real buying debate is staffing, operator load, and escalation speed.
See a concrete operational use case
Jump from proof assets into a production scenario with real failure modes, workflows, and deployment fit.
Use the guide, then validate it on your cameras.
Don't let the guide be the end of it. Take the checklist, a clear deployment path, and a direct line to ask implementation questions.
The checklist is built for operators evaluating a live pilot in the next 30 days.
Request a demo
See the flow on a real operating scenario and scope a pilot around one facility or corridor.
See deployment architecture
Review camera ingest, edge inference, alert routing, and what stays on-premises.
Get the implementation checklist
Download the deployment checklist buyers use before green-lighting an industrial AI pilot.
Talk to an engineer
Bring camera count, VMS constraints, latency expectations, and privacy requirements to a technical review.