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Platform & Hardware
Compatibility, cameras, and core platform questions
Ken360 is a hardware independent solution. This works with a wide variety of compatible off the shelf hardware.
The AI platform is built to accommodate 3 different modes of deployment: Cloud, On Premise and Hybrid.
At Intelense, we don't collect any data outside the client location. The data remains with the data owner.
Ken360 has machine learning and self-learning capabilities. The AI continuously updates over time without manual intervention, adapting to new patterns and improving accuracy for each client deployment.
Intelense is designed to work with standard IP cameras (RTSP streams), ONVIF-compatible cameras, and a wide range of IoT sensors. There is no requirement to replace existing infrastructure — our platform connects to your current cameras and sensors via software integration.
No. Intelense AI models are optimized to deliver high accuracy even on standard 720p or 1080p cameras. Higher resolution cameras can improve detection granularity, but are not a prerequisite for most use cases.
Deployment
Deployment timelines and multi-site management
Cloud deployments can be operational within 2–5 business days. On-premise deployments typically take 2–4 weeks depending on network complexity and camera count. Our team manages the full deployment process with minimal disruption to your operations.
Yes. Intelense supports multi-site enterprise deployments from a single management dashboard. Sites can be added independently and managed centrally, with unified reporting across all locations.
Privacy & Security
GDPR, data storage, facial recognition, and access control
Yes. Intelense is designed for GDPR compliance. Raw video data is not transmitted outside the client's network without explicit consent. We support data processing agreements (DPAs) for European clients and provide data retention controls.
Intelense does not perform facial recognition unless explicitly configured for an authorized use case. Our default models detect persons, objects, and behaviors — not individual identities. Privacy-by-design is a core principle of our platform.
Intelense uses role-based access control (RBAC) with multi-factor authentication (MFA). Administrators can define granular permissions for each user, including camera visibility, alert access, and report exports. All access is logged for audit purposes.
ROI & Getting Started
Returns, timelines, pilots, and how to begin
Based on aggregated client deployments (2024–2025), organizations report an average of 40% improvement in operational efficiency, 95% reduction in PPE violations, and 80% faster incident response times. Exact ROI depends on use case, site complexity, and baseline operations.
Most clients see measurable operational improvements within the first 30 days of deployment. Full ROI is typically realized within 6–12 months, depending on the complexity of the deployment and the baseline processes being improved.
Yes. Intelense offers proof-of-concept (POC) pilot programs for qualified enterprise clients. A pilot typically runs for 30–60 days on a subset of cameras and use cases. Contact us at enquiries@intelense.ca or book a demo to discuss a pilot for your organization.
The fastest way to get started is to book a 30-minute discovery call with our team. We'll assess your current camera infrastructure, discuss your use case, and outline a deployment plan. You can book at intelense.com or reach us at enquiries@intelense.ca.
Product FAQs
Select a product to see its specific questions and answers
Yes. KenVision integrates with major VMS platforms including Milestone, Genetec, Avigilon, and Axis Camera Station via API and RTSP feed integration. Contact us to confirm compatibility with your specific VMS.
KenVision AI models achieve up to 99% accuracy in standard conditions for anomaly detection, object classification, and person tracking. Accuracy varies by use case, lighting conditions, and camera quality. We provide model performance reports during onboarding.
KenVision AI models support infrared and low-light camera feeds. The platform integrates with night-vision or thermal cameras for 24/7 coverage. Accuracy in low-light conditions is optimized through model fine-tuning during deployment.
Yes. KenVision includes PPE detection for hard hats, safety vests, gloves, and other protective equipment. Violations trigger real-time alerts to site supervisors. The system is deployed in construction, manufacturing, and industrial environments. For comprehensive workplace safety analytics, see also KenSafety.
KenVision transforms retail security cameras into intelligence tools that track footfall, measure dwell time, analyse customer journey patterns, detect queue lengths, and trigger staffing alerts — all from your existing camera infrastructure.
KenSafety detects PPE non-compliance, unauthorised zone entry, vehicle proximity to workers, slip and fall risks, fire and smoke, equipment malfunction indicators, and crowd density alerts. Detection categories are fully customisable per site.
KenSafety delivers AI-generated alerts in under 2 seconds from event detection to notification. Edge deployments achieve sub-1-second latency — critical for time-sensitive applications such as PPE violations and restricted zone breaches.
Yes. KenSafety uses edge computing to process video locally on site, sending only metadata and alert payloads to the cloud. This enables real-time safety monitoring with as little as 1–5 Mbps of uplink bandwidth per camera — ideal for remote construction and industrial sites.
For on-premise KenSafety deployments, we recommend a GPU-enabled edge server (NVIDIA T4 or equivalent) with at least 16GB RAM and 100GB SSD storage per node. Requirements vary based on camera count and site complexity — our team assesses your environment during onboarding.
Yes. KenHome is designed for non-technical users. The mobile app provides real-time alerts in plain language (e.g., "Fall detected in kitchen"). Setup is guided by the Intelense team, and ongoing management requires no technical skills.
KenHome detects falls, unusual inactivity, smoke and fire, unauthorised entry, vehicle anomalies, and pet behaviour changes. Alerts are delivered to the family's mobile app within seconds, distinguishing between routine activity and genuine safety events to minimise false alarms.
Yes. KenHome connects to standard IP cameras, ONVIF-compatible devices, and common smart home platforms. In most cases there is no need to replace existing hardware — our software layer adds AI intelligence on top of what you already have.
KenAgri is built for scale. The platform ingests feeds from multiple cameras and sensors across large agricultural sites, correlating environmental data (soil moisture, temperature, humidity) with visual AI detections to provide actionable agronomic insights across thousands of acres.
KenAgri monitors soil moisture, temperature, humidity, light intensity, wind, and rainfall alongside visual AI detections from cameras. This multi-sensor fusion enables precision irrigation scheduling, early pest detection, and crop health scoring in near real time.
Yes. KenAgri integrates with drone imagery feeds for periodic aerial crop health assessments. Drone data is fused with ground-level sensor readings to produce field-level NDVI maps and yield forecasts, giving farm managers a complete view of their operation.
Yes. KenRobotics includes human-robot collaboration (HRC) safety zones. The system detects worker presence and automatically adjusts autonomous robot speed or stops movement to prevent collisions. All collaborative robot behaviours comply with ISO 10218 safety standards.
KenRobotics supports SLAM (Simultaneous Localisation and Mapping), LiDAR-based navigation, and vision-guided path planning. Robots build and update internal maps of their environment in real time, enabling dynamic obstacle avoidance without pre-programmed fixed routes.
KenRobotics is deployed in warehousing and logistics, industrial manufacturing, infrastructure inspection, and safety surveillance. The platform supports both indoor autonomous mobile robots (AMRs) and outdoor inspection drones, adapting to structured and semi-structured environments.
Cloud deployment processes IoT analytics on Intelense-managed infrastructure — ideal for organisations prioritising ease of management. On-premise keeps all data and processing within your facility, ideal for strict data residency needs. Hybrid combines both: edge processing handles latency-sensitive tasks while the cloud handles reporting, dashboards, and long-term storage.
For cloud deployments, KenIoT data is stored in the region of your choice — Canada, US, or EU. For on-premise deployments, all data remains within your facility. Intelense does not access or share your operational data with third parties.
KenIoT provides REST APIs and webhooks for integration with ERP systems (SAP, Oracle), ITSM platforms (ServiceNow), BI tools (Power BI, Tableau), and custom enterprise software. SCIM identity management and SAML 2.0 SSO are also supported.
KenIoT edge nodes require a GPU-enabled device (NVIDIA Jetson or equivalent) with at least 8GB RAM and 64GB storage for lightweight deployments, scaling up to full server-grade hardware for high-throughput industrial environments. Our team sizes the deployment based on sensor count and data volume.
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