Edge processing
Custom vision models running on local hardware such as NVIDIA Jetson, so video is analysed on site and footage stays where it was recorded.
Real-time AI computer vision security, local edge processing, and automated threat alerts for commercial facilities. Traditional video surveillance requires constant human monitoring and usually only records incidents after they happen. Active security uses AI computer vision to detect threats automatically and alert your team in real time.
OUR CAPABILITIES IN
AI Surveillance & Security Solutions
We audit your current systems, marketing, and funnels.
We architect a custom strategy bridging your exact gaps.
We deploy the tech, content, and pipelines required.
We seamlessly roll out the solution with zero downtime.
We track every metric to ensure it meets our strict KPIs.
We optimize the winning channels to compound your returns.
AI surveillance for Kerala sites, built in Kochi and installed on the cameras you already own. The system watches every camera at once, recognises the events the site has defined, and sends a person an alert with the clip while there is still time to act. Video is analysed on hardware at the site, so footage never has to leave the premises and the system keeps working when the internet does not.
Kerala has more cameras per business than it has people to watch them. A godown in Kalamassery, a jewellery showroom on MG Road, a hospital in Kozhikode, a resort in Wayanad and a gated community in Kakkanad all record everything and see almost nothing until after the fact. The value of the footage is in the moment, and the moment is what a person staring at a wall of screens misses.
We define the events with the people who run the site, tune the models on the site’s own cameras through the monsoon and the night, integrate the alerts with the way the site already responds, and measure false alarms until every alert is worth a look. The existing security company and the camera installer stay; the system reduces the screens they have to watch.
Privacy is designed in rather than promised. Events are detected without identifying individuals wherever identification is not needed, retention is enforced, access is logged, and the DPDP Act and the site’s own rules are applied from the start.
Custom vision models running on local hardware such as NVIDIA Jetson, so video is analysed on site and footage stays where it was recorded.
Connected to the IP cameras and recorders already installed, wherever they are capable, without ripping out infrastructure.
Intrusion, restricted zones, loitering, queues, occupancy, vehicles and plates, safety compliance, unattended objects, defined per site.
To security teams, managers and control rooms by app, WhatsApp, SMS and integration with existing systems.
Footfall, dwell, queue and occupancy data for retail, hospitality and facilities teams, without identifying individuals.
Local processing, retention rules, masking where required and access control to the DPDP Act.
Access control, alarm, building management and incident systems connected so an alert becomes an action.
Model accuracy, hardware health and alert quality monitored, with false positives tuned down over time.
| Engagement | Typical timeline |
|---|---|
| Site survey and camera assessment | 1 to 2 weeks |
| Pilot on a single site or zone | 4 to 6 weeks |
| Full site deployment | 6 to 12 weeks |
| Multi-site rollout | Phased, per site |
| Monitoring and support | Monthly |
Intrusion after hours, restricted zones, loading bay monitoring and vehicle tracking across godowns and yards.
Safety compliance, restricted area entry and incident detection on sites where a missed event is expensive.
Showroom monitoring, footfall, queues and loss prevention without identifying shoppers.
Perimeter, after-hours and restricted area monitoring for facilities with many entrances.
Perimeter, back-of-house and occupancy monitoring for resorts and hotels.
Perimeter and access monitoring for gated communities and apartment complexes, with privacy rules respected.
A site survey and a pilot on one zone to prove the events and tune the alerts before committing.
Full site deployment on a fixed scope with the integrations the site needs.
Model, hardware and alert quality monitored and tuned monthly.
A distribution godown on the industrial belt cares about one thing between ten at night and six in the morning: is anyone inside who should not be. A jewellery showroom cares about the opposite hours: how many people are inside, whether the queue at the counter is too long, whether anyone has been standing by the exit for ten minutes, and whether the back office door opened when it should not have. The same technology serves both, but the events, the schedules and the alerts are entirely different, and they have to be defined with the people who run each site.
We start every deployment with that conversation, then pilot on one zone until the security team trusts what the system tells them.
Defined with the manager and the security team, not from a list.
After-hours rules and business-hours rules for the same camera.
One area proven before the rest is committed.
False alarms measured and tuned down until every alert matters.
Site conditions in Kerala are their own engineering problem. Monsoon light changes how a camera sees from June to September. Rain on a lens, fogged housings and insects at night produce the false alarms that make control rooms ignore a system. Power cuts and voltage swings reset recorders. Internet connections on industrial estates and plantations drop for hours. A system designed in a lab fails on contact with all of it.
Edge hardware at the site keeps detection running through outages and disconnections, models are tuned on footage from the site’s own seasons, and the survey identifies the cameras, housings and power arrangements that need fixing before the software can be trusted.
Local hardware with power protection keeps detecting.
Models trained on the site’s real conditions, not stock scenes.
Housings, angles and coverage fixed before deployment.
Alerts queue and sync when the connection returns.
An alert is only useful if it reaches someone who will act on it, on a channel they will see, with enough information to decide. For most Kerala sites that means a WhatsApp message with a clip to the guard on shift and the manager, an alarm in the control room where there is one, and a door or a light triggered through the existing access control where the site has it. Every event is logged with its clip so the morning review takes minutes and the audit trail exists.
We integrate with the security provider’s process rather than replacing it, and the installer keeps responsibility for the cameras.
WhatsApp, app, control room or alarm, by event and time.
The alert carries the footage so the decision is immediate.
Doors, lights and alarms through existing systems.
Every event logged with its clip for a quick daily check.
A showroom that identifies every customer, a community that tracks every resident, a hospital that stores months of corridor footage with open access: each is a liability under the DPDP Act and a breach of the trust the cameras are meant to protect. Most security events do not need to know who a person is, only that a person is where they should not be or that a queue has formed. We detect events without identification wherever that is enough, mask faces and plates where required, enforce retention automatically and log every view and export.
For communities, campuses and hospitals we work through the rules with the operator before anything is installed, including signage and the policy residents or patients are entitled to see.
Events recognised without recording who a person is.
Faces and plates hidden where the site or the law requires.
Footage kept as long as needed and deleted automatically after.
Who viewed or exported what, recorded.
Infynix Solutions is registered separately in India, the United Kingdom and the United Arab Emirates. This page covers India. The same service, written for the other markets:
Yes, our vision software connects directly to standard video surveillance and IP camera streams.
No. Video analytics process locally on your on-site edge hardware for privacy.
Usually. Most IP cameras and recorders installed in recent years are capable. A site survey confirms which cameras work, which housings or angles need fixing, and where coverage is missing, before anything is committed.
Detection runs on hardware at the site with power protection, so it continues through outages and disconnections. Alerts are delivered on the local network and synced when the connection returns.
No. Video is analysed on site and stays there. Only the detected events and their short clips are sent to the people who need them.
Yes, because the models are tuned on the site’s own footage across seasons, and the survey fixes the housings and angles that cause rain and night false alarms before deployment.
Yes. Occupancy, queues, after-hours movement and restricted areas are detected without identifying individuals, with faces masked where required and retention enforced.
No. The system works with the existing guards, control room and camera installer, reducing the screens a person has to watch and sending alerts into the process they already follow.
A survey takes one to two weeks, a pilot on one zone four to six, and a full site six to twelve depending on cameras and integrations. Multi-site rollouts are phased.
By tuning the models on the site’s real conditions, measuring alert quality every month and adjusting until every alert is worth a look. A system that cries wolf gets ignored, so this is the part we spend the most time on.