Footage is only checked after something goes wrong
By then the theft, the accident or the missed delivery has already happened.
Computer Vision & AIoT
Computer vision development that turns your cameras into alerts, counts and records
We add AI to the cameras and devices you already have, so they spot intrusions, missing safety gear, defects and queues, count people and vehicles, and log attendance. Every model is tested on your own footage before it sends a single alert.
- Works with most IP cameras
- Edge, on-site or cloud
- False alarms measured before go-live
Engineering team in Jaipur, India. Building software since 2019, 500+ projects delivered. Working with businesses in the US, UK, Europe, UAE, Australia and India.
Your cameras record everything. Nobody has time to watch it.
Guards and supervisors can't watch every screen
Attention drops after the first hour, and night shifts and remote sites get the least cover.
Counts and checks are still done by hand
Visitors, vehicles, stock on shelves and defects on the line are counted on paper or not at all.
Basic motion alerts cry wolf
Trees, shadows, rain and animals trigger alarms until someone switches them off.
Computer vision closes all four gaps: it watches every camera all the time, raises only the events you care about, and turns each one into a record your team can act on.
Computer vision development services, built around what you need to know
AI video analytics on existing CCTV
Intrusion and line-crossing alerts, loitering, crowding, abandoned objects and after-hours activity, from the cameras you already own. Alerts go to WhatsApp, email or your control room.
Face recognition attendance and access
Opt-in face check-in at gates, sites and offices, matched to your HR or payroll system, with a card or PIN fallback for anyone who does not enrol.
Tainaat WorkforceOSVisual quality inspection
Cameras on the line flag scratches, dents, missing parts, wrong labels and misprints, and save an image of every rejected item for review.
People and vehicle counting
Footfall, queue length, occupancy and dwell time for stores and buildings; vehicle counts, licence plate reading (ANPR) and gate logs for yards, parking and logistics.
Safety and PPE compliance
Detect missing helmets, vests and masks, people in danger zones near machines or vehicles, smoke and fire signs, and falls, with a snapshot for every event.
Image and document recognition
Read meters, labels, serial numbers and ID cards from photos taken in the field. For invoices, statements and forms, see Document AI.
Document AICameras are one sensor among many. We also connect biometric terminals, RFID readers, GPS trackers and temperature, door and energy sensors, so every device event lands in the same alert and report flow.
Choose where the AI runs, and where your video goes
The same models can run in three places. We recommend one after the footage test, based on your bandwidth, privacy needs and number of cameras.
| Edge device at the camera or site | Server in your building | Cloud | |
|---|---|---|---|
| Best for | Remote sites, a few cameras, fast alerts | Many cameras on one campus or plant | Many small sites, central dashboards |
| Does video leave the site? | No, only events and snapshots | No, only events and snapshots | Yes, streams or clips are sent |
| Works if the internet drops? | Yes, events sync later | Yes, inside your network | No |
| Main cost | A small AI device per site | One GPU server | Monthly compute and bandwidth |
| Updates | Pushed to each device | One server to update | Managed centrally |
Whichever you choose, your recorder or video management system keeps recording as it does today. We add detection on top of it.
We tune every camera on your footage before it sends an alert
An alert system people ignore is worse than none. So we measure how often it is right before it goes live.
- Test on your own clips. We run the models on recorded footage from your cameras, day and night, and label what really happened.
- Measure two numbers. How many real events the system caught, and how many false alarms it raised per camera per day. You see both before deciding.
- Tune zones, times and thresholds. We draw detection zones, set schedules and adjust sensitivity per camera, and retrain the model on your scenes where needed.
- Let your team mark mistakes. Every alert has a "False alarm" button. Those marks are reviewed each month and used to retrain, so accuracy improves after go-live.
Works with the cameras and systems you already have
Cameras
Recorders and VMS
Access and attendance devices
IoT sensors
AI hardware
Where alerts and data go
Not on the list? If a device can share a video stream or send data over a network, we can usually connect it.
From recorded footage to alerts your team trusts
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Use case and site check
We agree what you need to detect or count, the decision it feeds and how success is measured, then review camera positions, light and network.
You get: a feasibility note and a go or no-go.
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Footage test
We run models on clips from your own cameras and measure detections and false alarms.
You get: a short report with sample snapshots and the two numbers.
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Build and integrate
We adapt the models to your scenes, set up the edge device, server or cloud, and connect alerts and records to your systems.
You get: a working system on your chosen cameras.
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Pilot on one site
Your team uses it for real, marks false alarms, and we tune it.
You get: a pilot report with accuracy after tuning and the rollout plan.
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Roll out and monitor
We add sites and cameras, watch accuracy each month and retrain when scenes change.
You get: monthly accuracy reports and support.
Not sure which problem to start with? Our AI consulting team ranks your use cases first.
We already connect devices, images and AI in live software
Our computer vision and device work builds on systems that businesses use every day.
Own product · Workforce software
Tainaat WorkforceOS
Our workforce software for security, facility and logistics firms connects ZKTeco biometric devices over ADMS and checks geofenced GPS check-ins, so attendance is tied to the right person at the right site.
See Tainaat
Client project · Document AI
DataSwitch (client project)
An AI document extraction platform we built for a client: it classifies uploaded PDFs and images and extracts their data into structured, checkable output.
Document AI
Own product · AI agents
Prilient AI Agents
Six AI agents (Receptionist, Customer Support, WhatsApp Lead Generation, Appointment Setter, Debt Collection and HR Interview Screening) that can act on an event, for example by sending a WhatsApp message or calling the site supervisor.
See Prilient AI AgentsComputer vision use cases we build most often
Security and facility services
Smarter guarding
Intrusion alerts at night, guard presence checks and face or biometric attendance at every site.
Smarter guarding with TainaatManufacturing
Inspection and safety
Defect detection on the line, PPE checks and danger-zone alerts near machines.
Retail and shopping centres
Footfall and queues
Count visitors, measure dwell time and queue length, and see which hours need more staff.
Warehouses and logistics
Gates and docks
Read plates at the gate, count vehicles and pallets, and log dock turnaround times.
Healthcare clinics and hospitals
Safer, smoother premises
Patient-area occupancy, fall alerts in restricted areas and staff attendance, without recording more than you need.
Safer, smoother premisesConstruction and field sites
Site safety and progress
PPE checks, after-hours intrusion and daily photo logs of progress.
Ways to start with computer vision
Footage test
For teams that want to know if their cameras can do the job. We run models on your recorded clips for one use case and report detections and false alarms.
Single-site pilot
For one use case on one site, end to end: models, hardware, alerts and a month of real use by your team.
Priced after a site check. Hardware quoted separately.
Rollout and run
For many sites and cameras, with monthly accuracy checks, retraining and new use cases added.
Length: monthly
Built for privacy from the first camera
- We sign an NDA before we see any footage
- Video can stay on your site: only events and snapshots leave it when the AI runs on the edge or your own server
- Face recognition is opt-in, with written consent and a card or PIN option for anyone who does not enrol
- We store face templates rather than photos wherever the system allows, and delete them when a person leaves
- Faces and number plates can be blurred in stored clips when the use case does not need them
- Retention periods are set with you, and old clips and events are deleted automatically
- We do not build emotion recognition for workplaces or schools, or identify people in public spaces
- Your footage is never used to train public AI models
Questions businesses ask about computer vision
What does a computer vision development company do?
A computer vision development company builds software that understands images and video: it detects people, vehicles, objects and defects, reads text and plates, counts, and recognises enrolled faces. We connect that to your existing cameras and business systems, so each event becomes an alert, a record or a report instead of hours of footage nobody watches.
Can you add AI video analytics to our existing CCTV cameras?
Usually, yes. Most IP cameras and NVRs can share a video stream over RTSP or ONVIF, and older analogue cameras can be connected through the recorder or an encoder. Before any build, we test the models on clips from your own cameras and tell you which views work, which need a different angle or more light, and whether a new camera is really needed.
How accurate is computer vision, and how do you handle false alarms?
Accuracy depends on the camera angle, light and what you want to detect, so we measure it rather than promise it. We label a sample of your footage, report how many real events the system catches and how many false alarms it raises per camera per day, and tune zones, thresholds and schedules until you agree the level is workable. Accuracy is then re-checked after go-live.
Does our video have to go to the cloud?
No. The models can run on a small edge device at the site, on a server in your own building or in the cloud. For most alerting, the video stays on site and only the event, a snapshot and the time leave it. We recommend the option that fits your bandwidth, privacy needs and number of cameras.
How much data do we need to start?
Less than most people expect. For common targets such as people, vehicles, helmets and vests, we start from pre-trained models and adapt them with a few hundred labelled frames from your cameras. For defect inspection, we need clear examples of good parts and of each defect type. The footage test tells you if what you have is enough.
How long does a computer vision project take, and what does it cost?
A footage test on one use case takes a few weeks. A pilot on one site takes longer, depending on the number of cameras, the hardware and the systems we connect to. We quote a fixed price for each stage before it starts, and hardware is quoted separately so you can see both costs.
Do you work with companies outside India?
Yes. Our engineering team is in Jaipur, India, and we work with businesses in the US, UK, Europe, the UAE, Australia and India. Workshops run on video calls in your time zone, footage tests use clips you share securely, and the finished system can run on hardware at your own site.
Find out what your cameras can already do
Send us a few minutes of footage from one camera and tell us what you want to catch or count. We will test it and tell you honestly whether computer vision can do the job.