Visual quality inspection
Defect, dimension and label checks on production lines, with reject signals to your line controls.
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Vision AI & Video Analytics
Cameras capture far more than anyone can watch. We build computer vision systems that detect defects, count and track objects, read number plates and text, and verify faces for attendance and access, running on existing CCTV or edge devices.
What this covers
Typical timeline
Proof of concept in 3–4 weeks; production rollout typically 6–12 weeks.
Who it is for
We design vision systems for real conditions: dust, poor lighting, varied angles and limited bandwidth. Privacy is built in, with consent-based enrolment for facial recognition, on-premise processing options and retention limits aligned with the DPDP Act.
Discuss your requirementManufacturers needing automated visual quality checks
Companies wanting face-based attendance for field and site staff
Retailers and warehouses counting people, vehicles or goods
Security teams monitoring restricted zones and safety compliance
Capabilities
Defect, dimension and label checks on production lines, with reject signals to your line controls.
Face-based attendance with liveness checks and geo-fencing, synced to HRMS and payroll.
People, vehicle and inventory counting, queue monitoring and occupancy analytics.
Helmet, vest and restricted-area alerts from existing CCTV feeds.
Number plates, meter readings, labels and serial numbers read from images and video.
Models optimised to run on-site on edge devices when bandwidth or privacy requires it.
How we work
You always know what happens next, who is responsible and what you will receive at each stage.
Typical timeline
Proof of concept in 3–4 weeks; production rollout typically 6–12 weeks.
Cameras, lighting, angles and target events are assessed.
Images are gathered and labelled for your specific conditions.
Detection and recognition models are trained and validated.
The system runs on selected cameras with accuracy tracking.
Deployment scales across sites with monitoring dashboards.
Deliverables
Technology & standards
We recommend tools based on your scale, budget and existing systems, not on what is fashionable. Every choice is explained in the proposal.
Engagement models
A 3–4 week pilot on your own data with agreed accuracy targets, so you see real results before scaling.
Hardened integration, guardrails, monitoring and admin controls, delivered in milestones with a fixed quote.
Ongoing prompt and model tuning, evaluation runs, cost monitoring and feature additions on a monthly plan.
How pricing works: AI projects are priced in two stages: a fixed-price proof of concept, then a production quote based on what the pilot proves. Model and API usage costs are estimated upfront and billed at actuals.
Get a quoteFAQs
In most cases, yes, if they provide an RTSP stream and enough resolution for the task. We assess camera positions and may recommend repositioning or a few additional cameras.
With good enrolment photos and liveness checks, accuracy is high in normal conditions. We add fallbacks such as OTP or supervisor approval for edge cases and test at your sites before rollout.
Use it with informed consent for a clear purpose such as attendance. We collect consent at enrolment, store face templates securely, restrict access and delete data when employees leave, in line with the DPDP Act.
No. Processing can run on edge devices or an on-premise server, sending only events and summaries to the cloud.
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