Sound-plus-camera checks that cut false alarms for remote security desks
TL;DR Twinproof is an edge box and software layer for India's remote e-surveillance desks. It listens for break-in sounds, checks them against camera video and passes only confirmed events to an operator. Monitoring firms pay per site, because fewer false alarms means each operator can cover more ATMs, branches and stores.
Alarms that cry wolf waste everyone's time. The clearest data comes from US gunshot sensors - in Chicago, 89% of over 40,000 police deployments from these alerts found no gun crime[1], and in New York only 13% of 940 alerts in one month were confirmed shootings[2].
India's version of this problem sits in central monitoring rooms. Banks have watched ATMs remotely since at least 2014, with hooters, two-way speakers and police alerts when the system flags activity[3]. Large providers now claim tens of thousands of live sites[4]. Every false trigger, whether it's a cleaner, a stray dog or a passing truck, eats operator attention, and no Indian provider publishes its false-alarm rate.
What it does, in regulatory terms: alert triage that supports a human operator. Twinproof does not call police on its own, identify people or make any decision about them.
A small box at each site connects to the existing cameras and adds a microphone. It listens for a narrow set of sounds that matter in Indian bank and store break-ins - metal cutting, drilling, glass breaking, shutter forcing and shouting. When it hears one, it checks the matching camera feed for a person in the protected zone at that moment. Only when both agree does the operator get a ten-second clip with audio. Single-signal events are logged for review but not pushed.
The seed wanted to fuse audio and video to stop false gunshot alerts. India has little street gunfire to detect, and the US evidence above shows how hard that market is. So we kept the core idea of two signals checking each other and pointed it at an alarm-monitoring industry India already pays for.
The buyer is the e-surveillance company that runs the monitoring desk on contract for banks, jewellers and retail chains. Its operators use Twinproof, and its margins improve if each operator can watch more sites. A per-site monthly fee works, priced below the cost of the operator time it saves. I couldn't find a public figure for Indian per-site monitoring fees, so pricing has to come from interviews.
Video analytics vendors have reached Indian banks at scale - one cash-logistics firm's AI product lists large public and private banks as customers and claims 43% fewer manual reviews[4]. Audio is the missing second signal. CCTV equipment has needed BIS registration since 2018[5], so standard hardware is easier to source, and the DPDP Rules notified in 2025 spell out what consent and retention notices must cover.
Nobody publishes a figure for India's alarm-verification market. The narrower proof points are one provider claiming over 50,000 live monitored sites[4], and bank e-surveillance contracts running since at least 2014[3]. Treat both as signs of a large installed base, not as market size.
That product layers vision AI onto existing cameras for banks and retail[4]. An Indian video-AI startup sells a product that adds analytics to existing CCTV[6]. Neither describes audio-and-video cross-checking. Abroad, gunshot-detection firms show what happens when you sell alerts with weak confirmation[1]. The gap is an add-on existing monitoring firms can deploy, not a rival service.
| Difficulty | Hard (54/100) |
| Starting capital | ₹1.6–3.2 Cr |
| Time to launch | 9–12 months |
The sound models need recordings of real Indian break-in noises against street noise, and collecting those takes time. The edge hardware has to survive heat, dust and power cuts. Selling to a few large monitoring firms also hands those buyers a lot of bargaining power.
Yes, the hardware needs approvals before you sell it, and the data rules apply from the first site.
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
Don't let AI call the police or identify anyone. Twinproof only triages alerts, and a human operator makes every decision.
Want to work out the AI layer for Twinproof? Talk to Yash →
I think this is a credible B2B idea for a team with audio machine-learning and edge hardware skills, plus a door into one monitoring firm. If you're hoping to sell to police or cities then it's a poor fit. First prove on 50 live sites that operator alerts fall by half with no missed real incidents.
My estimate is ₹1.6–3.2 Cr, covering hardware design, BIS and radio approvals, audio models and pilots with a monitoring firm. The kit breaks it down.
Yes. CCTV equipment falls under BIS compulsory registration, radio modules need WPC approval and the DPDP Act covers the audio and video.
Yes, remote monitoring is an established industry abroad. Check your local product safety, radio and privacy rules, and how police treat verified alarms.
The free Twinproof validation kit has the line-by-line capital breakdown, the effort scoring, the hardware and data-protection checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for monitoring firms and their clients, and 5 assumptions to test. Download the kit →
Thinking about building Twinproof or something close to it? The make-or-break work is proving fewer alerts with zero missed incidents on a monitoring firm's live sites, and I can help you plan that pilot and the raise around it. If you need a hand, you know where to find me. Talk to Yash →
For illustration only. Names are fictional and ideas hypothetical; sourced facts are real but may be out of date. Nothing here is legal, financial or professional advice, and Yash Khatri is not personally liable for any use of it. Read the full disclaimer.