Terzonova is the AI safety guard that never blinks. Connected to the cameras your site already has, it watches every worker and machine at once, sees a collision or fall forming 3 to 5 seconds before impact, and vibrates the wristband of the person in danger - fast enough to step back. The accident never happens. The paperwork writes itself. Every worker goes home.
Katherine Holtz, P.E., spent 25 years at the Texas Department of Transportation directing contract management for a $25 billion highway and bridge program. She has seen what preventable accidents cost in lives, schedules and lawsuits. Hear her case for why prevention - not paperwork - is the future of construction safety.
The deadliest industry in Canada still runs on line of sight. One year of official AWCBC data shows a plateau the reactive safety model cannot break - supervisors watching, workers reacting, paperwork after the fact. Read the full analysis →
Terzonova ingests live video from standard RTSP site cameras into a ruggedized on-site edge computer and produces two simultaneous outputs: real-time alarms that prevent accidents, and compliance analytics that document how many incidents were prevented - rather than how many caused injury.
Your existing RTSP cameras stream every risk zone on site.
On-site nodes project every trajectory 3–5 seconds ahead.
A haptic pulse lands on the workers involved in <0.5 s.
Every event is signed into an audit-ready compliance log.
Human perception needs 1.5 to 2 seconds to register an unexpected threat. Cloud video analytics adds a 2–5 second network round trip on top. Terzonova’s full loop - camera frame, wireframe inference, risk classification, wrist vibration - completes before a person can even turn their head.
Stage 5 - cryptographic signing and compliance mapping - runs in parallel, so documentation never delays the warning. Walk through all five stages →
This site is written for the people who will actually interrogate the claim - safety directors, CFOs, IT leads, union reps, underwriters and investors. Every number traces back to the business plan and its sources.
183 deaths and 39,131 lost-time injuries in one year. Why line-of-sight supervision has structurally plateaued, the physics of a struck-by, and the cost cascade a single incident triggers - from a $2M fine to a $10M+ shutdown.
Read the analysis →
Five engineered advantages - sub-second speed, trajectory prediction, wireframe privacy, self-writing compliance, offline resilience - and the competitive matrix against cloud CV, wearable-only and manual-software alternatives.
Explore the platform →
The five-stage pipeline against a hard latency budget, the full sequence diagram, the dual-loop architecture, and two hazard scenarios traced frame by frame from detection to signed record.
Follow the pipeline →
Redundant TPM 2.0 edge nodes in NEMA 4X cabinets, 104-camera PoE networks with QoS discipline, BLE haptic wristbands, bandwidth planning from 16 to 240 cameras, and the five-phase deployment sequence.
Inspect the hardware →
EdgeOS’s four modules on the critical path, the AVX-512 wireframe engine trained on 120,000 incidents, the Analytical Compliance Engine, the event-only sync protocol and six layers of security architecture.
Tour the software →
Cash-flow positive from site one: the $15,800 setup fee against ~$6,400 cost, $3,951 MRR, transparent pricing formulas, the five-year path to $7.5M revenue and $2.5M EBITDA, and every risk addressed directly.
See the business model →Canada’s construction sector employs over 1.6 million workers and contributes about $164.5 billion to GDP. Our entry market is roughly 2,500 high-risk sites. Terzonova ships bilingual (EN/FR) with a rules-agnostic engine that switches provincial compliance modules - Ontario Mode, BC Mode, Quebec Mode - with a single configuration change.
The launch market. Dense GTA high-rise activity, major transit programs, and a $2M-per-count fine cap that makes automated compliance urgent. Falls from height are the #1 killer here - the direct target of our fall-prediction algorithms.
The strictest enforcement in North America, with 2026 administrative penalties up to $816,148.69. Remote interior projects with poor connectivity are exactly where offline-capable edge processing beats every cloud-dependent competitor.
Industrial, energy and heavy civil work where struck-by incidents involving heavy machinery dominate - a one-to-one match for vehicle–worker trajectory forecasting.
Heavy civil infrastructure investment, full French localization, and a privacy architecture designed for Law 25 - a structural advantage over video-recording competitors.
We publish our progress the way our platform reports safety: factually. Terzonova is a pre-revenue Canadian startup executing a build–validate–scale plan, and this is exactly where we stand on it.
Dual-pipeline architecture designed and documented: edge inference, wireframe processing, trajectory prediction, haptic alerting and the 147-duty Ontario compliance mapping. Five-founder team assembled with infrastructure, engineering, finance and governance depth.
Patent applications in preparation for the wireframe detection method, the wearable alert pipeline and the constrained-bandwidth alarming architecture. Canadian trademark filings under way; compliance matrix being mapped for WorkSafeBC, Alberta OHS and CNESST.
A Senior Software Developer and an Electronic Engineer onboard in Ontario at funding. Edge node, camera pipeline and wristband firmware integrated, localized for English and French, and stress-tested against Canadian site conditions - snow glare, dust, −30°C - before the first commercial deployment.
Eight high-risk pilot sites across Ontario and British Columbia, each with a one-week shadow-mode calibration, a dedicated Success Engineer, and insurer-grade reporting from day one. Revenue begins in Month 7.
Expansion to Alberta and Quebec through insurance-broker channels and owner mandates, growing to 150 active sites monitoring more than 1,800 workers by Year 5 - then the U.S. market on the strength of the validated Canadian model.
Find answers to common questions about Terzonova’s predictive safety platform, its benefits, and the technology underneath it.
Terzonova is a business-to-business safety platform for construction sites. It combines on-site cameras, an edge AI computer, vibrating worker wristbands and a compliance dashboard. The system detects high-risk events as they develop, warns the people involved in under half a second, and automatically documents every event for regulators, auditors and insurers.
No. Video is analyzed on the site itself and converted into anonymous wireframe figures. The raw footage is discarded immediately. Nothing identifiable is stored or sent to the cloud, and there is no facial recognition. What remains is structured event data - for example, “a worker entered Zone B at 14:32 and was alerted.”
Usually not. Terzonova ingests standard RTSP video streams - the protocol most modern IP cameras already use. The platform layers intelligence on top of existing camera infrastructure, and we supply additional cameras only where coverage gaps exist.
A standard 104-camera deployment takes four to seven days of installation and commissioning, handled by our engineers. New sites then run for a week in silent “shadow mode” while the system learns that site’s rhythm - so the first alert a worker ever feels is a genuine hazard.
We are selecting Canadian general contractors, project owners and insurance brokers for our first pilot deployments in Ontario and British Columbia. Eight pilot slots. Here is what founding partners get.
First allocation of edge kits and wristbands, founding-partner terms locked for the full contract, and a pre-defined path from pilot to fleet rollout.
Our engineers run the install, the shadow-mode calibration and the first 30 days. Your crew gets protection, not an IT project.
Pilot partners shape the prevention metrics that insurers will underwrite against, and own the earliest documented safety record in the industry.
Whether you are a contractor exploring a pilot, an owner setting safety standards, a broker looking for risk-engineering data, or an investor who wants to learn more - our team is ready to assist with your specific needs.
