Niricson Software

Niricson Software is a Canadian software company focused on digital condition assessment and risk management for large concrete civil assets, including hydro dams and spillways, bridges, airfield runways, tunnels and ports. Its core product, AUTOSPEX, is an AI-backed platform for defect detection, quantification and tracking that uses AI and data fusion to map and quantify damage such as cracks, spalling, delamination and alkali-aggregate reaction. The platform includes change-detection functionality — a comparison mode and change grid for comparing successive surveys, crack-growth tracking, visual documentation of repair effectiveness, and deterioration-rate analysis intended to support maintenance planning [0][4].

Data collection is handled through DRONIC, a patented multi-layered data collection and fusion architecture that pairs drones with a proprietary drone-mounted concrete sounding hammer. The NCX Mini is a UAV-mounted compact acoustic impactor that taps concrete surfaces at about 20 soundings per second to collect sounding data for delamination detection on walls, piers, retaining walls, bridge deck undersides, beams and tunnels; the resulting signals feed a machine learning model within AUTOSPEX that produces delamination maps. Reference deployments of the sensor include the King Street Bridge in Melbourne, the Rideau River Bridge in Ottawa, and the Ray Hall Viaduct at M6 Junction 9 in the UK [0]. Management has described the company as an analytics business rather than a drone business, with drones serving as the tool for collecting data in hard-to-access areas [5].

Users and partners named across the sources include Yuba Water Agency, South Feather Water & Power Agency, WaterNSW, Auckland Transport, the consultancy Beca, Saskatchewan's Water Security Agency, BC Hydro, Metro Vancouver and Arcadis [0][6][7]. Other cited projects include the Purewa Bridge in Auckland, Gardiner Dam in Saskatchewan, Cleveland Dam in British Columbia, and a runway inspection at Toronto Pearson International Airport [0][6].

Founding story

The company grew out of an idea developed by Harsh Rathod while he was pursuing a PhD in civil engineering at the University of Victoria, aimed at making bridges and dams safer to inspect. Rathod co-founded Niricson with Seattle-based Aki Tomita at the beginning of 2020 [5][6].

Business model

Niricson sells software-driven inspection and condition-assessment services to infrastructure asset owners, collecting field data with its own drone and acoustic hardware (DRONIC, NCX Mini) and delivering processed defect maps, quantification and reports through the AUTOSPEX platform. The company has stated it is developing an AI-driven predictive analytics Software-as-a-Service platform dedicated to managing critical infrastructure assets [0][4].

Revenue derives from digital condition surveys and platform-delivered defect analytics for asset owners, with stated R&D intent to build a predictive analytics SaaS offering for critical infrastructure asset management [4].

Traction

By late 2021 the company reported more than 25 employees, over $2 million raised, roughly 10-20 concurrent projects, and demand in Canada, the U.S. and Australia, with hiring of about three employees per month. In August 2023, at the time of its Series A, it stated it served more than 20 large customers owning dams, bridges, runways and other critical assets globally. Named deployments include BC Hydro, Metro Vancouver, Arcadis, Water Security Agency's Gardiner Dam pilot, WaterNSW, Auckland Transport's Purewa Bridge and a runway inspection at Toronto Pearson International Airport [4][5][6][7].

Latest developments

Following its August 2023 Series A, the company said it would expand its global footprint and accelerate R&D on an AI-driven predictive analytics SaaS platform for critical infrastructure. Its site lists AUTOSPEX change-detection capabilities and NCX Mini acoustic sensor deployments on bridges in Australia, Canada and the UK, with upcoming work noted on the Camo, Cowpasture and Meadowbank bridges in Sydney [0][4].