Tech start-up behind $1tn of construction projects backed by GV

Posted on March 24, 2021 by Jonathan Symcox

nPlan

A start-up using data and AI analytics to mitigate risk on construction projects has raised £13.5 million. 

nPlan has already forecast the duration, risks and opportunities of nearly $1 trillion worth of global construction projects, spotting delays and recommending improvements by analysing the plans and actual outcomes of past projects. 

It has been backed by GV, formerly known as Google Ventures. 

Project delays and overspends are common in construction – one study estimates that for every billion dollars spent on projects, $127 million is wasted.  

In the UK, Network Rail is one of the leading investors of large-scale infrastructure projects. It recently worked with nPlan on some of its largest rail projects – including the Great Western Main Line and the Salisbury to Exeter Signalling projects – representing more than £3 billion of capital expenditure.  

By flagging unknown risks, nPlan’s platform identified cost savings of up to £30 million on the Great Western project alone. 

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In addition, the nPlan platform is constantly learning. As well as drawing on external market historical data, it uses intelligence from current projects on the platform, including HS2 and Shell, to educate and update its algorithms.  

As well as GV, investors in the round include LocalGlobe, Pentech, Entrepreneur First and former McKinsey & Company managing director Sir Ian Davis. With nPlan already operating in eight countries for nearly 30 customers, covering commercial, infrastructure, transportation and energy construction projects, the investment will be used to scale its algorithm-led assurance platform and launch a new category of insurance, to cover against the damaging losses of project overruns. 

CEO Dev Amratia and CTO Alan Mosca co-founded nPlan in 2017. Amratia, a former project manager with Shell, most recently led the national review on AI for the UK Government, and currently sits on the Expert Panel for the Department for Transport’s Acceleration Unit.  

Mosca conducted his doctoral research on Deep Learning Theory at the University of London, whilst working full time in Quantitative Finance at Wadhwani Asset Management and Jane Street Capital; his previous experience also includes High Performance Computing software on some of the largest systems in the world, and he has lectured at the University of London.

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Amratia said: “At a time of ongoing uncertainty, our goal is to provide confidence in a sector notorious for struggling to stick to deadlines or budgets.  

By using some of the most powerful machine learning capabilities in the world to analyse what worked and what didn’t in past projects, we can help our customers work out what’s going to derail their own initiatives, and stop problems happening before they even appear.” 

Tom Hulme, General Partner at GV, added: “Through due diligence, we spoke to a range of customers and prospects, ranging from infrastructure owners like Network Rail or the largest tech companies to contractors such as SNC Lavalin.  

In all cases, we were blown away that those responsible saw the benefit of applying modern machine learning techniques to such a difficult analogue problem. 

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“Enabling more efficient build in infrastructure is a multi-billion dollar opportunity, increasing by the day as governments drive investment post-pandemic.  

We couldn’t be more excited to see nPlan empower its customers to visualise and manage the project planning process, assess budgets, timeliness, and risk in an entirely novel way.” 

nPlan has raised $22.3m since its launch in 2017. 

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