Here’s why Alphabet VC arm backed UK machine-learning startup nPlan with £13.5M
London-based nPlan is a revolutionary system, which utilises machine learning and AI analytics to predict outcomes of construction projects and mitigate risk. In a recent development, the company pocketed $18.5 million (nearly £13.5 million) in a funding round.
Funding from Alphabet’s VC arm
The investment round was led by US-based GV (formerly Google Ventures), which is a venture arm of Alphabet, Google’s parent company. The other investors that took part in the round are Local Globe, Pentech, Entrepreneur First and former McKinsey & Company managing director Sir Ian Davis. With this round, the total funding bagged by nPlan is $22.3 million (nearly £16 million).
Already, nPlan operates in eight countries with nearly 30 customers spanning across commercial, infrastructure, transportation and energy construction projects. The company will deploy the investment will be used to scale its algorithm-led assurance platform. Also, it will launch a new category of insurance that will cover the damaging losses of project overruns.
CEO Dev Amratia co-founder of nPlan 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.”
“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,” said Tom Hulme, General Partner at GV. “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.”
AI to tackle issues in construction industry
Established in 2017 by Dev Amratia and Alan Mosca, nPlan uses its proprietary AI algorithms to tackle issues such as delays and overspends in the construction industry. The company uses machine learning to analyse the plans and actual outcomes of past projects to give customers accurate forecasts on project timelines and potential delays and opportunities. Its solutions will be vital as the industry becomes flush with investment and the security and success of projects are paramount.
To date, nPlan has analysed nearly $1 trillion worth of global construction projects and deploys this learning to spot delays and recommend improvements with an accuracy and scale that wasn’t available previously. Doing so, its data-led insights effectively reduce the volatility and increase investor confidence in construction projects.
In the UK, Network Rail is one of the leading investors of large-scale infrastructure projects. Recently, Network Rail and nPlan joined hands to work on some of the largest rail projects including the Great Western Main Line and the Salisbury to Exeter Signalling. By eradicating unknown risks, nPlan’s platform helped save up to £30 million on the Great Western project.
Alastair Forbes, Network Rail’s programme director (affordability) said, “By championing innovation and using forward-thinking technologies, we can deliver efficiencies in the way we plan and carry out rail upgrade and maintenance projects. It also has the benefit of reducing the risk of project overruns, which means in turn we can improve reliability for passengers.”
Besides cost-cutting and mitigating risk, nPlan is constantly learning. It uses intelligence from current projects on the platform including HS2 and Shell in order to educate and update its algorithms.