nPlan
Machine learning to improve construction projects
- 21-100 employees
- B2B
- Artificial Intelligence
- Construction
- Machine Learning
- Data Analysis
- Spitalfields, London, UK
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Company mission
nPlan's vision is that all construction projects should be built on time and budget, enabling the cities of the future to be built better.
Our take
nPlan is leading the drive to improve decision-making in construction by applying machine learning to dramatically improve how information is retained and utilised to influence risk and uncertainty.
It noticed the construction industry has remained static for decades and projects are consistently not delivered on time or budget. With intelligent software, nPlan has started to change the fundamentals of the industry and improve the outcome for all stakeholders.
Having already worked with some of the biggest construction and infrastructure companies in the world, including Network Rail and Google, the company completed its Series A at the start of 2021 with GV as its lead investor.
Freddie
Company Specialist at Welcome to the Jungle
Benefits
- Flexible working hours - core hours of 11-3pm, besides that we're to be flexible
- Work-from-home opportunities
- Unlimited paid time off policy - yes it's really unlimited!
- Share options for all employees
- Fitness allowance - £50/month to expense on any fitness activity
- Flexible work locations - work from our office, home, or abroad, as long as there's wifi we're not too fussed!
- Learning budget: £1000/year to spend on conferences, books, courses and subscriptions
- Visa Sponsorship and contribution towards relocation costs (role dependant)
- EAP & eye tests
- Season ticket loan
- Health insurance - Private Medical Insurance with Vitality
Funding (last 2 of 4 rounds)
Nov 2020
$18.5m
SERIES A
Jan 2020
$0.6m
GRANT
Total funding: $23.2m
This company has top investors
Leadership
Dev Amratia
(CEO)Previously worked at Shell for 9 years before authoring the UK's National AI Strategy.
Alan Mosca
(CTO)Spent 7 years as a technologist in quantitative finance and is completing a PhD in deep learning.