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AI digital twin for industrial sites: French deeptech Samp raises €6M to scale up Shared Reality platform

Samp funding
Picture credits: Samp

French deeptech startup Samp, which has developed a first-of-its-kind AI-generated digital twin solution to accelerate the transformation and decarbonisation of industrial sites, has raised €6 million in funding. The investment came from Promus Ventures, which backed Recycleye and The Exploration Company, and Kvanted, which backed Buddywise and Cozero

Funds utilisation 

The investment will allow the company to scale up and deploy its innovative “Shared Reality” solution internationally. It will help Samp meet the growing demand by developing the sales team in France and Europe; continue R&D to stay at the forefront of AI and 3D developments; and prepare for international expansion outside Europe.

The round was led by Promus Ventures, a US venture capital firm focused on deep tech investments that is also present in Europe. “We are excited to partner with the team at Samp and support their mission to become the operating system of Industry 4.0. By combining artificial intelligence with technical documentation and 3D data, Samp’s Shared Reality platform significantly enhances operators’ operational efficiency and accuracy, particularly in the water and energy sectors. We look forward to supporting them in this next growth phase,” said Jeremy Teboul, Vice President at Promus Ventures.

Story behind the company 

Samp was founded in 2019 in France by Shivani Shah (ex-CEA) and Laurent Bourgouin (ex-Dassault Systèmes), who met at STATION F, a big startup campus. Laurent, with 15 years in the Water & Energy industry, witnessed how outdated systems slowed industrial growth. Shivani, freshly graduated from her PhD at the French Nuclear Research Agency (CEA), had advanced AI tech. Together, they realised AI could solve these issues by creating smart 3D models of industrial sites. Now, their solution is used across Europe.

Its mission is to help industrial sites adapt to the growing imperatives of sustainability, safety, and staff shortages. The company is revolutionising the management and maintenance of sensitive industrial infrastructures by creating the fastest and most pragmatic digital twins on the market.

Shared Reality platform 

The startup has been developing a patented AI and 3D streaming technology to generate digital twins and optimise the management of existing industrial infrastructures. By integrating image captures from industrial sites, these digital twins offer a global and precise 3D vision of the state of infrastructures, allowing teams and stakeholders to make informed decisions before any inspection, maintenance, or modification. 

Samp’s technology allows for fast and constant 3D modelling and contextualising of the technical data (diagrams, plans, characteristics) of the equipment to be maintained or repaired. Its Shared Reality platform enables constant asset monitoring, thereby reducing risks and improving the safety and operational efficiency of inspection, maintenance, and construction sites. The solution reconciles 3D scans of sites with technical documentation (schematics, inventories, drawings) that is often incomplete and rarely up to date.

“Our ‘Shared Reality’ solution accelerates and improves the reliability of these sites’ transition towards sustainable production. Our ambition is to become the key solution allowing industrial players to face today’s colossal challenges in terms of security, resilience, and the environment,” declares Laurent Bourgouin, CEO of Samp.

Customer base 

Present in over 150 industrial sites in France, Samp has demonstrated its maturity and aims to become the reference method for faster, simpler, and safer monitoring of industrial assets. The company solves the challenges of obsolete documentation and knowledge loss, incompatible with the urgent needs for industrial site modernisation. 

Industry leaders like Engie, SUEZ, VEOLIA, Teréga (strategic natural gas storage), Trapil, and SFDM (oil pipeline networks) have already implemented Samp’s solutions. 

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