HomeHIVE Secures $15M to Develop Physical AI for Industrial Machines
HIVE upgrades existing customer machinery with sensors and a silicon-based control system. | Source: HIVE
HIVE announced today the closing of a $15 million pre-Series A funding round. The London-headquartered physical AI startup stated its mission is to create the intelligence layer for industrial machinery.
According to HIVE, it is developing a silicon brain that consolidates machine operations via a single intelligence platform. The company modifies existing vehicles to allow them to perceive, decide, and act autonomously. This technology can be applied to vehicles operating in warehouses, production facilities, construction sites, and other environments.
“We have spent the last few months recruiting top international talent to support our next growth phase,” said Christoffer Jørgensvaag, co-founder and CEO of HIVE. “The silicon brain is taking shape. With live deployments and strong market traction, we are well positioned to lead the next era of physical AI, delivering tangible results for our customers.”
Silicon brain in active operation
HIVE maintains offices in Norway and London, with U.S. expansion currently underway. The company has already deployed its technology across multiple sites in Scandinavia, enabling autonomous operation across various machine types.
For instance, at Vikafjellet, one of Norway’s most exposed mountain passes, clearing an avalanche typically required waiting hours for a geologist to approve the zone before crews could enter. With HIVE’s silicon brain installed, Presis Vegdrift can now dispatch a wheel loader immediately.
HIVE retrofitted a standard wheel loader with its advanced sensor and camera technology, effectively transforming it into a remote-supervised machine powered by the Hive Silicon Brain. Instead of operating from a vulnerable cab, the operator now controls the wheel loader from a safe, remote supervisor room.
HIVE aims to expand leadership and scale deployments
SuperSeed led HIVE’s investment round, with participation from Veriten, Skyfall, and Nysnø. Angel investors included Børge Hald, founder of Medallia, and Jørn Lyseggen, founder of Meltwater.
With this funding, HIVE plans to accelerate platform development, expand its founding team, and further scale commercial deployments with both new and existing industrial partners. The commercial model is designed to compound: each deployed machine hour feeds a large reinforcement loop across the machinery fleet. The startup projects that this learning loop will reduce productive machine-hour costs by 80%.
“SuperSeed backs the rare founders who can identify a category before it exists and possess the technical depth to build it,” said Mads Jensen, managing partner at Superseed. “HIVE’s silicon brain is powerful enough to retrofit existing industrial fleets, and the intelligence compounds in value with every hour it runs. This represents the defining wave of physical AI for the next decade.”
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工場機械にセンサーとAI制御を追加するHIVEの1500万ドル調達、実用化が楽しみだ。物理AIは製造業に革命をもたらす可能性があり、既存設備のアップグレードというアプローチはコスト効率も良さそう。倫理やセキュリティの懸念はあるものの、技術革新には期待大🤖✨
HIVE upgrades existing customer machinery with sensors and a silicon-based control system. | Source: HIVE
HIVE announced today the closing of a $15 million pre-Series A funding round. The London-headquartered physical AI startup stated its mission is to create the intelligence layer for industrial machinery.
According to HIVE, it is developing a silicon brain that consolidates machine operations via a single intelligence platform. The company modifies existing vehicles to allow them to perceive, decide, and act autonomously. This technology can be applied to vehicles operating in warehouses, production facilities, construction sites, and other environments.
“We have spent the last few months recruiting top international talent to support our next growth phase,” said Christoffer Jørgensvaag, co-founder and CEO of HIVE. “The silicon brain is taking shape. With live deployments and strong market traction, we are well positioned to lead the next era of physical AI, delivering tangible results for our customers.”
Silicon brain in active operation
HIVE maintains offices in Norway and London, with U.S. expansion currently underway. The company has already deployed its technology across multiple sites in Scandinavia, enabling autonomous operation across various machine types.
For instance, at Vikafjellet, one of Norway’s most exposed mountain passes, clearing an avalanche typically required waiting hours for a geologist to approve the zone before crews could enter. With HIVE’s silicon brain installed, Presis Vegdrift can now dispatch a wheel loader immediately.
HIVE retrofitted a standard wheel loader with its advanced sensor and camera technology, effectively transforming it into a remote-supervised machine powered by the Hive Silicon Brain. Instead of operating from a vulnerable cab, the operator now controls the wheel loader from a safe, remote supervisor room.
HIVE aims to expand leadership and scale deployments
SuperSeed led HIVE’s investment round, with participation from Veriten, Skyfall, and Nysnø. Angel investors included Børge Hald, founder of Medallia, and Jørn Lyseggen, founder of Meltwater.
With this funding, HIVE plans to accelerate platform development, expand its founding team, and further scale commercial deployments with both new and existing industrial partners. The commercial model is designed to compound: each deployed machine hour feeds a large reinforcement loop across the machinery fleet. The startup projects that this learning loop will reduce productive machine-hour costs by 80%.
“SuperSeed backs the rare founders who can identify a category before it exists and possess the technical depth to build it,” said Mads Jensen, managing partner at Superseed. “HIVE’s silicon brain is powerful enough to retrofit existing industrial fleets, and the intelligence compounds in value with every hour it runs. This represents the defining wave of physical AI for the next decade.”
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工場機械にセンサーとAI制御を追加するHIVEの1500万ドル調達、実用化が楽しみだ。物理AIは製造業に革命をもたらす可能性があり、既存設備のアップグレードというアプローチはコスト効率も良さそう。倫理やセキュリティの懸念はあるものの、技術革新には期待大🤖✨
