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HEAVY.AI Stock (HEAI)

Accelerated Analytics Platform

HEAVY.AI is an accelerated analytics company. The HEAVY.AI platform is used in business and government to find insights in data beyond the limits of mainstream analytics tools. HEAVY.AI uses GPU processors to speed up analytics and aims to perform tasks with near-zero latency. HEAVY.AI originated from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). HEAVY.AI is headquartered in San Francisco, California. HEAVY.AI is backed by investors including by GV, NVIDIA, Tiger Global Management, and Verizon Ventures.

About HEAVY.AI Stock

Founded

2013

Headquarters

San Francisco, CA, US

Total Funding

133M

Industries

Software, Data and Analytics

HEAVY.AI (formerly known as OmniSci) is a software company that claims to use graphics processing units (GPUs) and central processing units to analyze big data. The HEAVY.AI platform is used in business and government to find data insights beyond the limits of mainstream analytics tools. HEAVY.AI uses GPU processors to accelerate analytics and aims to perform tasks with minimal latency. HEAVY.AI originated from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).

HEAVY.AI was founded in 2013 and is headquartered in San Francisco, California. HEAVY.AI is backed by investors including GV, NVIDIA, Tiger Global Management, and Verizon Ventures.

Investors in HEAVY.AI

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HEAVY.AI Management

Leadership team at HEAVY.AI

Chief Executive Officer

Jon Kondo

Chief Technology Officer

Todd Mostak

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HEAVY.AI Key Facts

Heavy.ai targets industries such as construction, mining, agriculture, and logistics, where heavy machinery plays a critical role. These industries are increasingly adopting AI and automation to improve productivity, reduce operational costs, and enhance safety standards.
• They have extensive domain knowledge. Deep understanding of the complexities and requirements of heavy machinery operations allows Heavy.ai to develop tailored AI solutions that effectively address industry-specific challenges.
• Heavy.ai showcases success stories where their solutions have led to significant improvements in operational efficiency, reduced downtime, and increased safety for their clients.

• Disruption in supply chain partnerships for sensor components used in Heavy.ai's AI-driven machinery monitoring systems could affect product delivery timelines and customer satisfaction.
• The adoption of AI technologies in heavy machinery operations is contingent upon industry readiness, regulatory approvals, and integration challenges. Delays or resistance to technological adoption within target industries could impede Heavy.ai's growth prospects and revenue generation.
• Heavy.ai's financial performance may be susceptible to economic downturns, fluctuations in industrial spending, and the cyclical nature of capital investments in heavy machinery.

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