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DateInvestorsAmountRound
-investor investor

€0.0

round
investor

€0.0

round
investor investor investor

€0.0

round
investor investor investor investor investor

€0.0

Valuation: €0.0

3125.0x EV/Revenue

-11.4x EV/EBITDA

round
*

N/A

Acquisition
Total Funding000k

Financials

Estimates*

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Revenues, earnings & profits over time
EUR2017201820192020202120222023
Revenues0000000000000000000000000000
% growth--4 %-45 %5 %-
EBITDA0000000000000000000000000000
% EBITDA margin-(14448 %)(26294 %)(27409 %)(26744 %)--
Profit0000000000000000000000000000
% profit margin-(13164 %)(21818 %)(24134 %)(24583 %)--
EV0000000000000000000000000000
EV / revenue00.0x00.0x00.0x00.0x00.0x00.0x00.0x
EV / EBITDA00.0x00.0x00.0x00.0x00.0x00.0x00.0x
R&D budget0000000000000000000000000000

Source: Company filings or news article, Dealroom estimates

Notes (0)
More about GrAI Matter Labs
Made with AI
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GrAI Matter Labs specializes in developing advanced edge AI processors designed for machine vision applications in sectors such as robotics, augmented reality, virtual reality, and drones. The company's flagship product, the GrAI VIP, is a sparsity-native AI System on Chip (SoC) that optimizes for ultra-low latency and low power consumption, enabling 'Life Ready' AI solutions. By integrating dynamic dataflow paradigms with sparse computing, GrAI Matter Labs significantly reduces application latency, achieving end-to-end latencies for deep learning networks like Resnet 50 to the order of a millisecond. The company operates in the edge AI market, targeting industries that require efficient and responsive AI processing capabilities. GrAI Matter Labs generates revenue through the sale of its AI processors and partnerships with companies like FRAMOS and ADLINK, which help integrate its technology into broader industrial and consumer applications. The business model focuses on providing cutting-edge AI solutions that enhance the performance and efficiency of devices across various sectors.

Keywords: edge AI, machine vision, robotics, AR/VR, drones, low latency, low power, sparsity, SoC, deep learning

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