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Eugenie.ai

eugenie.ai

成立一年

2018

階段

Unattributed |活著

總了

$ 50 k

最後提出了

$ 50 k | 10 MOS前

馬賽克的分數
馬賽克評分是一種衡量私營公司整體財務健康狀況和市場潛力的算法。

過去30天累計漲90點

關於Eugenie.ai

Eugenie.aioffers an operational intelligence platform to reduce production wastage, avoid unscheduled downtimes, and build sustainable operations. The company was founded in 2018 and is based in New York, New York.

總部的位置

1號世界貿易中心76J套房

紐約,紐約,10007年,

美國

Eugenie.ai產品視頻

Eugenie.ai?

確保您的公司和產品在我們的平台上得到準確的展示。

Eugenie.ai的產品和差異化

    Ray-Finn

    從傳感器和SCADA係統中攝取大量數據。

專家集合包含Eugenie.ai

專家收藏是由分析師策劃的列表,突出了你在最重要的技術領域需要了解的公司。

Eugenie.aiis included in2專家收藏,包括石油與天然氣技術

O

石油與天然氣技術

657件

這些公司包括石油和天然氣行業的上遊、中遊和下遊部門,以及專注於可持續燃料的公司。行業是由公司的總體關注點標記的(即使該技術適用於各個行業)。

一個

先進製造

2284件

公司專注於提高製造業生產力的技術,從自動化和機器人到AR/VR到工廠分析和人工智能等等。

最新的Eugenie.ai新聞

氣候與碳——尤金妮婭。人工智能正在幫助從源頭上減少碳排放

2023年1月27日

2023年1月27日22:01 +08可持續商業實踐的必要性,特別是在工業部門,已不再公開辯論。用聯合國的話說,氣候變化是我們這個時代的決定性問題。要扭轉已經造成的破壞,需要工業企業加大可持續發展的努力,而美國近30%的溫室氣體排放來自這些企業。業內領導者目前麵臨的問題是,如何在不影響盈利能力的情況下變得更加可持續。Eugenie.ai, a global leader in helping heavy industries to reduce their carbon footprint, has the answer to that question. "The best approach for reducing carbon emissions is reducing them at the source," says Dr. Soudip Roy Chowdhury, Founder, and CEO of Eugenie.ai. "Other options, such as carbon sequestration or shifting to renewable energy sources, suffer from systemic issues; they have high costs and questionable impacts. By adopting an approach that reduces emissions at the source, organizations can make a measurable difference without affecting their economic goals." Eugenie.ai's technology solutions have been used by companies around the world to improve sustainability by tracing emissions to specific assets and process-level performance. Its unique approach of combining spatiotemporal emission data from satellite and other LiDAR (light detection and ranging) data sources with SCADA (Supervisory control and data acquisition) and IoT(the Internet of things) data from machines and processes allow it to track, trace, and optimize processes that are the root-cause for anomalies in the emission patterns. Gathering and analyzing data in this way enables Eugenie.ai to deliver real-time actionable insights to operation personnel for reducing emissions by optimizing systems and processes. "In many industrial plants, outdated machines and asset management tools create a digital divide between physical asset management and digital strategy," Dr. Roy Chowdhury explains. "Eugenie.ai's patented explainable AI and augmented analytics (combining knowledge of physics of the system with data and AI) framework fixes this problem. Our approach is generalizable across machines and industries irrespective of where they are in their digital transformation journey. Combining physics with AI makes our insights humanly interpretable, understood, and actionable - unique whitespace that is overlooked by the enterprise AI software community today." Eugenie addresses another sensitive yet pertinent problem of a largely used existing carbon reduction technique; carbon offsetting. According to a few recent studies, including those done by PNAS and Source Material, it is found that only 6% of the overall voluntary carbon emission purchased from the marketplaces were useful for real carbon emission reduction. This kind of offsetting approach also encourages carbon leakage malpractice. Carbon leakage occurs when sustainability controls shift unsustainable practices from one region to another where controls are less strict. Such practices encourage purchasing voluntary carbon credits from re-deforestation projects across the globe. This approach does not solve the problem of carbon emission reduction at the source. Unlike these, Eugenie reduces the emission at the source (Scope 1) for heavy emitters using AI for process optimization. Reducing emissions at source is a more reliable and sustainable practice than electrification. With electrification, which involves using electric equipment rather than conventional equipment for industrial processes, emissions are only significantly reduced if the electricity is sourced from a green energy grid. Unfortunately, that is not the case today. "Reducing carbon emissions at the source goes beyond sustainability to empower organizations to capture new business models," explains Dr. Roy Chowdhury. "For example, green steel sells at a 50 percent premium when compared with conventional steel. Reducing emissions at the source is the most promising way of converting the existing steel manufacturing process to a green process line. The increasing demand for green commodities in society is acting like a catalyst for industries to feel the pressure to reduce their emissions faster and more efficiently. After all, it is the green commodity channel that promises to improve the business while improving the world." Join the Discussion Dr. Steven Kaufman said Zeus Companies operates a real estate financing... Richardson, 23, claimed that the flight attendant, whom she refers to as... Aldrin has been married and divorced three times earlier to Joan Ann... ISIS fanatic, who romanticized Islamic jihad, planned to carry out a... The act was live streamed through the dashcam of Greek racer Jourdan...

Eugenie.ai常見問題

  • 歐也妮是什麼時候。ai成立嗎?

    Eugenie.aiwas founded in 2018.

  • 歐也妮呢?艾未未的總部嗎?

    Eugenie.ai's headquarters is located at 1 World Trade Center, New York.

  • 歐也妮是什麼?艾未未的最新一輪融資?

    Eugenie.ai's latest funding round is Unattributed.

  • 歐仁妮有多少。人工智能提高?

    Eugenie.airaised a total of $50K.

  • 誰是歐也妮。艾未未的競爭者?

    歐仁尼的競爭者。ai包括Senseye和1更多。

  • Eugenie的產品是什麼?人工智能的報價嗎?

    Eugenie.ai's products include Ray-Finn and 1 more.

比較Eugenie。ai對競爭對手

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SparkCognition標誌
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元素分析

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Petasense標誌
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Veros係統標誌
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Veros Systems為客戶提供整個企業工業資產可靠性和能源使用的連續、非侵入性、可擴展、預測性監控。Veros產品的核心是預測智能平台(PIP),該平台可以從電壓和電流波形數據中分析300多個離散可靠性和能效指標,然後將這些數據轉換為工程師、工廠主管和企業高管可執行的情報。終端用戶可以通過電子郵件或短信收到警報,警告他們在未來某個時候可能導致災難性故障的電氣或機械故障。為了更深入地挖掘,最終用戶可以轉向PIP的基於web的界麵,或與領先的企業資產管理套件集成。

吸收的標誌
吸收

Uptake是一家預測分析軟件提供商,為采礦、鐵路、能源、航空、零售和建築行業的客戶收集和解釋傳感器數據。Uptake集成了跨行業的專業知識、數據科學和工作流連接,以構建基於海量數據集的高價值解決方案,在問題發生之前發現問題,並提高安全性、效率和生產力。

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