Entity
  • PeerNova Inc

    Created in 2013
  • BETA

    Up & running (A)
    Existing signals show a regular activity
  • Social networks

    17,299 2,577
  • Activities

  • Technologies

  • Entity types

  • Location

    2055 Gateway Pl, San Jose, CA 95110, USA

    San Jose

    United States of America

  • Employees

    Scale: 51-200

    Estimated: 46

  • Engaged corporates

    8
    0 2
  • Added in Motherbase

    4 years, 10 months ago
Description
  • Value proposition

    PeerNova’s mission is to empower firms to make confident and timely decisions using high-quality data.

    PeerNova’s mission is to empower organizations to make confident and timely decisions using high-quality data and insights. Today, firms struggle with confident decision-making because they are unsure if their underlying data is fit for purpose. Poor or untimely decisions can lead to missed opportunities, client dissatisfaction, regulatory fines, and reduced profitability. Cuneiform® is a zero-code, decision-science platform that enables business users to monitor their data-quality metrics, evaluate whether data is fit for business purposes, identify and resolve high-impact exceptions, perform faster root-cause analysis, and ensure continuous data reliability through monitoring and trend analytics. Cuneiform is used for valuation risk (financial industry), data quality monitoring, Customer Relations Management (CRM), and Data Cloud. Founded by entrepreneurs with deep expertise in data and analytics, PeerNova is a Silicon Valley technology company with sales offices in New York and London. For more information, please visit https://peernova.com.

    Big data, Financial Services, FinTech, Data Governance, Active Data Governance, Business Performance Management, Data Quality, Digital Transformation, Silicon Valley, Enterprises Data, Data Management, Regulatory Compliance, and End-to-End Visibility

  • PeerNova - Decision Science: Confident Decisions Using Contextual Insights

    Important decisions are made without knowing whether the underlying data is fit for purpose. So, we asked, why rely on data that’s probably right?

  • https://peernova.com/
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