About Us

A Few Words About Numerica

NUMERICA is a technology company with more than 25 years of experience providing solutions to several industrial and educative sectors. Since the very beginning, we have faced and solved big challenging problems in the Oil & Gas, defense, mining, and transportation industries.

Our company was founded in 1995 as a local services provider in the Oil&Gas industry, focusing on innovative developments and long-term customer relationships

Today we have projects in more than 10 countries as leaders in M2M communications solutions in key sectors such as Oil&Gas and Utilities.

Our History

  • 1995

    This year, Numérica was established by our founders.

  • 1997

    Our first great project nationwide. This project required great innovation and the implementation of scientific computing algorithms in geophysics.

  • 2000

    Some of our members traveled to various countries to pursue postgraduate studies in areas of interest to the company. Communications networks, computer science, applied math, petroleum engineering, and geophysics were our target areas.

  • 2004

    Until this year, the company was focused on geophysical services. Starting in 2004, Numerica begins to develop and promote production-oriented services.

  • 2010

    The first version of WellMonitor is developed and put it in service for ALS systems.

  • 2011

    WellMonitor expands and has a presence in several national territories.

  • 2015

    Until 2015, we offered satellite communications services through business partners. This year we integrate our own communications service, which allows us to offer better rates to our clients.

  • 2018

    Numérica, along with its service WellMonitor, begins operations outside the country, through service companies in the Oil and Gas sector.

  • 2019

    International expansion, this year we increased our operation to 6 countries.

  • 2022

    A new release of the WellMonitor web platform is released. The new dashboard-based version includes special applications for ESP analysis and optimization, and machine learning tools for ESP operational events detection.