Goldspot Discoveries Inc.

account_balanceMining

  About Us
GoldSpot is a technology company that leverages artificial intelligence to reduce capital risk while working to increase efficiencies and success rates in resource exploration and investment. GoldSpot combines proprietary technology with traditional domain expertise, offering a front-to-back service solution to its partners. GoldSpot's solutions target big-data problems, making full use of historically un-utilized data to better comprehend resource property potential.
Website

https://goldspot.ca/

https://goldspot.ca/

Headquarters

69 Yonge Street, Suite 1010 Toronto, Ontario M5E 1K3

Public Issuance

2017

Shares Outstanding

94.54m

Corporate Filings

SEDAR

Stock Symbol

SPOT

location_on69 Yonge Street, Suite 1010 Toronto, Ontario M5E 1K3
 3 Reasons to invest
  1. QUANTITATIVE analysis refers to the financial analysis that looks to predict the behavior of stocks through the use of mathematical modelling and research. Quantitative analysis generally uses large computer systems, complex machine learning algorithms and large amounts of current and historical data to predict future stocks prices by looking at historically recurring patterns that look similar to current ones.

  2. QUANTAMENTAL analysis is the loose combination of quantitative and fundamental investment strategies.

  3. FUNDAMENTAL analysis refers to the analysis a stock by attempting to calculate its intrinsic value, done so by examining economic, financial and other qualitative and quantitative factors.

    Fundamental investors study anything that can affect a stock’s value, typically using a bottom-up approach. This includes, company-specific data, management, sector conditions, and the overall economy.

    The end goal of fundamental analysis is to calculate a value that can be compared to a stock’s current price indicating whether it is undervalued or overvalued.

    GolSspot Discoveries advantage centers around utilizing geologic-specific data as one of its data sources. One such layer is all the drill data produced and released by companies as assays become available.

    An algorithm immediately relates the depth, length and grade, with hundreds of other variables, including directorships, the ability to raise funds, insider buying, market data, and all financial data.

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 Current Team
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Data


Geological data is valuable. Companies spend hundreds of millions of dollars drilling, sampling, surveying, and creating geological models… but only a fraction of the data collected is utilized.

GoldSpot Discoveries bridges the gap between big data and geoscience. This starts with cleaning, analyzing, and refining a data set, and then extracting all useful information into a queryable database.

Moreover, data can often be contaminated by noise (or signals from other sources); instruments can exhibit small changes that cause random data error; or other variability due to changes in the environment and/or the operator (e.g. sampling methods).


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Geophysics

Applied geophysics consists of various methods that measure the physical properties of the Earth’s subsurface.

Techniques employed often measure the direct response (passive) or an induced response (active) of the ground physical properties. This leads to the ability to assess the underlying geological structure.

Geophysical modelling and inversion are indispensable tools for finding mineral deposit for greenfield or brownfield exploration.

Since most geophysical techniques used in exploration can penetrate through the overburden and sound at great depth, a 2D and 3D reconstruction of the spatial distribution of the ground physical properties (density, resistivity, magnetic susceptibility, etc.) can be produced through the process of modelling or inversion.
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Geochemical

Geochemical data acquisition and proper interpretation is fundamental in order to identify areas of hydrothermal alteration associated with high mineral potential.

Interpretation of geochemical surveys is critical in any exploration campaign, including highlighting geochemical fingerprints associated with different commodities in various types of deposits.

Geochemical surveys allow for the acquisition of several types of geochemical dataset: DDH and channels assays, lithogeochemical data, soils, streams and lake sediments samples.

GoldSpot’s targeting process aims to extract all the highly valuable data hidden in large databases.
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3D Modelling

Our modelling experts use all the geological information (data) available (e.g. diamond drill holes, surface mapping, etc.) to visually and accurately represent the geometry of each unique geological setting.

Our geological model comprises stratigraphy, structures, alterations, mineralization and more to integrate into a common Earth Model.

These various features represented and considered during our interpretation play a fundamental role in guiding us toward the discovery of new mineral deposits.

At GoldSpot Discoveries, regional or deposit geological modelling is always preceded by field work observations, homogenization of a database, and a brainstorming discussion with experienced geologists in order to build a robust and consistent geological model.
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Machine Learning

Data sets are often so large and complex that conventional processing applications are ineffective in dealing with them.

Machine learning investigates the creation of algorithms that can learn from and make predictions from big data. This allows companies to overcome strictly static program instructions and gives computers the ability to learn without being explicitly programmed.

These analytical models allow users to produce reliable, repeatable decisions and uncover “hidden insights” through learning from historical relationships and trends in the data. Mineral deposits form for a reason. Machine learning is used to link this “reason” to available geoscience data to determine the relationship:
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