Th The e Future uture of M of Min ineral eral Ex Explo - - PowerPoint PPT Presentation

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Th The e Future uture of M

• f Min

ineral eral Ex Explo ploration ration

Feb 2019

FOR ORWARD ARD LOOKING OOKING ST STATEME TEMENT NT

Certain statements in this presentation constitute forward looking information within the meaning of applicable securities laws. These statements relate to future events or Goldspot Discoveries Inc.’s (“Goldspot Discoveries” or “the Company”) future performance, business prospects or opportunities. Any statements that express or involve discussions with respect to predictions, expectations, beliefs, plans, projections, objectives, assumptions or future events

• r performance (often, but no always, using words or phrases such as “seek”, “anticipate”,

“plan”, “continue”, “estimate”, “expect”, “forecast”, “may”, “will”, “project”, “predict”, “potential”, “targeting”, “intend”, “could”, “might”, “should”, “believe”, “outlook” and similar expressions) are not statements of historical fact and may be forward looking information. Forward looking information in this presentation includes, but is not limited to, statements with respect to the Company’s future plans to acquire additional targets or properties including equity positions with partners, enter into joint venture, earn‐in, royalty or streaming structure agreements, or dispose of properties, achieve an income stream which would permit it to pay a dividend on its outstanding shares, the timing and amount of future exploration and expenditures and the possible results of such exploration. Forward looking information involves known and unknown risks, uncertainties and other factors which may cause the actual results, performance or achievements of the Company to be materially different from any future results, performance or achievements expressed or implied by the forward looking information. Such risks include, among others, the risk that the Company will not be successful in completing additional acquisitions, risks relating to the results of exploration activities and risks relating to the ability of the Company to enter into joint venture, earn‐in, royalty or streaming structure agreements, or dispose of properties, future prices of mineral resources; accidents, labor disputes and other risks of the mining industry including continued community and government support of the Company’s projects. The Company believes that the expectations reflected in such forward looking information are reasonable, but no assurance can be given that these expectations will prove to be correct and such forward‐looking information should not be unduly relied upon. These statements speak

• nly as of the date of this presentation. The Company does not intend, and does not assume

any obligation, to update any forward‐looking information except as required by law.

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Th They y ne need a n d a new way y to

• pl

play y th the min inin ing g sp spac ace. Investors don’t need an anothe

• ther

r exp xplo lora ration tion ga gambl ble... e...

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GoldSpot Discoveries is using machine learning as a very powerful extension of geological brainpower to unlo lock ck deep ep val alue ue in in expl xplorat

• ration

ion an and in investm estment ent dat ata. a.

ART ARTIFICIAL IFICIAL INT INTELLIGENCE. ELLIGENCE.

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From

• m incep

epti tion

• n throu
• ugh

gh to proof

• f-of
• f-co

conc ncept, t, GoldSpo dSpot has emerged erged as the e leader der in AI AI and machine hine learni rning ng in mining.

• ing. In

n tur urn, n, GoldSpo dSpot is able e to make e intelligent elligent invest stmen ent t deci cision ions, , acqui uire re roya yalti ties es on the e worl rld's d's best t ass ssets ts, , and d with h our ur team's m's technic chnical al prowess ess, , identi entify fy drill targe gets ts and optimi imize ze oper erat ations. ions.

• Par

Partne ners and clients ents include de Yamana ana, , Hoschchil chchild, , McEw Ewen, n, Sprott tt, , and d more re

• Team

m of 23 exper erts ts across ss Ea Earth h Scien ences ces and Data Scienc ences, s, including luding 9 PhDs in geology

• logy and data scienc

ence

• Utilize

zes s all kno nown wn data points ts to provi vide de minin ning compan panies ies with h the e very y best st targe gets ts

• Invest

estmen ent t in and d acqui uisiti tion

• n of roya

yalti ties es from

• m explor

lorat ation ion companies anies

• Developme

elopment nt of an AI AI-dri driven en indust stry y scree eenin ning g platform

• rm to det

etermine ermine ideal al partne ners s and invest stmen ent oppor

• rtu

tuni niti ties es

THE FUTURE OF MINING IS HERE

SKILL TO UNLOCK BIG DATA

GoldSpot’s domain expertise bridges ges the gap between geosc scien ience ce and artific ficial ial intelligen lligence ce by offering a front to back solution

Data Cleani ning ng & Digitiz gitizati tion Geochemis mistr try Inter erpreta pretati tion n & Mappi ping ng Geologica cal Modeling ng Structura ructural Geology Geology Geophysics ysics

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Deposits

• sits are becomi
• ming

ng more compl mplex x and harder er to find.

• d. Resou

esource ce compa pani nies es have e spent nt huge amounts unts of money in explor

• rat

ation

• n to collect

ect data. a. Peak k Disco cover ery spendin ding g has collect ected ed more data a at than ever befor

• re.

e. New data sources ces and techno nologi

• gical

cal advan ancemen cements ts have e resulted ed in enormous

• us

amoun unts ts of multi-varia ariant nt and compl mplex x raw data. a. Data a collecti ection

• n has signi

nifican cantl tly outpaced aced the capabil abilit ities es of tradit itiona

• nal geologists
• gists to fully

y underst stand nd and unlock ck all value ue hidden en in the data. a.

PEAK DISCOVERY & THE BIG DATA PROBLEM

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What t if a c com

• mputer

er could uld make e the e first st pass, , extr tracti cting ng corre relati tions

• ns and patterns

erns from

• m all this

s un underutilized derutilized data to predic dict t the e likel eliho hood

• d of finding

ding minera nerals ls? Machine ine Learning arning – a sub ubfiel ield d of data scien ence, ce, is one ne of many y tool

• ls

s to be us used d to provide ide an edge ge to explorer lorers, s, reducing cing time, e, costs ts and risk sks ass ssoc

• ciat

iated d with th explor lorati tion

• n.

Cloud d com

• mputing

ing allows ws easy y acces ess s to Sup uper er Comput puters s to run un compl plex x algorit rithm hms. s. AI AI is the e key y to un unlocki cking ng new w disco coveries eries in exist sting ng datas asets ts

DATA SCIENCE SOLUTION

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SKILL ILL TO O UNLOCK K BIG IG DATA

Bridging the gap between geoscience and data science.

VALID IDATI TING G TECHNO HNOLOG OGY WIT ITH H IN INDUSTR USTRY Y LEADERS ADERS

Working with motivated resource companies, with regional-scale exploration projects.

MONET NETIZ IZATI TION ON STRA RATE TEGY

Monetization through revenue services; investments, JVs, NSRs and Resource Quantamental.

SOLVING THE BIG DATA PROBLEM

Pr Private e and d confide dential 10 10

THE APPROACH

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THE SERVICES WORKFLOW

Data is cleansed, transformed, interpreted and then used to train machines in order to predict targets Targets are identified with high potential for mineralization Input Data

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VALIDATED TECHNOLOGY WITH INDUSTRY LEADERS

To date, GoldSpot is working with some of the mining industry’s most respected leaders to identify new targets and develop new technology and techniques. Our service partners are now some of our most supportive shareholders.

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CLIENT TESTIMONIALS

" We are very excited to be partners with GoldSpot, their approach to exploration using leading edge technology has not only allowed us to validate targets, but has provided us with fresh ideas and new concepts. GoldSpot is helping us to embrace new technologies.“

• Ramón

ón Barúa rúa, , CFO of Hochsc schild ild Min ining ing . “GoldSpot has produced a very high- quality 3D geological model of the Jerritt Canyon district which provides an excellent foundation for continued

• exploration. We look forward to drilling

the priority targets derived by GoldSpot through their detailed assessment (AI techniques) of the data. The management of Jerritt Canyon Gold looks forward to future collaboration with GoldSpot in the continued exploration and development of the Jerritt Canyon district”

• Jamie

ie Lavign gne, , VP Expl xplor

• rati

tion

• n of Sprott

Min ining ing "As the first AI company in mining, GoldSpot combines powerful machine learning and traditional geology to unlock deep value in exploration data. Our project in Idaho, DeLamar, is rich in history and data and we’re excited to be working with GoldSpot Discoveries to leverage the most innovative approach to exploration targeting the mining sector has seen.”

• George

ge Salam lamis is, , Pres esid iden ent, , CEO EO and Direct ector, Integra egra Res Resour urce ces

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MONETIZATION STRATEGY

REVENUE ENUE-GE GENERA RATI TING G SER ERVICES CES IN INVEST ESTME MENTS, S, JOI OINT T VENTU TURES RES & RO ROYAL ALTI TIES ES RESO SOUR URCE CE QU QUAN ANTAME AMENTAL AL

Examples mples

• Hochsch

schild d Mini ning ng

• McEwen

n Mini ning ng

• Sprott
• tt Mini

ning ng

• Yamana Gold

Case Study dy in Juni nior

• r X
• Invest

st in Juni nior r X t through ugh pri rivat vate placemen ent

• Esta

tablish sh a s servi vice e arrangem ngement ent to levera rage our team & techno hnology

• Receive

e a r roya yalty ty incent ntive

• Deliver

r targets ets and make a disco scover ery Case Study dy RQ

• AI

AI-driv riven en opportuni tunity generat ator r point nts s us to ideal eal comp mpani nies es to work rk with th

• Further

ther asse sess ss data to va validat date partne tnership hip opportuni tunity ty

• Leads to partner

tnersh ships ps, invest estments, ents, roya yalti ties

We Us e Use a e a Qu Quant ant-Ap Appr proach

• ach to M
• Mak

ake e In Investme estments nts

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RESOURCE QUANTAMENTAL

RQ combines the best of technology, people, data, and AI to identify long-term growth through partnerships, investments, and royalties. RQ uses the most robust and comprehensive database ever created in the resource business, taking over two years to assemble. When combined with machine learning, Goldspot will be able to identify the best projects and teams to work with worldwide, resulting in alpha generating investments and royalties. In addition, RQ can be leveraged in many different ways.

Geological Data Market Data Management Macroeconomic Data Company-Specific Data

THE E SMART ARTES EST MONEY EY

SH SHORT ORT TO O MI MID-TERM TERM CA CATAL ALYST STS

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Resource Qua uantam ntamen enta tal l (RQ)

Mining’s first AI-driven opportunity generator predicts which companies are most likely to be successful

New w Par Partner nersh ships ips

Collaborations open doors to new markets, new data types and deep value monetization

• pportunities

Net et Smelt elter er Royalti lties es / Inves estme tments nts

RQ highlights opportunities where Goldspot can shorten path to discovery. We assist technically and financially in exchange for royalties and equity

Revenue enue-Gen Generati ting ng Servi vice ce Agre greeme ement nts s

Obtain additional cash flow to finance R&D and sustainable growth

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LONG ONG-TERM ERM VI VISION: ION:

Mor

• re

e data.

• a. Smar

arter er machi hine nes.

We continuously evolve our machine learning algorithms to improve our outcomes.

Walk the Talk.

We invest in companies to drill our targets

Next Gene nera ratio tion n Technol hnology gy.

We constantly explore the latest mining technologies to generate more data and stay one step ahead of the curve.

INNOVATION

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Why? y? We are re a techn hnology logy company, not

• t a m

mining ing company. .

Our aim is to use data to further de-risk, lower costs and increase rates of discovery. We deliver value through data discovery.

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CAPIT CAPITAL S AL STRUCTUR TRUCTURE E (F (FEB EB 2019) 19)

Hoch chsch child ild Mining ning 7% 7% Insid iders (Escrowe crowed) 5% 5% Rob McEwen wen 1% 1% U.S. . Global

• bal

8% 8% Other er 22% 22% Palisa isade e Global

• bal (Escrowe

crowed) 14% 14% Mana nagem gement ent & Employee loyees 13% 13% ThreeD eeD Capit ital l (Escro crowed wed) 12% 12% Eric c Sprot

• tt

10% 10% Tripl ple e Flag g Mining ning 8% 8%

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SU SUMM MMAR ARY

RESO SOUR URCE CE QUANT NTAME AMENT NTAL AL

A quantitative and fundamental approach to identify high-value

• pportunities in data-rich

companies.

EX EXPL PLOR ORE E LES ESS.

• S. FIND

IND MO MORE. E. DEE EEP P VALUE E FROM OM DISCO SCOVER VERY. .

VALID IDATE TE

Combine geoscience and data science knowledge to assess opportunity.

COLLAB ABOR ORATE TE

Negotiate partnership terms: service agreement, direct investment, NSR, or joint venture agreement.

DIS ISCOVER VER

Apply machine learning to data to reduce exploration risks, costs and time and increase rate of discovery.

OUR TEAM

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Unlocking the value of discovery through A.I.