Cartier Unveils VRIFY-Generated AI Model Highlighting Key Discovery Targets Ahead of Largest-Ever Drill Program at Cadillac
TSXV: ECR | FSE: 6CA
ressourcescartier.com
Cartier Unveils VRIFY-Generated AI Model Highlighting Key Discovery Targets
Ahead of Largest-Ever Drill Program at Cadillac
Val-d’Or, Quebec, July 10, 2025 – Cartier Resources Inc. (″ Cartier ″ or the ″ Company ″) (TSXV: ECR;
FSE:6CA) is pleased to present its new predictive model for the Cadillac Project in the heart of the Val -d’Or
mining camp, Quebec, created with Artificial Intelligence ( ″AI″) using VRIFY’s AI -Assisted Mineral Discovery
Platform, DORA. With robust geoscientific information from across the 14,000 -ha Cadillac Property, the
Company was able to unlock value from this data by leveraging VRIFY’s proprietary algorithms and feature
processing to generate a VRIFY Prospectivity Score (VPS) over the entire land package. The VPS is a probabilistic
value, helping Cartier’s team prioritize and guide a portion of the Company’s upcoming 100,000-m drill program
using an approach backed by data-driven insights.
For an interactive view of Cartier’s 3D model showcasing the AI results, please use the link below:
https://vrify.com/decks/18798
Philippe Cloutier, President & CEO, stated: ″ We are very impressed by the results generated from DORA,
VRIFY’s AI -Assisted Mineral Discovery Platform. These results reveal potential extensions of known
mineralization laterally and at depth, and more significantly, map out new subsurface zones of high
prospectivity. We’re particularly excited by the discovery of multiple areas that showed high prospective scores
where little to no drilling or modern exploration efforts exist. ″ Adding, ″ We will drill these areas and have
planned contingency drilling to follow up on successes. ″
″ Cartier’s recent results are highly encouraging, particularly within the context of a mature, historically
productive mining camp where multiple high-potential zones remain untested, ″ noted Steve de Jong, CEO and
Co-Founder, VRIFY. ″ These outcomes highlight the strength of leveraging artificial intelligence as an
exploration tool, demonstrating how AI -assisted analysis of geoscientific datasets can systematically identify
targets that were previously overlooked by conventional methods . ″
Data Compilation and Feature Processing
The Company and VRIFY have collaborated to undertake extensive data aggregation and synthesis, leveraging
sophisticated AI techniques to extract meaningful insights from a wide range of proprietary and publicly
available datasets, including:
➢ Over 158,000 drill hole assays from ~ 544,000 m of drilling contained in ~ 4,500 holes;
➢ Surficial geochemistry including rocks, soils, glacial till, bark, and stream and lake sediments totalling
over 8,500 individual assays;
➢ Over 15,000 individual structural data points from regional and local bedrock mapping and down hole
measurements;
TSXV: ECR | FSE: 6CA
ressourcescartier.com
➢ Regional geophysics including magnetics, EM, and gravity providing continuous coverage over the
entire Cadillac Property;
➢ Several local high-resolution geophysical surveys including IP, ground and helicopter magnetics, and
VLF data.
Using VRIFY’s proprietary Feature Processing, a total of 148 additional geoscientific products were created and
leveraged to enhance the predictive modelling at Cadillac (Figure 1). These products have been instrumental
in providing additional geoscientifi c insights and have proven to hold considerable predictive power for target
generation.
Figure 1. Data stack representing the raw regional and proprietary data sets at the Cadillac Property (left -hand side) and
fully integrated data stack after VRIFY’s Feature Processing (right-hand side).
TSXV: ECR | FSE: 6CA
ressourcescartier.com
The Predictive Model and Target Generation
Through the use of DORA, the Company was able to run multiple experiments incorporating different data sets,
metal thresholds, and AI parameters resulting in a fine -tuned predictive model over the entire land package.
Due to the robust nature of Cartier’s data set, DORA was also able to project VPS results at depth, revealing
potential extensions of known mineralization and also mapping out new subsurface zones of high prospectivity.
This resulted in the recognition of multiple areas that showed high VPS scores where there was previously little
to no drilling or modern exploration efforts (Figures 2 and 3).
Figure 2. Cadillac AI model overview identifying target areas.
For each of the targets generated, VRIFY provided Cartier with a Feature Importance Table explaining the
relative weight of influence each geoscientific input had on the prospectivity model for that area. This has
allowed the Company’s technical team to ga in unbiased insights into the predictive power of its data sets and
incorporate these insights into strategic decision making to inform their upcoming exploration campaign.
TSXV: ECR | FSE: 6CA
ressourcescartier.com
Figure 3. Feature Importance Table, Example Omicron Target.
The Largest Ever Drill Program on Cadillac Property
Cartier is now fully funded for the largest -ever drill program on the Cadillac Property consisting of 100,000 -m
planned over the next 18 months. The drill program is set to begin late August 2025 and will include
approximately 600 drill holes supported by two rigs focused on expanding known gold zones and testing new
high-priority grassroots targets. Approximately 25% of the 100,000m is going to be dedicated to exploring
targets generated by DORA, VRIFY’s AI -Assisted Mineral Discovery Platform, alongside ot her litho -structural
targets.
AI-Driven Exploration and Real-Time Insight
DORA, VRIFY’s AI -Assisted Mineral Discovery Platform, uses a combination of proprietary algorithms and
datasets, that include a wide variety of exploration features, to train predictive models. This platform leverages
complex data relationships to predict mineral exploration targets, streamlining the process of identifying viable
mineral systems that can then be further validated by geoscientists. The automation of target generation also
allows trained models to be updated quickly with new data from ongoing exploration, as well as VRIFY’s growing
database, creating an iterative workflow to improve accuracy and results.
For more information, visit VRIFY.com.
TSXV: ECR | FSE: 6CA
ressourcescartier.com
Qualified Person
The scientific and technical content of this press release has been prepared, reviewed and approved by
Mr. Ronan Déroff, P.Geo., M.Sc., Vice President Exploration, who is a ″Qualified Person″ as defined by National
Instrument 43-101 – Standards of Disclosure for Mineral Projects (″NI 43-101″).
About Cartier Resources Inc.
Cartier Resources Inc. was founded in 2006 and is an advanced gold project exploration company based in
Val-d’Or (Quebec, Canada). In 2024, Quebec ranked 5th among the best mining jurisdictions in the world
(Fraser Institute). Cartier owns 100% of its f lagship Cadillac asset and controls a significant land package of
25,000 ha. The Cadillac project is located approximately 40 km east of Val-d’Or and close to existing gold mills
with available capacity.
The results of the recent Preliminary Economic Assessment 1 (PEA) demonstrate the economic viability of the
project with an average annual gold production of 116,900 oz over a 9.7 -year mine life. The current Mineral
Resource Estimate 1 (MRE) totaling 7,128,000 tonnes at an average grade of 3.14 g/t Au for a total of 720,000
ounces of gold in the Indicated category and 18,475,000 tonnes at an average grade of 2.75 g/t Au for a total
of 1,633,000 ounces of gold in the Inferred category.
1. NI 43-101 Technical Report and Preliminary Economic Assessment for Chimo Mine and West Nordeau Gold Deposits,
Chimo Mine and East Cadillac Properties, Quebec, Canada, Marc R. Beauvais, P.Eng., of InnovExplo Inc., Mr. Florent Baril
of Bumigeme and Mr. Eric Sellars, P.Eng. of Responsible Mining Solutions, May, 29, 2023.
- 30 –
For further information, contact:
Philippe Cloutier, P. Geo.
President and CEO
Telephone: 819-856-0512
www.ressourcescartier.com
Neither the TSX Venture Exchange nor its regulatory services provider accepts responsibility for the adequacy or accuracy
of this press release.