Mr. Mike Marrandino reports

GOLD HUNTER RESOURCES AWARDS DRILLING AND INFRASTRUCTURE CONTRACT TO MCL DRILLING OF DEER LAKE, NEWFOUNDLAND

Inverite Insights Inc. has discussed continued growth for the quarter ended March 31, 2026. Growth was driven by increasing adoption of the company's real-time financial data platform, AI-driven risk modeling, bank verification and fraud-prevention solutions across Canadian financial ecosystems, including lending and financial institution workflows.

Highlights

• Financial activity data points surpassed 38.9 billion, growing by approximately one billion per month during Q1 2026;
• Platform requests increased 30 per cent, from 690,051 in Q1 2025 to 897,141 in Q1 2026;
• Risk intelligence successful requests grew more than 71 per cent from 14,423 to 24,611 in Q1 2026, reflecting increasing adoption of Inverite's AI-driven intelligence layer;
• Inverite signals identified approximately 40 per cent of total defaults within the riskiest 15 per cent of loans;
• Production deployment demonstrated 41-per-cent lower default rates by loan count and 39-per-cent lower defaults by dollar amount.

During Q1 2026, Inverite continued scaling its proprietary risk intelligence infrastructure, processing significant increases in transaction activity and longitudinal financial signal volume across the Canadian financial services industry.

Infrastructure metrics

• Financial activity data points: 38.9 billion (3.2-plus billion quarter over quarter (Q/Q));
• Unique consumers connected: 7.67 million (7.2 plus per cent in Q/Q);
• Platform requests: 897,000 (30.0 plus per cent YoY).

The company also observed accelerating adoption of its risk intelligence layer during the quarter, with risk intelligence requests growing more than 71 per cent in Q1 2026.

Management believes this growth reflects deeper integration of Inverite's AI-driven intelligence into customer decisioning workflows. As more financial activity flows through the platform, the company's behavioural data network expands, creating a richer longitudinal view of consumer financial behaviour and enabling the continuous refinement of predictive intelligence models through real-world usage.

AI and machine learning models operating across the platform continuously compute and refine predictive intelligence as new behavioural and repayment data is incorporated into the system. Management believes this creates a compounding advantage, as the predictive capabilities of the platform improve alongside growing transaction volume and customer adoption.

"What we are building is a risk intelligence infrastructure that improves with scale," said Karim Nanji, chief executive officer of Inverite Insights. "Every transaction processed, every consumer connection and every repayment outcome contributes to a growing body of behavioural intelligence. The scale of Inverite's behavioural data network, which now exceeds 39 billion financial activity data points and continues to grow by more than one billion additional data points per month, provides a strong foundation for increasingly sophisticated risk intelligence."

Inverite believes the expanding scale, longitudinal depth and real-world activity flowing through the platform are beginning to translate into measurable improvements in predictive intelligence across financial risk workflows.

Management believes these results support the growing role of real-time transaction-derived signals as a foundational layer in modern credit decisioning infrastructure.

Inverite believes the market opportunity for real-time risk intelligence is continuing to evolve beyond standalone point-in-time financial analysis toward embedded risk-model-as-a-service (RMaaS) intelligence infrastructure operating continuously across financial ecosystems.

About Inverite Insights Inc.

Inverite Insights is a Canadian risk intelligence infrastructure company specializing in real-time financial data and AI-driven intelligence. The company's platform helps financial ecosystem participants better understand financial activity, risk behaviour and real-time financial patterns through permissioned financial data infrastructure.

We seek Safe Harbor.