Qualitas (QAL) investor relations material

Strategic rationale and structural AI opportunity

• AI is viewed as a transformational opportunity to drive efficiency and scalability in investment processes, leveraging a proprietary platform tailored to the firm's needs.

• The business model, with repeatable, data-intensive processes, is highly suited to AI augmentation, enabling faster, deeper analysis while maintaining rigorous human judgment.

• Over 90% of staff have adopted AI tools, reflecting strong internal engagement and a shift from increasing headcount to leveraging AI for productivity.

• AI is designed to make 18 years of underwriting knowledge accessible, improving consistency and speed in risk assessment.

• Management anticipates AI-driven efficiency will allow more investments without proportional increases in staff.

AI platform architecture, workflow, and initiatives

• The proprietary AI platform leverages large language models, machine learning, and 18 years of institutional knowledge, including 400+ investment committee papers.

• The system processes 160+ documents per investment, extracting 400 data points, running 370+ verifications, and conducting 260 analysis steps per deal.

• 33 specialized AI agents handle discrete risk assessment tasks, ensuring traceability and transparency throughout the workflow.

• Each investment involves evaluating at least 160 documents and addressing over 1,900 risk assessment questions.

• The platform is tailored for flexible, deal-specific analysis and supports continuous learning from every transaction.

Human oversight and reliability

• AI augments but does not replace human judgment; all analysis is transparent and traceable, with multiple AI agents double- and triple-checking data points for accuracy and context.

• Human oversight remains central, with AI providing audit trails and supporting, not replacing, investment judgment.

• The system is optimized for reliability and transparency, allowing investment teams to build conviction in decisions.