Every project here shipped. Measured. Handed over. No vapourware, no slides.
Retail and semi-professional traders lacked an all-in-one discipline system for position sizing, risk management, trade planning, and journaling. Existing tools focused on signal generation but ignored the execution and psychology side of trading.
A regional healthcare system in a developing market lacked reliable case forecasting to plan ICU capacity, oxygen supply, and public-health interventions. Off-the-shelf global models did not generalise to local epidemiological data.
Clinicians in a Nordic public health system needed rapid access to rehabilitation guidelines, clinical protocols, and best practices scattered across hundreds of unstructured documents. Manual search was slow, inconsistent, and pulled staff away from patient care.
State-of-the-art emotion recognition models were too large and power-hungry for on-device mobile deployment. Running inference in the cloud introduced latency, privacy concerns, and dependency on connectivity.
Voluntary carbon markets cannot scale if every project claim and emission sheet requires manual review. Policy-aligned verification checks need to run in parallel across multiple data sources without overwhelming human analysts.
E-commerce and growth teams managed multiple KPIs (revenue, CLV, churn, product mix) without a unified interactive platform for cohort filtering and time-range analysis. Spreadsheets could not handle real-time dashboard requirements.
Users cannot safely paste long PDFs into generic LLMs. Enterprise knowledge bases require grounded answers with source citations, and knowledge must update when documents change without retraining entire models.
NYC trip duration is driven by time-of-day, origin-destination patterns, and city-scale congestion. Simple time averages mis-price ETAs in operational routing systems, leading to customer dissatisfaction and driver inefficiency.