Tignis's target audience comprises large industrial enterprises and organizations operating in asset-heavy sectors. Specifically, these are industries where the continuous and reliable operation of machinery, equipment, and infrastructure is critical to their business model and profitability. This includes, but is not limited to, manufacturing (e.g., discrete manufacturing, process manufacturing), energy (oil & gas, power generation, renewables), utilities (water, electricity), mining, and potentially transportation. Within these industries, Tignis is targeting companies that are undergoing digital transformation initiatives, looking to modernize their operations, and seeking to extract greater value from their operational data. They are likely companies that are already generating significant amounts of sensor data, but struggling to turn that raw data into actionable intelligence. The sweet spot for Tignis would be companies that recognize the limitations of traditional rule-based or reactive maintenance approaches and are open to adopting advanced AI/ML solutions for predictive maintenance, anomaly detection, and operational optimization. They are likely to be companies with complex operational environments, high capital expenditure in assets, and a significant cost associated with downtime or inefficiencies.