What is an Intelligent Application?
An intelligent application is one that is powered by analytics, and embeds analytical insights within the Human-in-the-Loop decision support workflow.
Why do we see a Rise in the demand for Intelligent Applications?
- Having relevant insights at the time of decision ensures that better decisions are made, faster, resulting in millions of dollars in cost savings and revenue growth opportunities.
- Most decisions are better made by analyzing large amount of historical data, and being able to forecast events based on multiple dimensions that are constantly in flux. The human mind simply cannot meaningfully process big data or forecast trends as accurately, efficiently, or reliably as a machine.
- Intelligent Apps maximize human ingenuity, enabling humans to focus on more creative and value add work, while delegating tedious and repetitive tasks to the machine.
How are Intelligent Applications Powering Digital Transformation Across Industries?
- Healthcare: Clinical diagnostic support tools, like neonatal pain monitoring solutions in NICUs that use computer vision algorithms to detect pain from streaming video and alert a nurse to take action.
- Transportation: Fleet repair scheduling and routing support tools that use optimization algorithms to determine which repairs to schedule at which shop based on labor, capacity, part availability, and cost constraints.
- Manufacturing: Factory asset preventative maintenance that run real time streaming reliability algorithms on data coming from IIoT sensors to prevent unplanned downtime and catastrophic incidents.
- Finance: Banking and credit fraud prevention that run anomaly detection algorithms on transactions to detect criminal activity and alert users to secure their accounts.
- Trading: Stock and crypto portfolio management that uses forecasting algorithms to predict price moments and place automated trades based on user defined risk appetite thresholds.
About the Author
Naomi Kaduwela is the Head of Kavi Labs and BD and Kavi Global. Naomi has a dual BS in Computer Science and Applied Psychology from Ithaca College, and a MS in Analytics from Northwestern University. She also holds a certificate of business management and sales. She has led analytics teams for over a decade, at GE, as well as cross industry during her time at Kavi Global supporting Healthcare & Pharma, Transportation, and Manufacturing clients. Naomi is also on the founding editorial board of Springer AI Ethics Journal, a published AI ethics author, and has had several of her R&D papers published in scientific journals. Naomi enjoys yoga and art.