By way of the 2024 Smart Office Systems Assessment report done by Gartner, organizations employing Notes AI achieve a mean 214% year-to-year return on investment for knowledge management effectiveness. After Morgan Stanley’s wealth management business as an example, using the Notes AI voice semantic recognition engine (on 16 industry lexicon databases), customer meeting minute generation time was reduced from an average of 127 minutes to be processed manually to 9 minutes, accuracy of key decision point extraction was 92.3%, and historical case lookup efficiency was 4.8 times higher using the intelligent label system. This technology innovation facilitated 68% faster response times for financial advisor clients, having a direct effect on a $320 million quarterly AUM (assets under management) increase. In the medical field, after Notes AI’s electronic medical record support system was applied at Johns Hopkins Hospital, the doctors’ writing time of medical progress notes dropped from 86 minutes to 23 minutes per day, and by adopting the ICD-11 code automatic matching function, the rate of health insurance application approval reached from 78.4% to 97.1%, which saved the annual non-payment loss of $1.2 million. The related accomplishments ranked by JAMA (Journal of the American Medical Association) in 2023 as the first ten medical AI innovation cases include:
In smart upgrading the manufacturing industry, the Bosch Group China factory utilizes the industrial log analysis module of Notes AI to reduce the equipment fault diagnosis time from 6.5 hours before to 11 minutes. With the real-time processing of more than 450,000 sensor data streams per minute (18 types of parameters such as pressure, temperature, and vibration frequency), and the 3D digital twin model, the rate of accuracy for predictive maintenance is 94.7%, and the equipment annual downtime is reduced by 37.6%, equivalent to an additional output value of 280 million yuan. In legal industry application scenario, Linklinkers’ AI contract review system is based on the Notes NLP core algorithm to achieve 1,200 pages of legal document per hour analysis capacity in M&A (mergers and Acquisitions) business, and the key risk points coverage rate is 83% higher than human work. Attained reduction in the 100-page due diligence report creation cycle from 72 hours to 9 hours, with an error rate of less than 0.3%, resulting in a 29% increase in 2023 cross-border M&A revenue.
In education technology, after Khan Academy adoption of Notes AI’s smart note-taking software, students’ mastery of knowledge points increased by 41%. The system documents the learning trail of 12 million users through behavior analysis algorithms (sampling up to 60 times per second), and creates an individual review model that improves the slope of the knowledge memory retention curve by 2.3 times. In the markets, Bloomberg’s quant team used Notes AI’s earnings call analysis module to review 38,000 emotional semantic units per minute, digging out management “soft information” 76% further than standard text analysis. Helped hedge fund clients increase their alpha returns on S&P 500 stocks by 2.4 percentage points per year. For retail application, Walmart China’s supply chain department improved the effectiveness of inter-departmental collaboration by 58% through the meeting decision tracking feature of Notes AI, the accuracy of the demand forecasting model improved to 91.4%, and inventory turnover days were optimized from 32 days to 23 days, the equivalent of liberating 780 million yuan in working capital.
According to IDC’s 2024 Digital Transformation White Paper, organizations using Notes AI have reached 3.7 times the industry average in knowledge asset usage, and their fundamental technology platform includes: 1) multi-modal large model of 30 billion parameters, which can perform intelligent parsing of 12 file types; 2) A distributed computing engine processing 2.4TB of unstructured data per second; 3) A semantic understanding system aggregating 68 industry knowledge maps. Amazon AWS collaboration examples demonstrate that Notes AI attained 94% accurate automatic classification of work orders in cross-border e-commerce customer service situations, lowering the average handling time (AHT) from 8 minutes and 12 seconds to 1 minute and 47 seconds, rising by 19 percentage points in customer satisfaction (CSAT), and saving over $6.5 million in yearly labor expenses. These numbers confirm that Notes AI is taking an exponential jump in productivity by retooling the atomization-reorganization-value-conversion knowledge workflow chain, and its technology penetration will reach 43.6 percent of the enterprise software market in 2027 (61.2 percent CAGR).