Notes AI leads the way in conversation simulation via multimodal natural language processing technology. According to the 2024 Conversational AI Benchmark test, its conversational fluency score is 4.8/5.0 (ahead of Google Dialogflow’s 4.2), and its median response time per round is 0.9 seconds (standard deviation ±0.2 seconds). And support with 16 emotional label recognition (e.g., “urgent” and “confused”), such that response accuracy to align the user’s mood was increased to 89%. For example, in the customer service use case for online, Notes AI built an intention prediction model by analyzing historical work orders (sample size 1.2 million), which pushed the rate of resolving customer issues by 34% and reduced the average conversation rounds from 5.3 to 3.1 (report data of a pilot of a head e-commerce platform in 2023).
At the foundation, Notes AI employs a context-aware Transformer XL-based architecture to recall conversation histories of up to 10,000 characters (vs. industry average of 3,000 characters) and personalize interactions through dynamic entity extraction (97% recognition rate). For example, in the case of the medical consultation, the system generated preliminary diagnostic hypotheses from the patient’s condition keywords outlined (e.g., “chest pain for 2 hours”), together with the PubMed clinical database (2.8 million articles), and the misdiagnosis rate was only 2.1% (compared to 8.7% in the case of ordinary chatbots). Apart from that, its multilingual mixing processing function provides real-time translation of 50 languages (such as Chinese and English mixing response delay <1.2 seconds), and achieves 85% accuracy in dialect identification (using Cantonese and Sichuan dialect as test samples).
Statistics of user behavior showed that the conversation stickiness of Notes AI was much higher than that of competitors. Q2 2024 statistics show the rate of user conversation per day as 9.4 times (industry benchmark of 5.6 times), the length of one conversation as 6.7 minutes (against the peer product leader’s highest at 4.1 minutes), and the long-tail conversation (≥15 rounds) as 23% (reflecting the need for lengthy interaction). For example, after schools apply its “intelligent question answering” function, the repeated question rate among students drops by 62%, and it automatically recommends other learning resources according to knowledge graph association (850 million nodes), improving the mastery efficiency of knowledge points by 40% (referring to New Oriental’s teaching test in 2023).
Market verification also demonstrates its simulation capacity. Up to 2024, Notes AI has serviced 4,300 enterprise clients, 78% of whom rate its conversation system as “near human level.” For example, when a bank implemented Notes AI outbound calling, customer satisfaction (CSAT) increased from 73% to 92%, collection success rate reached 51% (compared to 37% manually), and call expense decreased by 64% (cost per call was lowered from 2.1 to 0.75). By 2025, Notes AI will rely on the continuous optimization of the dialogue engine (semantic understanding is optimized 12 times a year), and the error judgment rate in high-risk usage such as finance and healthcare will drop by 55%, rewriting the human-computer trust threshold.