technical architecture
Brainfish's environment AI agent adopts a layered visual understanding framework: the bottom layer captures interface element relationships through pixel-level DOM analysis, the middle layer applies behavioral pattern recognition to build a predictive model of user intent, and the top layer generates a decision tree in conjunction with product business logic. This architecture can accurately identify 87% operational blocking points.
operating mechanism
When the user stays in a certain interface for more than the average time, the system immediately initiates a three-stage response: ① comparing the solutions of similar scenarios in history; ② detecting the deviation of the current operation path; and ③ dynamically generating embedded prompts containing interface markers and step-by-step instructions. Measurements show that this function shortens the user learning curve by 40%.
Unique Advantages
Compared with traditional screen recording analysis tools, the technological breakthrough lies in the real-time processing capability: it supports simultaneous monitoring of 500+ concurrent sessions, with latency controlled within 300ms, and the accuracy rate is 3 times higher than that of log-based analysis methods. After an e-commerce platform accessed it, the amount of help requests dropped by 72%.
direction of evolution
The system is integrating augmented reality technology to directly guide user operations through visual markers in the future, and has achieved deep integration with development tools such as Jira, so that high-frequency user confusion points are automatically transformed into product optimization requirements.
This answer comes from the articleBrainfish: Self-generated Help Documentation for Online Customer ServiceThe
