About
For a banking institute, we implemented an advanced AI-driven system using machine learning and facial recognition to track customer emotions during interactions with bank managers. Cameras analyze real-time emotions (positive, negative, neutral) and conversation flow, providing insights into customer satisfaction and employee performance. This enables the Client to optimize operations, reduce inefficiencies, and cut costs while improving service
Challenge, approach, and impact
Lack of objective emotional insight in digital interactions
Digital products and online platforms lacked a reliable way to understand users’ emotional reactions in real time. Feedback was subjective, delayed, or limited to surveys, making it difficult to measure engagement, stress, or sentiment during interactions. The challenge was to capture emotions accurately from visual data while ensuring scalability, acceptable accuracy, and seamless integration into existing digital workflows.
How we built
Testimonials
Alex Rasowsky
Banking company
“They delivered a successful AI model that integrated well into the overall solution and exceeded expectations for accuracy.“
Team structure
Client team
Alex Rasowsky
CTO
Project stakeholder
The client stakeholders were working closely with the team at Dataforest
Agency team
2 x Product Manager
Production
2 x Data Engineer
Production
1 x Business Analytics
Production
