GOALS

• Integrate EyeLevel's AI solutions into our existing healthcare platform to provide personalized treatment recommendations to doctors based on patient data analysis
• Build an AI-powered system that can automatically analyze medical images like X-rays and MRIs to detect anomalies, assisting radiologists in faster and more accurate diagnosis
• Develop a secure and HIPAA-compliant AI system that can transcribe and analyze patient-doctor consultations, extracting valuable insights for research and improving patient care quality

Frustrations

• Concerns about data privacy and security when using AI, especially with sensitive patient information
• The lack of technical expertise within the team to effectively implement and manage AI solutions, requiring external consultants or training
• Resistance from healthcare professionals to adopt AI-based tools due to fear of job displacement or skepticism about their accuracy

GOALS

• Develop an AI-powered chatbot that can handle customer queries accurately and efficiently, reducing wait times and improving customer satisfaction
• Train LLMs on customer interaction data to personalize responses, offer product recommendations, and improve customer engagement
• Use AI to analyze customer feedback and sentiment from various channels to identify pain points, improve products and services, and proactively address customer issues

Frustrations

• The difficulty in finding and integrating high-quality, domain-specific data to train LLMs effectively for specific customer service tasks
• The constant need to fine-tune and update AI models to keep up with changing customer behavior and language trends
• The challenge of measuring the ROI of AI implementations in customer service and demonstrating their tangible impact on business metrics