Case Study: AI-Powered Note Summarization for Behavioral Health Professionals

Summary

Faced with the challenge of reducing the administrative burden on behavioral health professionals, I led the development of an AI-powered session summarization tool. Through rapid prototyping, competitive analysis, and customer research, I uncovered a critical industry barrier—trust in AI for sensitive documentation. This insight led to a strategic pivot, identifying new market opportunities where AI-generated summaries could thrive. The process showcased my ability to validate ideas, iterate quickly, and adapt based on user feedback.

Problem

Behavioral health professionals spend a significant amount of time completing notes after sessions. These notes are critical for demonstrating the need for continued care, insurance documentation, and legal protection. However, this documentation often extends beyond normal working hours. Additionally, providers who take notes during sessions may find it distracting for both themselves and their clients. The challenge was to create a solution that could generate accurate, efficient, and secure session summaries while addressing industry-specific concerns, such as privacy and trust in AI.

Process

1. Prototype Development:

- Created an initial prototype using Zapier to record the session.

- Developed a workflow that summarized the recording using AI prompts and stored it in a Google Doc.

- Tested the prototype in a mock setting, with promising results.

2. Customer Research & Competitive Analysis:

- Conducted a competitive analysis of existing solutions in the market.

- Discovered that all competing offerings were web-based and required direct recording from a computer, with no mobile app available.

- Engaged with potential users to understand their pain points and needs.

3. Product Design & Development:

- Created wireframes in Figma to visualize the user experience.

- Used FlutterFlow and Buildship to start building the front-end and back-end of the app.

4. Customer Validation & Pivot:

- Conducted multiple customer interviews with behavioral health professionals.

- Identified a major challenge: lack of trust in AI handling sensitive therapy session data.

- Concluded that the solution did not align well with the behavioral health industry’s privacy concerns.

- Pivoted to explore alternative markets where AI-generated summaries might be more viable.

Solution

The initial solution leveraged AI to generate instant and accurate session summaries, reducing the administrative burden on providers. While technically feasible, customer research revealed trust issues within the behavioral health sector, leading to a strategic pivot toward industries with lower sensitivity to AI-generated documentation.

Outcome

- Successfully built and tested an AI-powered summarization prototype.

- Identified key competitive gaps, such as the lack of a mobile-friendly solution.

- Gained valuable user insights that reshaped the product’s target market.

- Pivoted to new industry opportunities based on customer trust concerns.

- Demonstrated the ability to research, prototype, iterate, and adapt based on real-world feedback—key product management competencies.