Pain 1: Users reported that retrieving simple research data takes too long, particularly in investment sales and mortgage banking, where quick access to data from sources like Costar, Yardi, RCA, and MSA is crucial.

We conducted interviews with 20 users to identify the primary business pain points.

Pain 2: The creation of marketing and loan documents for property listings, including social media content, marketing materials, BOVs, OMs, and underwriting narratives, is also a significant burden.

Pain 3: Users generally lack of trust of AI technology, leading to uncertainty about its applications and fear of misuse.

We organized a strategic ideation workshop with the product and development teams to align on key user pain points and business objectives, while also gathering insights from developers regarding the feasibility of proposed solutions.
1. Prompt Library
2. User Profile
3. Data Assistant
4. Internal Tool Integration
5. Deep-research
6File Upload

By enabling investment sales advisors and mortgage bankers to easily select accurate, targeted data from multiple entry points, we improved both the efficiency and accuracy of their daily research. This enhancement helped them respond to client questions and requests more quickly and confidently.

To support less tech-savvy users in getting the most out of Berkie, we built a robust prompt library featuring examples across different business areas. It encourages users to interact, experiment, and learn by doing, ultimately boosting engagement and laying the foundation for a future best-practice business community.

After launching the prompt library, we received strong positive feedback along with high user engagement. We also gathered valuable constructive feedback, including:
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1. Some users expressed interest in sharing their best prompts with team members to help establish consistent standards in their workflows. For example, the underwriting team wanted to share preferred formats and guides to improve efficiency across their group.
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2. As the prompt library grew, users found it increasingly difficult to locate prompts relevant to their specific needs, such as their department, role, or tasks. During team discussions, we realized that while a fully personalized solution would be ideal in the long term, a quicker and more practical improvement would be to add a search function to the prompt library. This would allow users to easily find prompts related to key tasks and topics of interest.

Through continuous user feedback and workflow analysis, we uncovered a critical need for deeper research capabilities within Berkie. Commercial real estate (CRE) professionals—especially underwriting teams—often rely on highly detailed, specific data to support investment decisions, underwriting, and client advisories. Existing tools offered surface-level insights but lacked the depth and flexibility needed for more complex tasks, particularly in document discrepancy analysis and property underwriting summaries. To close this gap, we designed and built an deep-research function that enables users to dive deeper into property, market, and deal-level data without having to manually compile information from multiple sources.

To enhance user engagement by creating a more cohesive and visually appealing experience that meets user expectations, we decided to rebrand this product. Refreshed brand identity into UI elements, interactive components, and storytelling can make interactions more intuitive and engaging. A modernized design system also improves usability, streamlining workflows and building trust in the platform.

We developed a comprehensive entry point system for commercial real estate users, enabling fast and precise data retrieval for diverse research requirements. This system facilitates the extraction of pertinent data efficiently.

AI product design differs from traditional UX, as it’s driven by technological advancements rather than user needs. Designers must adapt by aligning AI capabilities with real problems while leveraging AI tools to accelerate research and development.

The rapid pace of AI shortens product cycles, requiring agile processes to keep users at the center. However, blindly copying existing AI models can be ineffective. Instead, designers should prioritize usability, integrate AI seamlessly into workflows, and validate solutions through rapid testing.

Success in AI UX hinges on adaptability, critical thinking, and balancing innovation with human-centered design to create meaningful user experiences.

We developed a comprehensive entry point system for commercial real estate users, enabling fast and precise data retrieval for diverse research requirements. This system facilitates the extraction of pertinent data efficiently.