Aiberry

Before we started:

Working with mainly a team of engineers on the product side. I created a workflow process for design revision and developer handoff documentation. The team lacked a design system, but we had to be resourceful given tight deadlines and quick turnaround times. We decided to implement the Material Design system and modify its elements to align with Aiberry's branding and essence.

Research:

Aiberry operates in a competitive landscape where its distinct GTM (Go-To-Market) Strategy sets it apart. While many competitors focus to B2C markets, Aiberry's primary focus centers on B2B engagements, particularly targeting Healthcare/Wellness Corporations and Institutes (considered the toughest audience to convince about product efficacy).Analyzing B2C competitors revealed consumer preferences and dislikes. And it helped us understand how we could better serve our users, especially those taking on a "patient-role" within these organizations. Shaping strategies to meet their unique needs and expectations.

Priority #1 Switching Core Functionality to Self Screening - AI

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Goal

Based on product strategy meetings, we decided to pivot from telehealth and focus our efforts on self-screening functionality. The goal is to make this feature the main differentiator between Aiberry and other competitors. We're focusing on multiple roles: the practitioner role and the member/patient role._‍

Thinking about Audience:

1. Practitioner Users (Healthcare Providers - Age: 35-70yrs):

Healthcare providers can conduct quick and objective mental health screenings.

Objective Mental Health Screening: Prioritize a streamlined interface that allows for quick and efficient mental health screenings.

Ease of Use: Design intuitive workflows and navigation considering potential variability in technological proficiency among users.

Data Interpretation: Provide clear, concise data presentation and interpretation to aid practitioners in making informed decisions.

Compliance: compliance with healthcare regulations to instill trust in the platform.
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2. Patient Users (Age: Varies from young adults to seniors):

Individuals that are in need of help for their mental health.

Comfortable and Non-Intimidating Interface: Create a welcoming and easy-to-use interface that doesn't overwhelm users dealing with mental health issues.

Clear Guidance: Offer clear instructions and guidance throughout the assessment process to alleviate any potential confusion or stress.

Accessibility: Ensure the platform is accessible to users of varying technological literacy and different age groups.

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The challenge was twofold:

First, it involved designing an interface and user experience that felt welcoming and comfortable for patients and practitoners.

Secondly, the design had to ensure that the use of AI was seamlessly integrated without causing confusion or overwhelming the patients to a degree that might affect the accuracy of their assessment results.

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Exploration:

Key Aspects to keep in mind:

1. In order to have an accurate result by using AI, flow will have to incorporate text, audio, video.
2. Patient will be able to do “self assessments”. Practitioners can only task the user to take a self assessment and receive results.
3. Need to think about mobile and desktop resolutions

During research, it became evident that AI was best represented with an avatar. However, I was concerned about the use of avatars, as they could make users uncomfortable if implemented poorly. This was especially important considering that this app would be used by individuals dealing with mental health disorders

Aiberry had incorporated emojis as part of their branding. We decided to experiment with this concept as one of the options for representing the AI.

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Micro interactions:

Talking pulsing animation, voice element, talking and listening transitions.

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Solution and Validation:

After creating multiple options and constant collaboration with developers, product owner, stakeholders, and internal clinical researcher team.

We presented the top two flow/prototypes options to a group of practitioners and qualified patients, to validate the experience. And conducted in-person user testing.

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Patient Flow:

• Insights from user testing had incredible value
• Patient users felt comfortable talking to an AI
• Patient users liked the emoji avatar “Botberry”
• Patient users were able to navigate easily through the assessment

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Solution:

• Botberry conversational expressions, by creating and animating different emotions.Phase 1, started with 2 ( talking, and listening)
• Time-limit without disrupting patient or cutting them off without a warning.

Practitioner Flow:

Insights from user testing had incredible value

• Easy to use
• Excited to assign self-screening assessments to their patients
• Concerns about some patients not having the right environment to conduct self-screening, affecting results

Solution:

To create a step by step-check equipment flow pre-screening to insure Microphone and Camera met the environment requirements for AI to provide accurate results.

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Results:

Recovery Health Center became an investor, partnering to improve the platform and provide greater insights into the market

“Dr. Tammy Malloy PhD, Chief Operating Officer of Futures Recovery Healthcare, a Palm Beach, FL alcohol and drug rehab treatment center, implemented an AI-based assessment technology from Aiberry to improve quality of care.”

Series A- Seed Round Closes with $8M

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Additional Context: (Other Major Flows /Functionality)

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Patient Detail and Assessment Results Practitioners

Practitioners needed access to patient information, including a quick glance at their progress, upcoming screenings, and assessment history. The system also needed functionality to alert practitioners if a patient was at high risk / in need of intervention based on assessment scores and insights.

For practitioner role, the result page is one of the most important pages reviewing patients scores and insights based on self screening assessment. With the help of AI , we could provide valuable insights to the practitioner showing Symptoms analysis of mood, concentration & energy and access to the conversation transcripts. Based on practitioner feedback, we focused on improving the information hierarchy and visually demonstrate all this information without overwhelming the user.

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Dashboard Analytics

A highly anticipated feature for organization owners was the dashboard analytics. To provide a comprehensive view of patient progress, we developed a dashboard that tracks various data points. This dashboard offers a snapshot of the organization's performance in utilizing Aiberry's telehealth and self-screening assessments. Through extensive research and collaboration, we designed a range of visualizations to effectively represent key metrics.

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Telehealth Flow Improvement

Aiberry initially focused on telehealth services but shifted its strategy to prioritize self-screening based on business objectives. The success of self-screening led us to reassess and enhance the telehealth experience. By incorporating AI into the process, we aimed to provide practitioners with a valuable tool to improve patient care.