OMA

Seniors and their loved ones are facing increased, but not unprecedented, physical distance during the COVID crisis, making even more evident the emotional and mental strain that multigenerational circles face to stay connected. Through extensive Design research, we created an MVP to enable families supporting seniors to connect and provide present and future care. 

OMA is a mobile app that leverages ethical AI to amplify the connection between seniors and their support network providing opportune wellbeing insights to project better care through old age

With 225M Americans over 65 by 2050 and 27% living alone, social isolation ,loneliness is a serious yet under-appreciated public health risks that affect a significant portion of the older adult population. While there are challenges in measuring social isolation and loneliness precisely, there is strong evidence that many older adults are socially isolated or lonely in ways that puts their health at risk, the majority have family members that are interested in connecting and providing care, but current designs fall short of facilitating insight and connection.

Through prototype testing and ethnographic research, we found that shared stories are the foundation of many gatherings and phone calls where stories are built upon every time they gather. They help Seniors and their family members connect and are a viable way to detect cognitive and emotional wellbeing, making it easier for families to stay together, everywhere.

OMA leverages Voice Interactions and Ethical AI to amplify the interaction between seniors and their families, facilitating opportune insights and projecting better care through old age. Aiming to incite storytelling and sharing through voice and visuals, OMA enriches family interactions with media and new facts, whilst delivering emotional and cognitive prompts to detect variance over time and project future care. 

Designed for radical Usability, OMA can be used on Smart TVs, Home Voice Assistants, and Smartphones. Rooted on existing interaction mental models Senior users have with natural conversations, radio, and TV remote controls, OMA leverages emotion, orientation, and cognition recognition models to deliver private and ethical insights about aging to a close family circle.

Through understanding this multi-stakeholder problem we found in 2 main populations needed a solution for this problem: 

• Seniors aging at home or at low-intervention housing such as community housing : 

  • Little insight into their emotional / mental health or unwillingness to share - makes it difficult for them and people around them to manage and project care

• Adult children / grandchildren: 

  • Deal with the emotional change of now being a care provider for their parents and  often have little insight into seniors mental and emotional state 

To solve for those needs, my solution needed to carry out three key jobs to be done for Adults and  Seniors

• With the least amount of digital barriers around our design , it needed to help understand seniors emotional and mental state through non invasive check ins

• It also needed to Facilitate meaningful connection beyond phone calls, creating shared bonds through accessible interactions

• And finally , it needed generate Care predictions based on pattern variance over time: so we could provide insights into current and projected wellbeing of a seniors

In other words, allow users who are aging or supporting aging to : Check in to collect information of seniors emotional and mental state, Connect beyond phone calls to maintain permanent bonds , And discover present and future needs based on collected data

1 in 3 seniors suffer from isolation and loneliness, which lead to a serious loss of physical and cognitive decline. To efficiently support seniors’ mental and emotional health, there is an urgent call for adult children to stay tuned of how a loved one is doing mentally and emotionally, and intervene before damage is done. 

Targeting Adult Children as customers for a monthly subscription, OMA is a senior-friendly digital platform that leverages accessible interactions and AI to create meaningful connections between seniors and their loved ones. With OMA’s daily check-in feature, adult children will get access to and keep track of seniors' mental and emotional health. The connection feature allows families to share and interact in the context of their long-term relationship and their day-to-day discovery. The check-in and connection data are analyzed by AI-powered systems to provide adult children insights into potential mental and emotional care needs of seniors.

As designers, we thrive by looking for answers to tough human problems and needs. Experienced in design thinking and lean startup building ,we have led successful design sprints, workshops and projects and have prototyped and tested to get answers of how we should design innovation, especially when it comes to human-centered AI. 

Having been a corporate Designers and Product Managers , we have core development skills for technology. I think there is a great opportunity for team members grow as leaders and designers by collaborating on a 0 to 1 venture that solves a real human problem.

Founder: As an immigrant Latina Founder, SOLVE is an opportunity to refine my business skills, gain new perspectives and refine the skill of generating the business strategy of a great product. I gain confidence pitching the venture quickly and efficiently and building the tech product that leverages ethical design.

We are applying to solve for the impact of the community and mentors, we believe that if we surround ourselves with social-mission driven founders we will win insight and partnership that will better inform our venture, we also look forward to helping as best as we can. 

If we are admitted to SOLVE, we plan to be dedicated to pitch and refinement of ideas , as well as getting key feedback from advisors. On the other hand, we are committed to community and being of service with product and design workshops. By allocating resources on designer salaries and Machine Learning advising, we will have a constantly improved prototype and a ML infrastructure paper that will help us size the venture requirements

As we move away and become Adult Children of Senior parents, there is a need to bridge day-to-day interactions and gameplan care and support as best as we can. Of the 53M Seniors in the US (projected to grow to 83M by 2050) 1 in 3 live alone, at the same time, 1 in 5 American adults are caring for a senior whilst living apart. The physical distance and reversal of care roles make supporting and going through aging often challenging.

OMA leverages Voice Interactions and Ethical AI to amplify the interaction between seniors and their families, facilitating opportune insights and projecting better care through old age. Aiming to incite storytelling and sharing through voice and visuals, OMA enriches family interactions with media and new facts, whilst delivering emotional and cognitive prompts to detect variance over time and project future care. 

Designed for radical Usability, OMA can be used on Smart TVs, Home Voice Assistants, and Smartphones. Rooted on existing interaction mental models Senior users have with natural conversations, radio, and TV remote controls, OMA leverages emotion, orientation, and cognition recognition models to deliver private and ethical insights about aging to a close family circle.

Through prototype testing and ethnographic research, we found that shared stories are the foundation of many gatherings and phone calls where stories are built upon every time they gather. They help Seniors and their family members connect and are a viable way to detect cognitive and emotional wellbeing, making it easier for families to stay together, everywhere.

Current solutions focus either on collecting information first hand and sharing statically (such as Ancestry) or in-the-moment connection (such as Portal and Instant Messaging solutions). OMA allows for natural collection of memories through voice, incentivizing connection between seniors and their families whilst providing insight into seniors current and future wellbeing.

In the next 5 years we expect to measure our impact in the following ways:

• Simplicity

Easy or intuitive regardless of experience, knowledge base, language skills, and level of concentration

• Consistent with users’ expectations

• Eliminates complexity

• Provides cues, prompts, and feedback

• Inclusive

Creates products that are physically, cognitively, and emotionally appropriate for a wide range of diverse people to access those products, including people with and without impairments

• Inclusive AI:

  • Cultivate diversity with privacy and consent

  • Enlist customers to correct AI bias (dataset bias, association bias, automation bias, interaction bias, confirmation bias)

• Create solutions with utility and elegance to reduce physical, cognitive, and social exclusion

• Scalable

Able to be easily extended and incorporates enhancements in the future.

• Able to foster communication, connection and community

• Extendable to international markets

• Modular features to incorporate the complex and evolving situations of end-users

2.In the next 2 years we expect to cover the following milestones

No.

Milestone

Date of Completion

M#1

Design for V1 completed

T0+6

M#2

Code for V1 completed

T0+12

M#3

Testing for V1 completed

T0+13

M#4

Release Version 1 (ALPHA)

T0+13

M#5

Design for V2 completed

T0+15

M#6

Code for V2 completed

T0+19

M#7

Testing for V2 completed

T0+22

M#8

Release Version 2 (BETA)

T0+23

M#9

Continuous Support and Maintenance.

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In early stage (0-6 month)

• Goals: justify our product direction by proving:

  • 1. new users see the value in the product or new feature 

  • 2. users enjoy app content and keep engaging with it

  • 3. Users find the app helpful and easy to use

• Metrics:

  • Metrics for adoption:

    • Download rate, expected: 20%+

    • Registration rate, expected: 70%+

    • Feature adoption rate for collecting memory, expected: 95%+

    • Feature adoption rate for revisiting memory, expected: 90%+

    • Feature adoption rate for sharing memory, expected: 85%+

  • Metrics for engagement: 

    • Average session length, expected 15+ mins

    • Average session frequency, expected 3+ times /week

    • Daily active users

    • Monthly active users

    • Daily number of memories uploaded

    • Monthly number of memories uploaded

  • Metrics for satisfaction:

    • Net Promoter Score, expected 70+

    • Customer satisfaction rating

    • Number of 5-star reviews

  • Metrics for usefulness:

    • Mood ratings from seniors, expected 20% increase during usage

In growth stage (6month - 2 years)

• Goals: justify our business model by proving:

  • 1.users keep coming back to the app

  • 2.revenue generation for OMA and partners

• Metrics:

  • Metrics for engagement: 

    • Average session length, expected 20+ mins

    • Average session frequency, expected 5+ times /week

    • Daily active users

    • Monthly active users

    • Daily number of memories uploaded

    • Monthly number of memories uploaded

  • Metrics for retention:

    • Subscription renew rate, expected: +70>#/p###

  • Metrics for revenue: 

    • Partners sales, expected 5% increase

Beyond the need to design and build accessible and ethical support for aging, we believe OMA is a catalyzer for responsible preventive care for aging.

One of the biggest opportunities for disruption and equitable value creation over the next decade is going to be the disruption and re-configuration of care. Arguably one of the consumer groups is US healthcare which will skew older and more independent and in a 6 Trillion Dollar business that is the healthcare industry, the ability to disperse care from only doctors offices or hospitals into devices and homes could potentially take care from an reactive sickness-driven industry to a preventive health-driven industry. 

Our goal is to responsibly give seniors and families insight and agency in their senior care. Designing for dignity and equity in aging by shaping AI into the responsible and ethical tool seniors and their families need to get to early discovery and intervention, whilst allowing them to come closer through family stories

OMA is a mobile app that allows users to create social circles and do three things: check in, connect and gain insight into senior’s well being.

summary of tech by value prop:

• Incite connection through natural interactions: Voice API, phone interact API

• Detect key neurocognitive data : Key phrase detection, NLP 

• Exercise and maintain mental and memory acuity:  GANs memory description

• Layer and create content based on key data: Category , Vision API

 Details:

• Set up: allows family members and seniors to set up a closed networks and set up accessibility and privacy settings this is important because it determines whether reaching the senior will be mostly through voice or voice and visuals

  • It also allows users to leverage voice hardware and smart TVs as platforms through which users can interact

• Check In: accessible mental check in system that supports senior solo work through mental games and emotional prompts so we can share , when consented,  results with family members opportunely 

  • We leverage : Conversational AI: used to prompt and respond to mental check ins 

• Connect : a connecting platform that allows families to share and interact in the context of their long term relationship and their day to day even when they cant hop on a call. The connection platform focuses on long term connection by collecting stories and facilitating family responses, album creation and enrichment by adding music and new fact we can relate to memories. 

  • The technology leveraged here are used to enrich family material with new facts and media and categorize content

• Discover: discover is an insight platform based on check ins and connection data to support better care decisions

  • Based on Care predictions based on NLP linguistic pattern variance over time: Used provide insights into current and projected wellbeing of a senior

As 3 minority founders and designers, we understand Growing up underrepresented in the US, working as designers in tech , our existence is often split as a minority in tech but also as a creatives in a lets get results fast land. We recognize how this split perspective is important , as it gives us the platform to pose questions about why we are building AI solutions with the user or ethics as an afterthought . It has given us the ability to be a beacon for underrepresented minorities in AI and tech and we are dedicated to building cutting-edge technology for social good with teams. 

Our approach is simple, we mentor and train underrepresented individuals without traditional backgrounds in tech to give them the space they need to solve challenges and as we expand with them. A great example is our UI/UX designer Tomomi, coming from a preschool teaching experience into UIUX through design apprenticeships with us. 

Targeting Adult Children as customers for a monthly subscription, OMA is a senior-friendly digital platform that leverages accessible interactions and AI to create meaningful connections between seniors and their loved ones. With OMA’s daily check-in feature, adult children will get access to and keep track of seniors' mental and emotional health. The connection feature allows families to share and interact in the context of their long-term relationship and their day-to-day discovery. The check-in and connection data are analyzed by AI-powered systems to provide adult children insights into potential mental and emotional care needs of seniors. 

Revenue streams:

- Subscription based (monthly-based, free cancellation)

- Seniors that live independently or are in senior care facilities: 13.8 million + 2.5 million = 16.3 million

- Capturing 1% of this population @ $5.99 per month subscription = 11.7 million per year

We will focus on partnerships and DTC advertising for new customers, and on going CRM (both active and passive) to maintain and retain users

Customer relationships:

Adopters (adult children): 

- Reactive relationship = in-app chat bot

- Proactive relationship = notification bot

External end users (service providers):

- Reactive relationship = ticket-based feedback/questions

End user (seniors):

- Reactive relationship = voice bot/chat bot

- Proactive relationship = visual prompts (ex. Memory tasks)

Key partners:

Software companies:

- Google software

- integration into existing communication tools

Care facility:

- help acquire users

- purchase products to advance their service

- educate and participate in regular use of the product

Healthcare agency:

- resources for seniors, provide them data for research purposes

Key activities:

- Revise product functions

- Update platform with useful resources and tips for seniors and their family

- Analysis of user data from end-user for health and mental process tracking

- Analysis of user data for business decision

- Interviews/collecting feedback from all users

- Customer service

- Technical support

Unit Economics: A subscription of OMA is one unit.

Customer Lifetime Value (LTV):

LTV = Annual Collection/Customer * Gross Margin (%) * Lifespan of customer

• The annual collection per customer/revenue is estimated based on comparing pricing information we obtain from our potential competitors and some justification and modification is made on the estimation, considering that our product is at an early stage. We estimate a monthly subscription cost of $20

• We estimated a gross margin of 45% to account for operational expenses, R&D etc.

• We estimate a lifespan of a customer to be at least 2 years, but here we just considered the first year after App launch.

 Customer Acquisition Cost (CAC):

 CAC = Cost to acquire one customer through marketing 

• We assumed 20,000 new customers for the first year, considering that our product is brand new and is at its early adoption stage

• We estimated a total cost of $767,800 to acquire all 20,000 customers through sales and marketing (See the cost details in Marketing Costs)