Mindcurrent

Mindcurrent uses Artificial Intelligence to discover, predict, and visualize workplace stress.

Its machine learning algorithm identifies each employee’s unique stress patterns. The company then provides personalized recommendations from experts to help each user manage and reduce their stress.

Mindcurrent’s Chief Technology Officer has achieved three successful tech exits. Its Chief Product Officer has sold more than $1 million of online learning content, and has been a personal coach to NFL athletes and CEOs.

Mindcurrent has attracted 25,000 users. Early customers include finance companies, universities, law enforcement agencies, and non-profit organizations. It’s also received investments from executives at Nike and the city of Beaverton, Oregon. The company is raising funds to expand its customer base and further develop its platform’s unique algorithms.

Workplace stress is a $977 billion problem. According to the European Agency for Safety and Health at Work, workplace stress costs European businesses $677 billion in lost productivity each year. The American Institute for Stress reports another $300 billion lost in the U.S.

Many companies offer wellness programs. But most of these programs put the responsibility for stress reduction on the employee, with no means of measuring progress or success.

Mindcurrent is the only solution that enables all employees to see where their individual stress is coming from, and receive personalized recommendations suited to their needs. The company also provides privacy, as all data is aggregated anonymously. This enables companies to see where progress is being made without seeing individual employee's status.

The key to Mindcurrent’s potential is its ability to quantify and predict the root of a person’s stress. In doing so, the company can offer personalized wellness solutions.

Recommendations are designed to be quick, easy, and flexible. This enables users to make progress each day without disrupting their schedules or making large commitments. Mindcurrent believes this is how stress can be systematically reduced.

As a few examples, users can receive recommendations for solutions like:

• Nike Run Club to help with fitness goals.

• Oura, which provides insights into sleep habits and patterns.

• Headspace, which offers meditation tips and lessons.

• And Noom, which provides advice for improving one’s nutrition and diet.

By recommending these solutions through partnerships with companies like these, Mindcurrent could potentially create several additional sources of revenue.

Mindcurrent developed its initial prototype in early 2019. This version asked users questions about their mood and feelings, tracked their responses, and offered personalized advice. Local media in the company’s home state called Mindcurrent a “Fitbit for the brain.”

Mindcurrent then fine-tuned its app, creating a second and third version. The third version is available in the Apple App Store and Google Play Store.

Most recently, the company designed its fourth version using feedback from users and companies. This version enables users to capture and categorize stress within seconds, and integrates biometrics from their smart watches for stress pattern predictions.

Furthermore, this version introduces a reward system where users are incentivized to "check in" daily and take simple, quick actions to reduce stress.

A demo of its latest version helped Mindcurrent win the 2020 Beaverton Startup Challenge in Oregon. It also helped the company secure its newest customer, the city of Beaverton. This city is working on a pilot program with Mindcurrent using its government employees and first responders.

Mindcurrent’s latest version is also being used in a joint behavioral study with the Center of BrainHealth, Brain Performance Institute, and University of Texas at Dallas. 50 students and faculty are tracking their stress with Mindcurrent over 45 days.

They’re also contributing biometrics with data from their Apple watches. According to Mindcurrent, when published, this will be one of the largest studies of its kind to determine key stressors affecting life for college students.

Mindcurrent hasn’t started generating revenue yet. Soon, it will sell its service to companies through subscriptions.

The company will offer pricing based on the size of the companies. Prices will range from $99 per month for small businesses (fewer than 50 employees) to $1,999 per month for companies with between 500 and 1,000 employees.

Team Background

Drew Brazier - Chief Product Officer

Throughout his career, Drew has built two private practices for personal coaching, and sold more than $1 million in online learning content. He’s personally coached NFL athletes and CEOs.

For 10 years, he was a leadership performance consultant for 361Leadership, a company providing mentoring and coaching.

Before that, he spent 11 years as a professional speaker, lecturing on topics including human performance, leadership, and personal development.

Early in his career, Drew owned Optimal Solutions, a Colorado-based private practice focused on helping clients with issues like weight loss and Post Traumatic Stress Disorder.

He holds a Doctorate degree in Clinical Psychology from Argosy University.

Sourabh Kothari - Co-Founder & CEO

Sourabh began his career as Assistant Vice President of Research Marketing for Merrill Lynch.

He then spent two years as a principal strategist with ON24, an Internet services company focused on webcasting. From there, he worked for Cisco (Nasdaq: CSCO), a company developing telecommunications equipment.

More recently, Sourabh was Director of Advocacy for Signifyd, a software company specializing in fraud protection. In 2016, this company was recognized by Forbes as part of the “Forbes Fintech 50.”

Sourabh studied Economics and Finance at San Francisco State University.

Daniel Cunningham - Co-Founder & CTO

Daniel is a serial entrepreneur with three successful exits.

He has started software-related companies focused on online gaming, fraud prevention, and logistics.

More recently, he became an angel investor focused on investments in Artificial Intelligence and machine learning.

Daniel studied Computer Science at the University of California San Diego.

Co-Investors