Mike Betzer, CEO
Today, many organizations have started on their AI/ML journey but have fallen into a typical trap of data science projects. They are stuck at the experimentation stage and not deploying models into production environments where they can become valuable to the business. In other cases, organizations may not have the data scientists, ML engineers, and application developers needed to execute an end-to-end AI solution.
Enter Hypergiant. The company specializes in getting AI projects “unstuck” and across the finish line through a combination of its industry-leading consulting services and the HyperDrive data science platform. “When Hypergiant was founded, we had a mission in mind: to revolutionize and improve the way the world’s most critical systems operate. Space is our next frontier, but it already has a huge impact on daily life due to the colossal amount of data that comes from satellites,” says Ben Lamm, Founder of Hypergiant.
He mentions that turning raw data into valuable intelligence is challenging. That is where Hypergiant has applied advanced ML/AI capabilities to clean, interpret and understand the data and then to use AI for predictive purposes. “When we think of our role in the space industry, we see ourselves as partners with companies and organizations that use satellite data to drive improvements on earth and beyond,” mentions Betzer. Hypergiant’s HyperDrive enterprise AI platform facilitates developing ML models and deploying them into production. “Right now, data science teams build on average two models per year. At that pace, we will never be able to scale AI solutions quickly enough to meet industry challenges and demand,” states Betzer. With the platform, Hypergiant intends to speed up the model development-to-production pipeline and drive broad-scale improvements in ML model efficiency and efficacy. Hypergiant has a unique pipeline approach to solving the needs of customers that happens in a phased approach.
Mohammed Farooq, CTO and Chairman and Ben Lamm, Founder
First, the company begins with an analysis of current business needs and user pain points, but then they like to dive deeper to understand how solutions can be built for delivering long term value to the enterprise. “The goal with this is resiliency: we want the AI/ML solutions to provide continuous value as organizations scale and digitally transform,” says Betzer. Once the exploratory phase is complete, Hypergiant engages its agile design and development process to implement the customer’s solution, all while staying aligned with legacy system integration requirements, data governance, and business KPIs. The company continuously gets user and stakeholder feedback during this process, so when they launch the final product, it will be compelling for end-users and deliver a strong ROI to the business. At the same time, Hypergiant builds custom AI solutions for a wide variety of customers, including those in space, defense and critical infrastructure with customers like Schlumberger, Sumitomo, the United States Department of Defense, and more.
The goal with this is resiliency: we want the AI/ML solutions to provide continuous value as organizations scale and digitally transform
What differentiates Hypergiant is its team and the culture that they have built. “We hire the best talent and work with the best companies. It’s like baking a cake: the final product is only a result of good ingredients. Everyone can make a box cake but a box cake ultimately doesn’t taste good. To make a great cake, you need all the best ingredients: talent, opportunity, partners, challenging goals, time and committed financial plans,” says Betzera. Hypergiant’s culture is bold, curious, fun and intent on setting and delivering the best, most interesting products they can. “We love culture. In fact, one of our early hires was a VP of Culture because we wanted to set the precedent for what it means to be part of a company like Hypergiant.”.
Hypergiant’s next big focus is on launching HyperDrive as a pivotal aspect of its business. “HyperDrive is an AI platform with managed data science workspaces and integrated workflows supporting the complete ML model lifecycle. This matters in Space Tech because we need to utilize the best in AL/ML to achieve our objectives: life on Mars, a space base on the moon, stronger satellite defense capacity, etc.,” shares Mohammed Farooq, CTO and Chairman of Hypergiant. The company believes that as they help scale data science opportunities to make AI models faster and continue to work with partners to offer best in class solutions for space related challenges, they will continue to grow in this segment and bring solutions to the market that are exciting and important.