Welcomes Elizabeth Samara-Rubio as its Chief Business Officer and Prepares for Scale

Krishna Rangasayee

At we have had a whirlwind of successes this year, following our September product release of Palette Edgematic to democratize AI and ML for anyone, the company’s August MLPerf results surpassing NVIDIA in computer vision performance for a second time, as well as the launch of our Partner Program and additional capital raised in June. We continue to push the boundaries of edge AI computing, developing high-performance solutions that cater to a wide range of industries. 

Much of our traction this year has made it abundantly clear that we have achieved product market fit with our purpose-built edge ML solution. With the appointment of Elizabeth Samara-Rubio as Chief Business Officer, is now poised to scale to meet the market opportunity ahead. Elizabeth’s experience and leadership will help us strengthen our operational foundation as we continue to meet customer demand and further advance our footprint in the market. As soon as I met Elizabeth it became clear very quickly that her experience and expertise with computer vision, ML, SW, and embedded experience along with her specialization in driving and managing all aspects of GTM and business management over various companies of size and stage was an ideal fit for

Elizabeth is an entrepreneurial executive with a demonstrated history in driving double-digit, top-line growth in developing and scaling routes to market for products and services in AI/ML, high-tech, manufacturing, and distributed energy. Her digital transformation leadership across product management, business development, software development, hardware engineering, system integration, field service, and sales will accelerate our ability to execute. We are incredibly lucky to have her on board and are looking brightly into the future.

I sat down with Elizabeth to get her thoughts on the market, why and what she hopes to accomplish. Please read on to learn more.

Krishna: With such vast domain expertise in the embedded edge space, what are your thoughts on the industry landscape? What are some of the biggest challenges end users are facing today?

Elizabeth: The industry has always explored the use of computer vision systems and mechanisms to enhance various aspects such as anomaly detection for improving product quality, optimizing production processes, and even surveillance, particularly in applications like retail and manufacturing. While this pursuit is commendable, the ultimate driving force lies in automation. The most effective automation is one that collaborates with humans. If I were to describe the direction the industry is heading, it would be towards ‘collaborative intelligence.’ As AI becomes more integrated at the edge, closer to human interactions, we are introducing AI as an assistant to human tasks. The ideal outcome is a seamless collaboration between AI and humans, and this is shaping the industry’s perspective.

However, the journey towards this goal comes with significant challenges. These include cost considerations, the readiness of customers to adopt AI at the edge, and access to the data required to create necessary datasets. Additionally, managing numerous models at the edge requires robust governance. Overcoming these challenges in deploying edge models necessitates a strategy like what has been doing with edge AI computing, we define the necessary models and systems required to run at the edge tailored to their specific tasks, conduct inference closer to the user, and this proximity to sensitive information makes privacy and security as crucial as cost and efficiency.

Krishna: We are a lean team, what makes you choose a startup versus a larger company for your next venture?

Elizabeth: I joined because of the promise of intelligent edge technology and its potential to assist humans, whether in a professional or personal context. This vision revolves around optimizing the footprint, managing costs, and improving efficiency, all while maintaining a strong commitment to responsible development. As I got to know the team under Krishna’s leadership during my decision-making process, I became convinced that I couldn’t find a more talented group to help us achieve our goals in the way I envision. With a startup’s inherent bias for action, speed is a critical factor. When discussing the cloud versus edge debate, I often say it comes down to a comparison of cloud speed versus edge speed, and I’m confident that we can operate at the faster pace of the edge.

Krishna: What makes you most excited about joining

Elizabeth: At I see an opportunity to take edge AI/ML to ubiquitous use; integrated into the activities and environments where people live and work. The team members I have met are experts in their domain with a passion to create a simple to use platform for customers to build, deploy, and scale applications at the edge. Together, we will fortify a relentless focus on our customers’ and partners’ journey to reimagine their businesses and processes with edge AI.

Krishna: You’ve only just started and will certainly be getting more up to speed over the coming weeks and months, but as you see it today, what is SiMa’s primary differentiator from the customer point of view?

Elizabeth:’s effortless methodology of hardware and software makes it a no-brainer for integration and practical for scaling AI/ML applications at the edge. In addition to our technology, our commitment to our customers will be a standout as we dive deep into their requirements and barriers to scale, escalating issues early and frequently, and committing to create the change that customers need to achieve their goals.

Krishna: Tell us a little about your leadership philosophy and how you will plan to leverage your learning as an experienced executive from companies of all sizes?

Elizabeth: My philosophy always starts with the customer. Specifically, we aim to become partners with our customers. We begin by asking questions such as where they want to go, why they seek to achieve those outcomes, and where they currently stand. With these answers, we determine how we can assist the customer in reaching their goals. This customer-centric approach is our number one priority and serves as our north star.

One of the core reasons why this philosophy is so important is that it positions us to lead rather than follow. By focusing solely on outperforming the competition, the conversation can eventually become one of imitation. However, by staying committed to customer outcomes, we have an open and clear canvas to define what is achievable and thereby lead the industry.

My second principle involves being comfortable with discussions about what is working and what is not. We fully expect team members to say, ‘I’ll start this, but I’ll stop doing something else.’ This process is called prioritization, as not all tasks are of equal importance. I expect the best from every talented individual on the team every day, and the only way to achieve this is by setting clear priorities. This enables team members to focus on what is most crucial for

Third, trust is paramount. It is not only essential for the development of talent but also crucial for moving swiftly. Team members need to know that when they make decisions, there are either two-way door decisions, where they are fully trusted in their roles to execute, with the expectation of learning, accomplishing, and achieving, or one-way door decisions, which are significant and merit discussion. However, these one-way door decisions should be few in number.

If we aim to lead, we must move quickly. And for us to move quickly, trust among team members is imperative, as it translates into action.”

Krishna: For SiMa’s size and stage, what’s really important to focus on right now?

Elizabeth: We need to commit to delivering results to our customers, and this starts with our dedication to asking tough questions early in our conversations with them. It’s essential that we anticipate potential challenges and barriers to adopting SiMa, such as identifying significant obstacles or ‘big rocks.’ In my experience, getting the technology right is typically not a barrier to scalability. Instead, the primary hurdle, especially for a company of our size, lies on the commercial side. We need to ensure that we are targeting the right customers who are prepared for what we offer. This is our first priority—asking the right questions when engaging with customers and making the necessary hard decisions.

The second aspect involves fostering strong collaboration within our team. In a startup, we are all deep domain specialists, but we are also versatile and adept at contributing in various areas. While this is an advantage, it can sometimes lead to difficulties in making tough decisions about what we should stop doing. With a lean team, we must be deliberate in our choices. Sometimes, we need to create space by relinquishing certain tasks to focus on more critical and essential endeavors.

Lastly, trust is paramount in a startup. As we navigate the fast-paced world of startups, we will inevitably encounter obstacles. Trust is what helps us tackle these challenges together and emerge on the other side stronger. This is a common experience for many companies, but it’s especially critical for startups. Trust is the key to overcoming growing pains and moving forward together.

I think I speak for everyone when I say we are all very excited to have you join the team. I have no doubts that you will be instrumental in paving a pathway of operational success as we continue to scale , and take the embedded edge AI industry head on.