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Evangelos Simoudis, Founder and Managing Director, Synapse PartnersThe exploding worldwide interest in generative AI is bringing broad attention to AI. I started working in the field in the early eighties and over the years I have experienced its ups and downs in various capacities. But through the years I haven’t lost my optimism that AI can be a game-changer for the enterprises. Today organizations of all sizes are starting to imagine, or reimagine, how their business processes and business models can benefit from the incorporation of AI. And while there is growing discussion about the negative impact of AI, be it in the loss of jobs, the increase in misinformation that can lead to social upheaval, and several other ills that are predicted to be the result of AI’s broad application, we view this as an era that will result in many important startups.
Synapse Partners was founded in 2016 with the singular focus on investing in early-stage startups that develop horizontal or vertical enterprise software AI applications. We are convinced that AI will impact the enterprise in the same way as cloud computing and a few other technologies have already done. The transformative innovations will be created by startups that will use AI to automate mundane tasks, increase the speed and accuracy of work typically performed by humans, enhance entire business processes and even enable us to reimagine them. And that was before we were even thinking about the opportunities that generative AI creates. Having firsthand experience with building intelligent applications for the enterprise, we also recognized that our portfolio companies will require “patient capital” and a firm that is able to provide them with insight relating to these applications in addition to capital.
To be in the position to provide value for as long as we remain investors in a company we needed to form a team that understands AI and appreciates its role in the enterprise. We augmented this team with an enterprise advisory board and an AI advisory board. Our firm’s enterprise advisory board consists of a small group of enterprise executives that provides us with ideas about strategic enterprise problems that need to be addressed. They inform us of the parts of the enterprise that have a problem, e.g., marketing, manufacturing, etc., who will pay for the solution, and oftentimes even the characteristics the solution must have. Once we invest, this group also helps the portfolio company with introductions to potential customers. We devote significant time to the interactions with the members of this board. We are convinced that to understand a problem, that gives rise to an investment thesis which results in several investments, we need the perspective of more than one member and that perspective comes by interacting with them at their place of work rather than just a meal. These long-term and in depth interactions resulting in investment theses lead to understanding ground mobility, and using AI to automate data engineering and model deployment.
Our firm’s AI advisory board includes AI experts that help us assess the quality of each prospective investment’s AI technology and explain if it provides significant barriers to entry. They also help us assess the team’s technical competence to solve the problem at scale. More than once we came to realize that what worked well in early versions of a startup’s software didn’t ultimately scale. This is a problem encountered in enterprise AI systems as large data sets and/or complex knowledge bases need to be used by the application to either build and update a model or perform inferencing to arrive at the derived outcomes.
" Having firsthand experience with building intelligent applications for the enterprise, we also recognized that our portfolio companies will require “patient capital” and a firm that is able to provide them with insight relating to these applications in addition to capital "
AI is woven deeply into our firm. In addition to the input from our advisory groups which adds to our perspective in the field, we utilize analyses and predictions from the proprietary databases of startups and founders we maintain and curate to refine our investment theses, identify potential investment opportunities, and understand a sector’s competitive landscape. For example, we track over two thousand startups developing mobility-related AI solutions. We perform extensive data engineering on these databases, creating a variety of ratios, derivatives, and other derived attributes, to help us generate the “signal” we need to determine if a startup possesses a special quality or characteristic that will cause us to pay more attention and try to participate in its funding round.
We invest in startup teams from the US, Europe, and Israel with strong AI competence that fit our investment theses. We identify these startups through our outreach efforts using the “signal” we get by exploiting our databases. Like all venture firms we also receive a significant number of unsolicited investment proposals from our advisory boards and our broader network.
Machine learning has become synonymous with AI these days, and many of our portfolio companies excel in it. Portfolio companies like Humanising Autonomy or Awake Mobility have access to proprietary data, or proprietary domain knowledge, that can be used to train AI models, or even customize open-source models with proprietary data by retraining them using transfer learning. But we have also funded companies, such as Divergent3D or Safegraph, that solve important enterprise problems using advanced reasoning and planning techniques often by combining it with machine learning.
These days, like every other investor, we spend significant time evaluating investment opportunities in startups that develop generative AI solutions for the enterprise. We are focusing on horizontal solutions focusing on two broad areas. First, applications that can help the enterprise take advantage of generative AI and validate the answers produced by these systems. Early examples of generative AI applications and the Large Language Models at their core showed us that these systems are engineering marvels that were developed with painstaking trial-and-error process that will need to be facilitated and expedited. Second, applications that assist specialists in their work increasing their productivity while decreasing the cost of the output. Our firm’s corporate advisory work pointed us to investing in automated assistants to support the entire software engineering lifecycle, as well as the customer support lifecycle. But there are several other business processes that can benefit from generative AI-based assistants.
AI is experiencing another spring. Everyone’s excitement runs high because of the performance exhibited by recently released generative AI systems. But there are many more reasons to feel excited about the potential of many other AI system types in the enterprise. Our team continues to aggressively look for the startups that take advantage of these opportunities and show them why Synapse Partners should be one of their top firms to help them succeed in their entrepreneurial endeavors.
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