Analysis, forecasting, and thoughts on all things venture
We believe that we are at an inflection point where stream processing will become the standard that powers user-facing analytics. The growing importance of the use cases enabled by stream processing is being met with solutions that are increasingly easy to adopt.
No one can tell exactly what 2023 will bring, but one thing is for certain: there is a sprint to efficiency with improving burn multiples and slowing revenue growth across the board. Comparing 2022 performance with 2023 plans shows the stark reality. The slowdown in ARR Growth we saw in 2022 will result in a slowdown in GAAP Revenue Growth in 2023. At the same time, startups have tightened their belts to become more efficient.
Some high-level thoughts about how CFOs of technology companies should be thinking about their annual planning ahead of 2023.
Here's the data we're sharing with our portfolio companies as they develop 2023 annual plans.
With the bulk of 2022 behind us, attention now turns to planning for 2023. The topic of conversation in every boardroom is the corresponding tradeoffs between growth and burn. Check out the tool that we built that helps you understand how you compare with other companies. Stay tuned as we’ll also be publishing our 2023 Whisper Numbers later this month.
We are closely following the momentum of these overlapping but distinct trends. And to track our own work and share some of the knowledge we’ve accumulated, we’re introducing the Scale Generative AI Index, a list of nearly 200 companies in the space and details about what they’re building. We’ll keep adding to this market map as our research progresses.
We believe that in this moment of generative AI hype, nothing is more valuable than hearing directly from entrepreneurs and product leaders building in the Generative AI space. That’s why last month we hosted a panel with a group of entrepreneurs and AI practitioners to discuss the key challenges entrepreneurs are facing when it comes to building category-defining generative AI companies.
Since our inception, Scale Venture Partners has been on a mission to invest in the best entrepreneurs and support them as they build market-leading companies. And much like the companies we invest in, the team that's assembled to help accomplish the mission is the most important asset we have. In the 2 years following the announcement of Fund VII in 2020 we've spent considerable time and effort building the team. With today's announcement of Fund VIII, we are excited to announce several new promotions, the addition of new team members, and capabilities to our Scaling Platform.
Over the last few years, building an AI startup used to require “do-it-yourself AI,” which consisted of gathering training data, labeling it, architecting complex data transformations, tuning hyperparameters, and selecting the right model. It was a herculean task, similar in complexity to the workload of the Salesforce engineer above. But in the last year or two, foundation models have emerged as a time-saving shortcut that enable entrepreneurs to do more faster. These foundation models aren’t specific to particular AI use cases, but are largely general and have something to offer almost anyone. Entrepreneurs can now decouple parts of the training data and model (which comes pre-packaged in a foundation model) from the application layer, which we at Scale call a cognitive application.
Turns out, phones are quite good payment platforms. This poses a challenge for traditional consumer payments. Debit cards, credit cards, and other legacy payment methods are making way for Apple Pay, BNPL, QR code payments, Venmo, and Zelle — and that’s just in the U.S. Outside the U.S., super apps are beating Visa and Mastercard to the punch. China is a prime example, where WeChat and AliPay process more USD equivalent volume collectively than Visa.
