Perspectives, not platitudes.

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.

Scale Studio Flash Updates analyze a representative sample of enterprise software startups to measure industry growth rates and the health of the SaaS market. The most recent updates were Q122, 2022 Whisper Numbers, Q421, Q321, and Q221. 
 
 Note that for this update — due to recent market fluctuations — we spent some additional time acquiring a broader sample than in previous editions of our Flash Updates. 

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. 

This post walks through the data and methodology behind our growth and burn multiple benchmarks, summarizing some of the key decisions we made in calculating them and providing some benchmark tables that might be useful for venture-backed software startups.

Responding to the flow of venture advice

A founder's tool to compare growth and burn across two years relative to similar-sized SaaS comps

Writing this content is a desk worker’s low-skill labor, demanding little skill but lots of time. (The quality of GMail autocomplete, introduced in 2018, illustrates just how repetitive business writing is.) It’s this attractive target that makes Natural Language Generation (“NLG”) products so exciting, because this new technology has finally grokked the patterns interwoven in our prose.
 
 NLG products are newly feasible, enabled by linguistic “transformer” models like GPT-3 from OpenAI and Jurassic-1 from AI21 Labs.

Scale Studio Flash Updates analyze a representative sample of enterprise software startups to measure industry growth rates and the health of the SaaS market. The most recent updates were the 2022 Whisper Numbers, Q421, Q321, and Q221.

Though usage-based models are not new—having first been championed by AWS (2005) and Twilio (2008) — there’s been a notable increase in their adoption in recent years. This trend continues to accelerate as the landscape for usage-based models quickly evolves. Scale's Max Abram on the next frontier of Usage Based Billing Infrastructure.

We are excited to announce that we have led the Series B in Dusty Robotics, which is building autonomous robots (or field printers) that assist in automating the layout process for mid- to large-scale construction projects.

Product-Led Growth is rightly the go-to sales motion for startups tackling large addressable markets where your product can effectively do the early selling. As the first sales leadership hire at Esper, where we tackled category creation around “DevOps for Devices”, we decided to develop multiple sales motions far earlier than conventional wisdom says you should.

This eBook distills 20 years of SaaS metrics in to one, definitive guide complete with benchmarks of growth, efficiency, churn, and burn by revenue band, and calculations to use at different stages of startup growth.

Scale partner Eric Anderson observes that for software startups, distribution is often more important than unique technology.

Andy Vitus on our investment in synthetic data leader Datagen.