The $200 million vehicle is larger than its prior two funds. Its raise puts Amplify in crowded company, as many venture firms have raised funds of increasing scale in recent years.
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The Menlo Park-based venture group has invested in companies like Fastly, Cask, and Keen.
When the firm announced that it raised the new $200 million vehicle, Crunchbase News reached out to the firm to get a grip on why it had raised more this time around.
Amplify’s Sunil Dhaliwal responded to our casual set of questions:
Crunchbase News: Amplify’s fund sizes have consistently grown ($50M to $125M to now $200M), something that we’ve seen from a number of firms. Why does Amplify need to add more to Fund II than it raised in Fund I for Fund III? Also, how does its rising capital base change how the firm invests (larger checks, more frequent checks, longer pro-rata interest into later rounds, etc) and operates (larger staff, broader carry distribution, etc)?
Sunil Dhaliwal: Amplify’s fund size has stayed pretty consistent on a per-partner basis. Fund 1 was raised with one investing partner, Fund 2 was raised with two investing partners, and Fund 3 was raised with four investing partners. We’ve grown our team to ensure we have a critical mass of great enterprise investors who surround our founders with domain-specific expertise and overlapping networks of connections.
We’re not meaningfully changing our investment approach—we continue to back technical founders innovating in Machine Intelligence and Computer Science from Startup to Series A. The larger Fund III also allows us to lead Series A rounds for great companies who need to raise $10 million (or more…) for their business, which wasn’t feasible at our previous fund size.
Also, as companies stay private longer, and as we cross the ten-year mark in the current tech bull market, we want our founders to know that we have the capital to support them through any downturns, and through as many rounds as needed, on the way to their eventual exits.
Crunchbase News: Does the firm have a favorite example of what companies that “pioneer new applications of machine learning and those pushing the frontier of modern computing?” 1 Machine learning is a pretty common phrase used among modern software startups, to the point of it seeming common, making it hard to tell who is full of shit, and who is building something materially interesting.
Sunil Dhaliwal: We definitely agree with the meta-point. We see so much “AI-washing” of traditional software businesses that we can get numb to the term after a while. However, we’ve been investing in AI since 2014 and our team and network has a lot of history here.
Our first investment in the space, Enlitic, continues to pioneer the application of Deep Learning to augment and improve clinical radiology. Last year, they beat out 250 companies to win a one million euro prize for breakthrough applications of deep learning in medicine. You can read that news here.
Primer.ai is another amazing company. They use natural language processing to aggregate and synthesize disparate text, from multiple sources and languages, into a common form of meaningful insight and intelligence. They’ve already scored huge deployments among both commercial and government customers.
Covariant.ai is a brilliant team of technologist from UC Berkeley and Open AI who are among the world’s foremost experts in Reinforcement Learning. They are applying RL to teach industrial robots to “learn” so that they can do more than simply execute the rote tasks that humans must painstakingly specify for them.
Crunchbase News: How many investing partners do you have now, and what is your average check size?
We are typically investing $500,000 to $10 million as lead investors in startup through Series A financings with significant follow-on capital available to support our companies throughout their life cycle.
Crunchbase News: What are your thoughts on the growth of pre-seed firms and investments (for example: positive/negative/symptom of a bubble/Series Seed is now just Series A and pre-seed is seed/etc)? Amplify’s post notes “Series Seed” as one of its investing categories, so I presume the firm has a check floor (re: size).
Sunil Dhaliwal: We haven’t spent our time worrying about minimum check sizes as we tend to be more focused on identifying the right founders, solving the right problems, and backing teams at the earliest possible stage. Moreover, we don’t get too caught up in the semantics of what to call a particular round as the trend of ‘finely slicing’ the nomenclature around these rounds is probably more about small funds trying to find ways to carve out their niche rather than an actual change in the ecosystem.
Amplify continues to be the first-check investor in many of our companies, often investing behind nothing more than a founder and an idea, with no team in place and no code written. For example, our first investment in Gremlin was $500,000 out of Fund II to get Kolton Andrus and Matt Fornaciari started from ground zero. We later followed-on with a larger seed financing before ultimately bringing in Index Ventures to lead the Series A.
And that’s a wrap. If you find this sort of interview useful, let us know.
That line comes from Amplify itself.↩
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