Unlike SaaS, deep tech companies have a unique valuation trajectory: a sharp seed-to-Series A increase, a long plateau during R&D, and then massive step-ups post-production. This requires a bimodal investment strategy focusing on early stage and the final private round before inflection.
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For a proven, hyper-growth AI company, traditional business risks (market, operational, tech) are minimal. The sole risk for a late-stage investor is overpaying for several years of future growth that may decelerate faster than anticipated.
Unlike SaaS startups focused on finding product-market fit (market risk), deep tech ventures tackle immense technical challenges. If they succeed, they enter massive, pre-existing trillion-dollar markets like energy or shipping where demand is virtually guaranteed, eliminating market risk entirely.
Despite headlines about rapid-growth companies, the typical startup journey is slowing dramatically. The median time between Series A and B rounds is now close to 1,000 days (almost 3 years), creating a barbell market where a few companies raise quickly while the majority face a much longer path to their next milestone.
Redpoint's early-growth fund concentrates on Series B deals, entering after product-market fit is established but before explosive growth becomes apparent in the metrics. The strategy is to invest "a half step before something becomes obvious in the numbers," capturing value at a critical turning point.
AI companies raise subsequent rounds so quickly that little is de-risked between seed and Series B, yet valuations skyrocket. This dynamic forces large funds, which traditionally wait for traction, to compete at the earliest inception stage to secure a stake before prices become untenable for the risk involved.
Contrary to common belief, the earliest AI startups often command higher relative valuations than established growth-stage AI companies, whose revenue multiples are becoming more rational and comparable to public market comps.
For deep tech startups lacking traditional revenue metrics, the fundraising pitch should frame the market as inevitable if the technology works. This shifts the investor's bet from market validation to the team's ability to execute on a clear technical challenge, a more comfortable risk for specialized investors.
With trillion-dollar IPOs likely, the old model where early VCs win by having later-stage VCs "mark up" their deals is obsolete. The new math dictates that significant ownership in a category winner is immensely valuable at any stage, fundamentally changing investment strategy for the entire industry.
Traditional valuation doesn't apply to early-stage startups. A VC investment is functionally an out-of-the-money call option. VCs pay a premium for a small percentage, betting that the company's future value will grow so massively that their option expires 'in the money.' This model explains high valuations for pre-revenue companies with huge potential.
True alpha in venture capital is found at the extremes. It's either in being a "market maker" at the earliest stages by shaping a raw idea, or by writing massive, late-stage checks where few can compete. The competitive, crowded middle-stages offer less opportunity for outsized returns.
