3 Methods For Valuing Prerevenue Novel AI Startups

Since 2006, Ryan E. Long has been a principal attorney at Long & Associates. The Santa Monica law practice solves complex IP issues for technology/media clients to securely measure or access them.

Evaluating pre-revenue tech startups is an established process today, but are the methods used to pre-revenue businesses using new AI equally applicable? What are the challenges of implementing this in an AI development business that can quickly grow to millions of users? These questions are not academic.

This article provides specific guidance on traditional methods used to value pre-revenue startups, explores some limitations when using these methods for new AI startups, and suggests ways to mitigate risk.

Let's start with three commonly accepted ways of valuing early- or early-stage companies: valuation, venture capital, and the Berkus method. Next, we'll explore some of the challenges of implementing these methods in early-stage companies with new AI applications.

How to Earn Scorecards

AI can scale faster than other technologies, so an AI product that works in beta, or at least a viable product, may not work for millions of users.

This evaluation method tries to compare the startup with others in the market.

First, the average pre-fund valuation of other startups in the same market is determined. This benchmark is then used to compare individual startups, taking into account factors such as the strength of the management team, size of the opportunity, product/technology, competitive environment, and marketing/sales channel.

Although highly subjective, each of these items is assigned a score, similar to a grade. If the average pre-market valuation of a startup is $1 million and the various startup factors add up to 1.125, then the two numbers are multiplied to get the pre-money valuation.

Venture capital approach

The venture capital approach attempts to determine the pre-cash value of a startup by extrapolating its post-cash value. When compiling a scorecard, you need to make assumptions by comparing startups to benchmark companies in the same market.

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