Why Investing

  1. White label AI solution seems inevitable. Just like banks collided together to make Zelle to combat Venmo, it makes sense that automakers worldwide would not be thrilled at Google, Apple, and Amazon holding such stark leadership positions in AI.
  2. Valuation is right ($5MM, needs to be below $10MM), is a SaaS business. Has a product, early revenue, and Mitsubishi contract going on.
  3. Chief scientist Bruce Wilcox seems like a legitimate heavy weight. 


1. Ssyndicate lead has >5 years investing and >1 unicorn investmentFail
2. A startup that is based in SVPass
3. Has at least 2 founders Pass 
4. Has product in the market Pass: Yes, $54k in revenue 2017
5. 6 months of continuous user growth or revenue.Pass: Revenue grew from $1k to $54k in 2016 to 2017
6. Notable investors?Fail: None that are easily identifiable.
7. Post-funding, will have 18 months of runway Pass: Yes, Raised $401k, 2017 expenses were $146k.
8. Proprietary technology?Pass
9. Network effects?
10. Economies of scale?
11. Great branding?
Fail (by default)


  1. The Engineering question
    • Bad: hard to imagine that this will be better than Google, Amazon, or Apple in the near future. 
  2. The Timing question
    • Bad (by default): not sure if this is a good time, therefore no points on this.
  3. The monopoly question
    • Good: as with the Zelle analogy, if this is truly adopted wide by card manufacturers for white label, then this could absolutely be the last non-tech affiliated AI virtual assistant solution.  
  4. The people question: 
    • Bad (by default): lots of things relying on CEO and scientist. CTO is interim. 
  5. The distribution question
    • Bad (by default): the consumer play is going to be very challenging, mainly cause AI needs to work with services. The car question could be good but would require exceptional B2B sales.
  6. The durability question
    • Good: cheap processing, AI, and SaaS have promising futures. Unless Google, Amazon, and Apple decide to suddenly white-label their software solutions, it’s very likely that a Zelle for car AI virtual assistants plays ball.
  7. The secret question: 
    • Bad (by default): perhaps that car companies will really need artificial intelligence virtual assistants, will be bad at building them, and will pay good money to have the feature in when the time comes. 

What has to go right for the startup to return money on investment:

  1. Consumers demonstrate that AI powered cars become a must-have and not just a nice to have. Upon analysis, car manufacturers decide that they both really want data, and are also not qualified to build a solution. Then SapientX must be the best option for acquisition/convergence on to a standard.
  2. Adoption of AI VA usage in the next 3-5 years must really go up. This means major advances on natural language processing. 
  3. The technology behind SapientX must be good enough to work and gain car manufacturers enough to compete on. 

What the Risks Are

  1. Leadership risk: is this CEO cut out to be a SaaS CEO? Is this scientist going to be a good CTO? Who will be the CTO?
  2. Product-market risk: Will car manufacturers collude to make a cross manufacturer artificial intelligence virtual assistant? Would they want to build their own? In addition, I should have downloaded SapientX’s mobile app and test driven it before investing. 
  3. Timing risk: what is going to be the adoption and demand elasticity of AI powered automobiles? I used Siri/Google/Alexa occasionally but the quality hasn’t wow’ed me yet.


05/28/19 (received by email):

  • Q4 Revenue: $0
  • Q4 Net Income/(Loss): ($110,546)
  • Q4 Cash Balance: $233,693
  • Full-Time Employees: 5
  • Most Recent Valuation: $5mm Pre-Money
  • “Our work with Mitsubishi continued to be delayed due to their merger activities with Nissan and Renault.”

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