Looking at a company and would like some expert input

[Brian]

UPDATE 4/27/20 – Thom pointed out that my initial notes below apply to GuruMD, not Guru by MSBAI (sorry for the mixup). My thoughts on MSBAI are posted further down in the replies to this thread.

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Original message:

Hey Thom,

First off, I’ll start by saying that the telemedicine / self-health space is definitely one I’ve looked at and invested in. I invested in Circle Medical’s round on WeFunder back at the end of 2018, and other home health companies such as Innamed on Republic (blood testing at home) and Vivoo.

Circle Health is probably the closest analogy here to GuruMD, although it’s more of an AI-based solution for primary care (in San Francisco) and GuruMD seems to be targeting more of the ER and urgent care market.

The space is definitely hot/competitive – CallingDr was another campaign on StartEngine, and also mentioned emergency and urgent care.

So my biggest initial question is – what makes GuruMD unique and special in this space? What’s their unfair advantage or differentiator compared to all these other solutions that are out there?

What they cite as a “cutting-edge user experience” isn’t as convincing of a differentiator as I’d probably be looking for.

The team looks experienced, but I wouldn’t say they have any special sauce that some of these other businesses in the same industry don’t have. Seems they have relatively decent traction in their pilots (though the charts are hard to read without labels on any axes…), but I would question whether what works locally in TX/NM can operate and succeed at scale when ready.

A Big Red Flag – Company Repurchase Rights

I’ll be honest, I didn’t dive very deep into this deal, since the very first thing that caught my eye and gave me a sense of the team’s thinking is that they have company repurchase rights in the terms.

“In the event of an institutional or venture financing for $1,000,000.00 or more, the Company may repurchase the shares sold in this offering at the greater of either (i) the valuation of the Company in the institutional financing, or (ii) 110% of the original purchase price.”

I can understand the thinking of the founders in adding these terms to give themselves options in the future, but if this investment ends up being your 1/100 unicorn that does extremely well and starts taking off in terms of valuation, do you truly believe that the founding team will have the best interests of their smaller crowdfunding investors at heart?

Because of this, I view it as being a limited potential upside investment (not subject to a Black Swan type outcome, since my guess is that the founders would do whatever a large VC would ask, which would probably mean buying out early crowdfunding investors).

I’m sure the majority of the time these rights would not be exercised; however, it isn’t the “majority” of the cases I’m worried about, but that 1/100 investments that end up generating the power-law returns required to make an early-stage portfolio successful. And while investors would get perhaps even a “decent” return if they are bought out at a 2-5X+ valuation, investors would likely be missing out on the potential of the 100X+ return truly required to make it worth it.

For that reason alone, I will probably not be investing in this deal; however, it doesn’t mean it can’t still be an investment others decide to make, especially if you believe that the founding team wouldn’t exercise those rights in such a situation (but if that’s the case, why would they include it at all?). FYI – I have invested in a few SAFEs in the past that had repurchase rights, but now I scrutinize those deals much more closely and tend to avoid them for the above reasons.

Having these rights on the Common Stock/Tokens is something I haven’t seen as much…it seems to me that including these repurchase rights mis-align incentives between the founding team and early investors.

[Brian]

FYI – for me, the repurchase rights risk boils down to one quote from Peter Thiel’s book Zero to One (our book summary here). I ask this single question over and over again when screening deals as it helps to filter out a lot of potential investments:

“The biggest secret of the venture capital is that the best investment in a successful fund equals or outperforms the entire rest of the fund combined. This implies two strange rules for VC. First only invest in the companies that have the potential to return the value of the entire fund. This leads to rule number two: Because rule number one is so restrictive, there can’t be any other rules.”

If the possibility of the business repurchasing early investors puts the above at risk (having a single investment outperform the rest of the fund combined), then I tend not to invest, or at least I do it for reasons beyond just potential financial gains (e.g. I really believe in the product or founder, want to see the product in the world or use it myself, etc.).

[Brian]

OK – I took a look at the correct Guru (by MSBAI) this time. Let’s try this again.

From what I gather (took me a little while reading their page), they are essentially trying to:

1. Allow generalist engineers to run more specialist simulations
2. Allow these engineers to use High Performance Computing (HPC) for their simulations (essentially running it on supercomputers and spreading the simulation among a bunch of processing cores and/or GPUs)

Is it a good idea? Sure – enabling more generalist engineers to carry out the task of specialists would help lower overall costs for running these types of simulations and models…assuming they are done right, and that’s a big assumption. There is a reason today that specialists are typically required for these types of things.

Now, is it a practical idea? That needs some additional questions answered…

First, I’m speaking purely from an aerodynamic and thermal simulation perspective for electronics and airplanes/helicopters – I can’t provide any input really on the Energy Efficiency side. I used to run Computational Fluid Dynamics (CFD) analyses using HPC on our own supercomputer grids of 64-128 processors.

I personally think this could be useful for small businesses (and even generalists in larger corporations), but primarily for running first-pass analyses during preliminary design and while conducting trade studies. I think if you’re going to manufacture something complex like an aerodynamic fairing, you need the expertise and control of a specialist. Or you at least need the assurance that Guru is using the proper assumptions. It’s great that it abstracts some of that complexity, but a common saying is “garbage in, garbage out” – you can get any type of beautiful results, but if you didn’t set it up properly, the results will be meaningless (although they’ll still look pretty).

If I had to guess, because the CEO/Founder seems to have an in-depth aero background, I’m guessing their “AI” today is mainly taking their own knowledge and expertise and productizing that expertise via the Guru interface. One of my main concerns is that they tout “AI” as being a major part of this product, yet right now it seems neither of the founders (nor advisors) have in-depth AI experience, and I question whether you could pull it off by outsourcing that part of the product development to someone else.

Personally, I also don’t get the voice command feature – it’s either a very minor feature that they are playing up in the marketing, or I question whether they are spending time on where the real value is to be added. Maybe I’m just set in my ways and will be proven wrong, but I find it hard to imagine a room full of engineers giving simulation commands via voice.

Questions I have about the campaign page:

1. All their Letters of Support are from early 2018 – any updates since then?
2. Hard to tell if the team is full-time – both have other jobs/professions listed on their LinkedIn page
3. Who is the Artificial Intelligence expert? AI experts cost huge $$ in today’s market and I don’t see either of them with solid AI backgrounds, so I question their ability to pull of the AI part of the business
4. Maybe I don’t get the product, but I personally can’t understand why they are focusing on a voice interface – seems like more of a sales gimmick to me. Any engineer looking to run this would have some type of decent computer set up.
5. BIG questions about the pricing and unit economics, especially if they plan to target Small and Medium-Sized Businesses (SMBs). They mention $500 per simulation or $20,000 per year, but this depends on a lot of assumptions – are the solvers they are using open source or commercial? Does it depend on compute resources requested? How does protecting sensitive data / restricted data work with the cloud computing, etc. See questions below

I had some more technical questions about how the product would work, which I posted to their campaign page. Answers to these questions would help address whether it will really be as cost-effective or not as they are saying for SMBs.

Here are the questions I posted to them on their campaign page:

1. Does the company still have to own or lease the software license(s) for the software simulation package, or is that included in Guru’s cost? (e.g. if I wanted to run a FLUENT CFD simulation on 32 cores, do I need FLUENT or HPC licenses)? Or do you only use open-source solvers?
2. Do users pay based on resources used or time, or are there caps on what is included in the standard Guru subscription? e.g. if I want to run on 128 cores instead of 64 to get quicker results, am I charged a different amount?
3. While it would be ideal to say “Guru, go run this geometry at these conditions” and have it spit back results, there will always be a need for adjustments in settings, checking the grid quality, etc. Does Guru allow for these adjustments and checks along the way?
4. What about sensitive data and simulations, especially for DoD, DoE, and others who might have ITAR and other restrictions? Does Guru still allow you to run on local clusters, and does the supercomputer implementation today allow for handling sensitive (but unclassified) data?

Hope this helps! If I somehow managed to review the wrong one again, feel free to call me out 🙂

[Thom]

Hello All –

This is very humbling for me. So glad I asked. So I have confirmed that I can spot a good idea…but not necessarily a practical one. That is why I am constantly seeking advice from experts. Your reply might well have been in a different language in some parts. Fact of the matter is that I have no business investing in tech deals like this without advice.

Would like to propose that we follow this one out. Lets’ see how the questions are answered and revisit this as that happens – kind of like “the anatomy of the diligence of a CF tech investment”

If you are willing, look forward to continuing this discussion as it plays out.

De Angelis

[Brian]

Hey Thom –

Agreed – happy to keep following this one.

First update, I asked a very good friend who is probably one of the best and most thoughtful engineers that I know, and he had this to say (we didn’t exchange any thoughts at all before he wrote this, so it’s interesting to see he came to the same “garbage in, garbage out” analogy that I did):

“CAE is a garbage in, garbage out system – which is heavily reliant on engineering talent to get the context correct. You can layer on the complexities of working with many different solvers and software packages. So, the value proposition for an “AI ” system is either being totally generalized OR a specialized system for a certain type of analysis. The former doesn’t strike me as likely anytime soon. The latter is plausible.

Then I think to the market demand- why would companies not be using HPC? High upfront cost and lack of expertise is an obvious one. Lack of available resources is another – even with clear value proposition, finding resources (hires) can be tough. There could also be a place for doing repeated analysis of similar systems (think n variations of airfoil designs). Again, big companies will have the resources to do this themselves, but small to mid may not. Market size is the key question here. It will be the difference between a lifestyle company (consultancy) or a 10x+ growth to acquisition.”

Second update – the founder responded to my questions on StartEngine here. One thing Allan said that raised a few more questions about how viable this will be to sell when targeting SMBs is “2) It’s like Amazon Prime – where you purchase a Prime subscription, and then Amazon helps you buy specific products. (You purchase a GURU subscription, and then GURU orchestrates your payments to the third party ISV & cloud vendors for that job) see “GURU Orchestrates Payments”.

Thus, if I understand the unit economics and pricing correct, it sounds like you will pay the $500 per simulation or $20k per year subscription to Guru, then have to pay the normal cloud compute and HPC fees on top of that. I was thinking that they were somehow going to perhaps leverage being able to purchase compute power in bulk and then allocate it among their customers so that they could pass along savings.

This is a major potential obstacle in my opinion, as it doesn’t really solve the issue of cost of running these analyses (which can be very steep, especially for a small business); it only seems to solve the issue of resources and expertise. And if that’s the case, I wonder more if they’ll be able to get enough initial customers and sales and if they are addressing the real paint point properly.

Let’s keep an eye on this one.

[Thom]

All good. We are stronger as a community.

[Thom]

For those following this one – it appears that Guru has signed a contract with the DOD that (I think) was announced AFTER this posting. This could be a game changer? Any thoughts?