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PLTR - Palantir Technologies


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This is a pretty controversial co in the field of big data. They started out with defense work, but now more then 50% of their revenue comes from commercial customers. In a way, it is a bit like the well known defense contractors I own. Their main moat might be they they are willing wo do work, that other’s won’t touch. I am not sure if their government work gives them an edge with commercial work or puts them as a disadvantage.

Here is an S1 tear down:

https://mattturck.com/palantir/

 

It’s highly valued at around 15x EV/revenue run rate. Losses have been considerable , but operating results are improving and they actually generated an operating profit (ex stock option expenses) in H1 2020.

 

This will go in my watch list for the time being.

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I got in at $9.

 

This company effectively sells what IBM has been trying to sell for the past 10 years (Watson, etc), but in contrast to IBM, it seems they actually have a useful product.

 

Transitioning from gov’t/military to private sector clients will be crucial.

 

I didn’t see anything compelling in the NY Mag article other than they have an aggressive bootstrap mentality and focus on ensuring they create a good UI. These are positives IMO.

 

Valuing this as equivalent to a run of the mill defense contractor is laughable.

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I got in at $9.

 

This company effectively sells what IBM has been trying to sell for the past 10 years (Watson, etc), but in contrast to IBM, it seems they actually have a useful product.

 

Transitioning from gov’t/military to private sector clients will be crucial.

 

I didn’t see anything compelling in the NY Mag article other than they have an aggressive bootstrap mentality and focus on ensuring they create a good UI. These are positives IMO.

 

Valuing this as equivalent to a run of the mill defense contractor is laughable.

 

I will disagree with the comparative usefulness quote. Both of them are equally useless (or only sometimes useful). Marketing in these cases always wins. And Palantir is good marketing machine of Silicon Valley and has a decent chance of success despite the shortcomings. No opinion on valuation, do not know enough about potential TAM and their technology stack. For specialized field like data mining in defense this quote from the nymagzine is spot on -

 

“Here’s the dirty secret of all of these data-analytics solutions,” a former Pentagon research manager told me. “They all claim to take these disparate data sources and put them together and then discover these amazing correlations between variables. But the problem is that all of these data sets are terrible. They’re dirty.” Many types of information, after all, are gathered and processed by humans. It may be entered inconsistently or provided in wildly different formats or riddled with inaccuracies. It’s messy, like the real world it reflects and records, and it doesn’t always fit into software with any sort of mathematical precision."

 

I can tell you this is identical to amazing promises made by software tools in pharma-biotech. Since human genome was sequenced in 2000, claims abound that software with AI capabilities will put data from genetics, protein, RNA, cytokines, metabolites etc together and provide insights in an automated fashion. Nothing like that has happened so far. But of-course many companies (or their management) have made money selling the dream during this time.

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Long AYX.

 

I got in at $9.

 

This company effectively sells what IBM has been trying to sell for the past 10 years (Watson, etc), but in contrast to IBM, it seems they actually have a useful product.

 

Transitioning from gov’t/military to private sector clients will be crucial.

 

I didn’t see anything compelling in the NY Mag article other than they have an aggressive bootstrap mentality and focus on ensuring they create a good UI. These are positives IMO.

 

Valuing this as equivalent to a run of the mill defense contractor is laughable.

 

I will disagree with the comparative usefulness quote. Both of them are equally useless (or only sometimes useful). Marketing in these cases always wins. And Palantir is good marketing machine of Silicon Valley and has a decent chance of success despite the shortcomings. No opinion on valuation, do not know enough about potential TAM and their technology stack. For specialized field like data mining in defense this quote from the nymagzine is spot on -

 

“Here’s the dirty secret of all of these data-analytics solutions,” a former Pentagon research manager told me. “They all claim to take these disparate data sources and put them together and then discover these amazing correlations between variables. But the problem is that all of these data sets are terrible. They’re dirty.” Many types of information, after all, are gathered and processed by humans. It may be entered inconsistently or provided in wildly different formats or riddled with inaccuracies. It’s messy, like the real world it reflects and records, and it doesn’t always fit into software with any sort of mathematical precision."

 

I can tell you this is identical to amazing promises made by software tools in pharma-biotech. Since human genome was sequenced in 2000, claims abound that software with AI capabilities will put data from genetics, protein, RNA, cytokines, metabolites etc together and provide insights in an automated fashion. Nothing like that has happened so far. But of-course many companies (or their management) have made money selling the dream during this time.

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I got in at $9.

 

This company effectively sells what IBM has been trying to sell for the past 10 years (Watson, etc), but in contrast to IBM, it seems they actually have a useful product.

 

Transitioning from gov’t/military to private sector clients will be crucial.

 

I didn’t see anything compelling in the NY Mag article other than they have an aggressive bootstrap mentality and focus on ensuring they create a good UI. These are positives IMO.

 

Valuing this as equivalent to a run of the mill defense contractor is laughable.

 

I will disagree with the comparative usefulness quote. Both of them are equally useless (or only sometimes useful). Marketing in these cases always wins. And Palantir is good marketing machine of Silicon Valley and has a decent chance of success despite the shortcomings. No opinion on valuation, do not know enough about potential TAM and their technology stack. For specialized field like data mining in defense this quote from the nymagzine is spot on -

 

“Here’s the dirty secret of all of these data-analytics solutions,” a former Pentagon research manager told me. “They all claim to take these disparate data sources and put them together and then discover these amazing correlations between variables. But the problem is that all of these data sets are terrible. They’re dirty.” Many types of information, after all, are gathered and processed by humans. It may be entered inconsistently or provided in wildly different formats or riddled with inaccuracies. It’s messy, like the real world it reflects and records, and it doesn’t always fit into software with any sort of mathematical precision."

 

I can tell you this is identical to amazing promises made by software tools in pharma-biotech. Since human genome was sequenced in 2000, claims abound that software with AI capabilities will put data from genetics, protein, RNA, cytokines, metabolites etc together and provide insights in an automated fashion. Nothing like that has happened so far. But of-course many companies (or their management) have made money selling the dream during this time.

 

Sure, but can you point to anyone who has truly "clean" data set inputs? It's one thing to point out an issue with a specific approach. But this is more of an industry wide issue, and I think you fairly point this out. Regardless of issues (in the data industry), every company (customer) is looking for an edge in this hyper competitive business world; and big data is on the forefront of this.

 

 

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Real world data is always going to be messy. That’s the inherent barrier to competition in this space and why IBM failed. PLTR has failed and fails often too, but their successes are telling. I count many more than IBM.

 

PLTR can also aggregate and work with disparate sources/interfaces in a single org: AWS, Azure, IBM cloud, proprietary cloud, hybrid cloud, etc.

 

They are effectively a consulting biz with a wide and growing moat.

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Currently doing DD on this, particularly on valuation versus reality of their eventual potential market, technology edge etc. Here are my concerns currently that I need to convince myself out of.

 

Sure, but can you point to anyone who has truly "clean" data set inputs? It's one thing to point out an issue with a specific approach. But this is more of an industry wide issue, and I think you fairly point this out. Regardless of issues (in the data industry), every company (customer) is looking for an edge in this hyper competitive business world; and big data is on the forefront of this.

 

This is exactly why scaling any operation here is hard. Proprietary datasets that are not clean, are relatively quite small as compared to what google or facebook collects, and are not a good fit for data hungry algorithms. Unlike Google for instance that can combine massive datasets because there are no legal hurdles, Palantir cannot use US govt (say CIA) data and merge it with UK's MI5 data. Even within US there are laws governing what govt can collect and merge that are hurdles. So it is not a pure play consumer tech growth company. Valuation now will matter because it may never get to the same scale/size. As for big data as edge there is a joke someone posted a while back -

 

"Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it..."

 

Real world data is always going to be messy. That’s the inherent barrier to competition in this space and why IBM failed. PLTR has failed and fails often too, but their successes are telling. I count many more than IBM.

 

I would say IBM did not fail, infact even though they have average product they still had govt contracts and are the incumbent. Thus the barrier was for Palantir not IBM. I would definitely give it to Palantir for shaking the incumbency (al la SpaceX). However, road forward is not clear cut for me because unlike SpaceX where we know they are ahead in technology, I have no way to judge Palantir's edge regarding their tech stack.

 

PLTR can also aggregate and work with disparate sources/interfaces in a single org: AWS, Azure, IBM cloud, proprietary cloud, hybrid cloud, etc.

 

All modern tools do that and this is not an edge that IBM cannot replicate. API's are fairly well understood for most of the connectors and if anything IBM has an edge with more hands on deck to keep adding new connectors. See Tableau's list for example -

 

https://help.tableau.com/current/pro/desktop/en-us/exampleconnections_overview.htm

 

They are effectively a consulting biz with a wide and growing moat.

 

Yeah, I agree. But to me software with consulting has limited market size and scalability, especially if the focus is narrow right now to govt contracts. IBM is into similar business but has tenticles into a lot of market segments (banking/financials, govt, shipping and logistics, healthcare etc etc). Palantir already failed trying to gain traction in a bigger financial market. The question is how much more is the market size for them and what does current valuation already reflect.

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Currently doing DD on this, particularly on valuation versus reality of their eventual potential market, technology edge etc. Here are my concerns currently that I need to convince myself out of.

 

Sure, but can you point to anyone who has truly "clean" data set inputs? It's one thing to point out an issue with a specific approach. But this is more of an industry wide issue, and I think you fairly point this out. Regardless of issues (in the data industry), every company (customer) is looking for an edge in this hyper competitive business world; and big data is on the forefront of this.

 

This is exactly why scaling any operation here is hard. Proprietary datasets that are not clean, are relatively quite small as compared to what google or facebook collects, and are not a good fit for data hungry algorithms. Unlike Google for instance that can combine massive datasets because there are no legal hurdles, Palantir cannot use US govt (say CIA) data and merge it with UK's MI5 data. Even within US there are laws governing what govt can collect and merge that are hurdles. So it is not a pure play consumer tech growth company. Valuation now will matter because it may never get to the same scale/size. As for big data as edge there is a joke someone posted a while back -

 

"Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it..."

 

Real world data is always going to be messy. That’s the inherent barrier to competition in this space and why IBM failed. PLTR has failed and fails often too, but their successes are telling. I count many more than IBM.

 

I would say IBM did not fail, infact even though they have average product they still had govt contracts and are the incumbent. Thus the barrier was for Palantir not IBM. I would definitely give it to Palantir for shaking the incumbency (al la SpaceX). However, road forward is not clear cut for me because unlike SpaceX where we know they are ahead in technology, I have no way to judge Palantir's edge regarding their tech stack.

 

PLTR can also aggregate and work with disparate sources/interfaces in a single org: AWS, Azure, IBM cloud, proprietary cloud, hybrid cloud, etc.

 

All modern tools do that and this is not an edge that IBM cannot replicate. API's are fairly well understood for most of the connectors and if anything IBM has an edge with more hands on deck to keep adding new connectors. See Tableau's list for example -

 

https://help.tableau.com/current/pro/desktop/en-us/exampleconnections_overview.htm

 

They are effectively a consulting biz with a wide and growing moat.

 

Yeah, I agree. But to me software with consulting has limited market size and scalability, especially if the focus is narrow right now to govt contracts. IBM is into similar business but has tenticles into a lot of market segments (banking/financials, govt, shipping and logistics, healthcare etc etc). Palantir already failed trying to gain traction in a bigger financial market. The question is how much more is the market size for them and what does current valuation already reflect.

 

"Unlike Google for instance that can combine massive datasets because there are no legal hurdles, Palantir cannot use US govt (say CIA) data and merge it with UK's MI5 data"

 

Aren't you comparing two different data sets/sectors here? If Palantir is also focusing on the commercial side then they should be able to share that data just as easily as GOOG if there is no tie to government agencies.

 

FWIW: I have a good friend who works at the NSA. I'll try to pick his brain if he has any experience with this product.

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Aren't you comparing two different data sets/sectors here? If Palantir is also focusing on the commercial side then they should be able to share that data just as easily as GOOG if there is no tie to government agencies.

 

FWIW: I have a good friend who works at the NSA. I'll try to pick his brain if he has any experience with this product.

 

Proprietary data of a commercial enterprise remains proprietary. Palantir may bring its own dataset to enrich the data but they can't just take data of their commercial customers and blend it.

 

FWIW, Palantir has been agitating a lot of customers with their price structure and some of its customers have been moving away to alternatives that might be lower on the maturity/sophistication curve but good enough to get the work done.

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  • 1 month later...

https://seekingalpha.com/news/3633300-palantirplus-19-on-potential-biden-victory-hedgeye-adds-to-best-idea-short-list

 

Hedgeye sees more than a 50% downside for Palantir (NYSE:PLTR) over the next 6-12 months due to the lack of enterprise adoption even after 17 years in business and three relaunches.

 

Gotta love Hedgeye with their groundbreaking "analysis"...

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Thats not their analysis, that is the Seeking Alpha boilerplate summary. Their research is behind a paywall and much more extensive than that. Not that it is always right. They like to peddle short positions the same way Einhorn does. Research is very solid, but often directionally wrong.

 

https://app.hedgeye.com/insights/79736-nvta-the-amazon-of-genetic-testing-call-12-12-2pm-et

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Thats not their analysis, that is the Seeking Alpha boilerplate summary. Their research is behind a paywall and much more extensive than that. Not that it is always right. They like to peddle short positions the same way Einhorn does. Research is very solid, but often directionally wrong.

 

https://app.hedgeye.com/insights/79736-nvta-the-amazon-of-genetic-testing-call-12-12-2pm-et

 

That’s all fine regarding NVTA, but what has this to do with PLTR? The latter seems to do rather well lately.

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Its generally helpful to have an idea who is in the market on either side of the trade and what their investment rationale is. Once the brainiacs and valuation guys start piling on the short side, things tend to get bullish. Its pattern recognition. Happens quite frequently. Usually its an opportunity trade. Just like with NVTA. PTON shortly after the IPO saw the same phenomena, both within the last 12 months. Lots of parallels to PLTR. With these kind of things the narrative is often much more important than the fundamentals.

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https://www.bloomberg.com/news/articles/2017-11-29/shake-shack-short-sellers-see-trouble-in-long-lines-for-burgers

 

This was another good one from Hedgeye a few years ago.

 

“They’re never going to do better than they did in New York,” said Howard Penney, an analyst at Hedgeye Risk Management. “There’s plenty of places to get a burger. There’s nothing unique about the model.”
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  • 3 weeks later...

Embarrassing , but I never bought the stock despite finding some attractive attributes when I looked at this. I should have listened to the voices from the peanut gallery that were screaming “ Swing, you bum!”. Or as someone said on Twitter: “ Do you want to look at numbers or do you want to make money?”

 

I guess the voting machine wins over weighing machines this year.

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I guess the voting machine wins over weighing machines this year.

 

So when are we gonna have Internet crash #2?

Oh wait, it should be in 2021 so it would rhyme with 2001.  8)

 

No profits stocks going up every day - check. No sales stocks going up every day - check. Overlevered BK stocks going up every day - check. Everyone making 100%+ returns on calls - check. People buying private/angel cos without financials - check. People buying SPACs at huge prices - check. People buying crypto for X00% returns - check.

 

I know it's wrong thread.  8)

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Hi Andrew Left. Thanks for setting up more shorts to get slaughtered.

 

Jokes aside a $5-10 pullback wouldn't be out of this world considering the s/t move, which if I had to wager is all Andrew is playing here. He often just likes to put a bow of unnecessary research around his calls when in reality he's just trading; all he needs to do is just emulate Tepper's "I thought it would go up" response for SNAP, and that would be sufficient enough for me, but I guess he has a flair for the dramatic...

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Anyone know how the folks over at hedgeye are doing ?

 

Ha. I pay for one of their services and get value from it in tracking macro markets. But I am sometimes bemused by their analyst conclusions on individual stocks. They reversed on Peloton and Zoom after each had gone up multiples.

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Anyone know how the folks over at hedgeye are doing ?

 

Ha. I pay for one of their services and get value from it in tracking macro markets. But I am sometimes bemused by their analyst conclusions on individual stocks. They reversed on Peloton and Zoom after each had gone up multiples.

 

Andrew Left also was short PTON—said it was worth $5 when it was $30. Didn’t work out too well. His short target for PLTR is $20 which is not all that bearish considering it’s 2x first post direct listing price...

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