Shamelessly doing some investment research. Supposed to be a generative AI tool for diligence: point it towards a dataroom and you can ask it questions about the content like a search engine.
None of my PE friends have even heard of this (except for the ones who went to Stanford since the founder is mid-20s / Stanford undergrad) but it’s pretty buzzy in the VC circlejerk so wanted to check here. Thanks all
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Well, based on the most helpful WSO content, I don't have any specific information about Hebbia. It seems like it's a tool that's gaining some traction in the VC circles, but it hasn't been mentioned in the context of the WSO threads I have access to.
However, the concept of using generative AI for due diligence is quite intriguing. It could potentially revolutionize the way we approach investment research, making the process more efficient and comprehensive.
If you're considering investing, I'd recommend doing a deep dive into the product, its capabilities, and its market reception. Also, consider the broader trends in AI and how they might impact the success of a tool like Hebbia.
Remember, the best investment decisions are informed ones. Keep digging, my friend!
Sources: What job to take if you best want to ride the generative AI wave over the next couple of decades. Serious question., HYPSM ex-Quant Fund Intern Senior career advice and opinion on the future of finance and the world, What Harvard Business School is Teaching This Tech Entrepreneur, Ken Griffin speech on how he started Citadel
It’s financial services specific document based search. It is the next generation of elasticsearch except an emerging trend is that they’re coming to market verticalized. It is good for document search but not great for multimodal search. Clean is a better solution there but not out of the box. I’m not sure how hebbia does at xlsx but maybe that counts as text search, I don’t know.
promising candidate for v2 of enterprise search with enough fine-tuned FS specificity it maybe widely useful for analysts down the line. Doing mid single digits $mm in revenue I think.
please do a product evaluation of them and report back :)
Got a demo on it, basically croaked while doing the demo and didn't work.
We decided to pass on it because it was just too buggy. And btw, I suspect ChatGPT does it better anyway (now we can upload docs using our Azure ChatGPT playground).
What was the pricing - cost and fee structure?
No
My team took a look and decided it would be smarter to just wait until an even better product is in market from an established business. The TAM for this kind of product is too big to not see some heavy hitters build a similar solution internally. Just wait 9-12 months for Azure AI Search or something similar to be even more commercialized.
Genuine question. Does anyone else feel like whenever something like this is posted, it’s just a way to promote and drive engagement without a direct pitch? For some reason that’s always the first thought in my brain.
Yeah this post totally seems like an add.
What was the pricing - cost and fee structure?
Heard that the product is shit, but riding the VC hype train trying to seem differentiated. Genuine question--why wouldn't you just use GPT document search? MSFT can probably just have similar technology built into window soon as well
Whatever happened to CTRL+F?
I think they're a great example of both the potential and issues with the market.
1) It is by far the worst SaaS product I have ever used hands down (regardless of category). That said, they are growing like crazy and have signed deals with a lot of funds. IMO this shows that whatever the reason for the demand, it's very real since people are not scared off by how bad the product is. IMO after using it and meeting some of the folks there it got me a lot more bullish on the space because it was remarkable to me how you could get so much revenue with such a miserable product. These problems are IMO fixable -- what I used was just insanely buggy.
2) That said, for right now I think the nature of the demand is not actually to do work. I suspect that its valuable for institutions to buy it as a marketing tool and for this reason alone it easily justifies its cost so long as they trend towards making the product better. You have to keep in mind people in finance spend money for reasons that seem arbitrary but actually are rational - like hiring for pedigree. Why do you hire for pedigree? Why do you need a nice office? You do it because it helps you raise more money later on. Same reason why you buy hebbia. In other words, they are not really selling productivity quite yet - they are just improving the effectiveness of investor relations at this point. And, to be clear, this is valuable, particularly since these firms compete with eachother to get capital and talent.
To date, the evidence doesn't show that surgical robots have any improvement whatsoever versus normal surgery in outcomes, safety etc. The only real improvement is a slight change in wound healing time, but imo its not big. That said, it is excellent for getting the top surgeons to come to you and to appeal to certain discerning patients that only want the best. A lot of people shorted ISRG on this thesis because this concept is unintuitive to them. This is literally one of the most successful healthcare companies of all time.
Their most active user btw is a managing director at blackstone. her daughter uses it for chemistry homework. The "killer use cases" are honestly few and far between at this point. An example would be semantic search across many documents. But to be honest, I think that given the large context window that Claude provides there isn't that much incremental benefit.
That said, I do think that actually underinvesting in user experience and focusing on sales has tradeoffs as a strategy, but isn't obviously bad. Building a large customer base before you have a sincere use of your product (e.g., making people more productive rather than the appearance of being on the right side of change) They will go up the experience curve a bit faster than competitors and will be able to spend more on R&D when the ecosystem develops more useful things around them. The risk to this strategy is of course that when you commit to a direction it can be hard to steer the ship.
How much are they paying you to post this?
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