Sramana Mitra: So I think the subtlety here is that if the decision makers are not adjacent decision makers, then the whole sales cycle has to be repeated. You may get a referral that, “Oh, we’re using this product and this product is doing well for us.” Right now, from a technology point of view, the same technology can be applied to a lot of different things. Your agent technology, for instance, can be applied to various use cases—like marketing, human resources, or engineering—but these aren’t adjacent use cases. They’re far apart within an organization, and in a larger enterprise, that adds complexity.
>>>Sramana Mitra: Enterprise has always been like that. We have this solution selling methodology that you have to break it down to technical decision makers, economic buyers, champion, and coach. That has always existed.
>>>Sramana Mitra: Lyzer sounds very interesting. So how does this company go to market? It sounds like it’s a horizontal technology. So presumably selling to the CIO.
>>>Sramana Mitra: Yash, I agree with you on workflow automation and very precise domain-specific AI being a much better opportunity to build businesses and do startups in than boiling the ocean and trying to do something much broader. In general, in startups, I don’t think broad brushed approaches work very well. They just burn a lot of capital. They don’t really produce very effective companies.
>>>Yash Hemaraj is General Partner at BGV, and Founding Partner at Arka Venture Labs. This is a very interesting discussion that goes into the nuances of high velocity Positioning and Go To Market strategies.
>>>Sramana Mitra: Just know, I have a slightly different question on capitalization of these companies. So you talk about these two kids from MIT who are commercializing their PhD thesis, I guess. You have this CalTech professor who’s commercializing his work in the domain of drug discovery using AI. Talk to me a little bit about how you structure these deals. You’re getting in at almost an R&D level.
>>>Sramana Mitra: Other than H2O.ai, have you invested in any other open source AI companies since?
Jishnu Bhattacharjee: We have invested in over twenty AI companies.
Sramana Mitra: Talk about some of them. How are you thinking about what to invest in? Do some case studies.
>>>Sramana Mitra: I think it depends on what timescale we are talking about because inside the enterprise, whatever application that you bring in, whether it’s non AI or AI, now everything is kind of in the AI domain. There are three things to consider – domain-specific understanding of what’s happening in that enterprise which includes domain-specific vocabulary, domain-specific workflow, and then domain-specific API integration.
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