The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 11 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Jain: Missing enterprise knowledge is a bigger problem than AI hallucinations
“People talk about hallucinations as a big problem with AI models. You know, we feel like, you know, a bigger problem for us is not even hallucinations. It's about Like, you know, most of the times you can't even, you know, find that information. Sometimes it's…”
Jain: Companies feared effective search because it exposed internal governance gaps
“We started to hear from businesses that, oh, I'm scared of good search. I don't want a good search product in my company because I have all these governance gaps. I have like, you know, sensitive information all over the place.”
Jain: Enterprises Care More About Process Automation Than Personal AI Assistants
“Businesses are actually a lot more, more interested in, not in that, but in actually thinking about how they can transform their company with AI, how they can take specific business processes, you know, where they're spending a lot of money and how, how do the…”
Jain: Glean's largest customer holds over 1 billion internal documents
“One of our largest customers. They have more than one billion documents inside their company. Now hear this, you know, when Alain and I, you know, when we were working on search, At Google, you know, in 2004, the entire internet was actually one billion docume…”
Jain: Glean faced nonexistent enterprise search budgets, unlike Rubrik
“In Rupert, we're an established market, like the budget, several dollars, and you had to actually replace an old technology with a new technology. Here we were in a market where we had no budgets. There was no concept of buying a search product in the enterpri…”
Jain: Looking closely at market priors leads founders to kill their ideas
“The more you look at priors, the more you're going to actually, likely you're going to actually ultimately kill your own idea.”
Jain: Enterprise search requires top-down sales because full-corpus indexing is expensive
“We cannot offer the product to one individual inside a company. Even one person, you know, their search needs require us to actually search over all the entire company's information for them. So it's expensive. You have to actually index, you know, all of your…”
Jain: Users adopted Glean search immediately but struggled with conversational Assistant
“Everybody has been trained over the last 20 years to actually type in, you know, one or two keywords, like Google has sort of taught us, you know, on what search can do. So with search, we never had a problem. Like, you know, we launched our product, we had, l…”
Glean Used Transformers for Semantic Matching in Version One
“The version, one of our product actually already used transformers for semantic, you know, matching”
Glean Built Custom Enterprise Embeddings on Top of BERT
“We started with this BERT model that Google had put in open domain, which was trained on all of the internet's, you know, data and knowledge. And we would then take those models and then for every customer of ours, we'd actually build custom embeddings, you kn…”