why aren't all 10 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
Assertion Not checkable as stated
LLM migration eliminated annotation teams and increased Glean AI's gross margins
“The accuracy rates are better. Our cost to compute has gone down and like, it is the data scientist. We don't need a team to do annotations anymore for the models. And it's just like, it's like our gross margins. It's done like two step functions over the cour…”
Assertion Not checkable as stated
Katzenberg: 99 out of 100 vendor bills were approved automatically at Better
“And when I actually analyzed what our approval rate was at Better, 99 out of a hundred bills were getting approved.”
Assertion Not checkable as stated
Katzenberg: Commercial LLMs do not provide extraction confidence scores
“One of the drawbacks of using LLMs is like, we're not receiving confidence scores. On the extractions.”
Assertion Not checkable as stated
Katzenberg: LLMs are very poor at performing calculations
“We're going to do the calculations because the LLMs are very poor at that.”
Assertion Not checkable as stated
Katzenberg: Glean AI business grew over 3x in 2023
“Our business is up like three X, over three X so far this year.”
Prediction Held up
Katzenberg: External AI model pricing will fall over 12-18 months
“I think their pricing will continue to improve. So we can't just look at like where their pricing is today and assume it's going to be static over the next 12 months or 18 months. Cause like as they compete, their compute costs will come down. Like they'll, I …”
Assertion Not checkable as stated
Katzenberg: Manual vendor spend audits consistently yielded about 10% savings
“Inevitably, we'd find errors, we'd find consolidation opportunities, we'd play bad guy negotiations, but we'd find about 10% of savings opportunities each time we conducted this exercise.”
Assertion Not checkable as stated
Better identified $1.5M in savings on $15M of annual vendor spend
“The last time we did it was in 2019 and, at Better, the run rate on vendor spend at the time was about fifteen million dollars annually. And we've identified 1.5 million of savings.”
Assertion Not checkable as stated
League Apps saved $20,000 on Salesforce contract using Glean AI benchmarking data
“So we gave him benchmarking data and he reported back that they saved 20 K versus their prior contract.”
Assertion Not checkable as stated
League Apps estimates Glean AI saves 2-3% of non-payroll spend
“And then he also said like, he estimates that Glean, like the value is like two to three percent of non-payroll spend.”