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17 results for “technical insights”
When you give a marketing document to a chat GPT and say, I did this campaign last week. Next week, I'm going to reinvent, create a new campaign. It'll do a great job. But you can't do that with IT systems because you want Hawkeye to give you exactly
17:08 / 18:21
from transcript17:08 – 18:21
...they'll report back with hypotheses and insights
6:01 / 7:01
from transcript6:01 – 7:01
like we do here at Launch, having the best, most up to date data at your fingertips, well, it's essential. Listen. I'm smart, but I am not an expert in every single sector, industry, or cutting edge technology. That's why our entire team is addicted
20:12 / 21:26
from transcript20:12 – 21:26
...That's exactly what Alpha Sense does. With the acquisition of Tagus, AlphaSense is now the ultimate research platform built for professionals who need insights they can trust fast. I've used Tagus before for company deep dives right here on the podca
2:04 / 3:16
from transcript2:04 – 3:16
...insights plug directly into your earnings, diligence, and PitchBook workflows with no tool switching. AI for coverage and efficiency, humans for complexity and conviction. Sounds like just the right mix to create a scalable institutional edge without
3:42 / 4:48
from transcript3:42 – 4:48
Sounds like just the right mix to create a scalable institutional edge without growing headcount. For hedge funds, this means validating thesis assumptions before earnings across dozens of experts instead of a handful. For private equity, it means fa
0:46 / 1:57
from transcript0:46 – 1:57
...so your primary insights plug directly into your earnings, diligence, and PitchBook workflows with no tool switching. AI for coverage and efficiency, humans for complexity and conviction. Sounds like just the right mix to create a scalable institutio
3:41 / 4:45
from transcript3:41 – 4:45
And imagine having that sort of step change, but instead of a dot moving on a map, you have a live multimodal understanding of an entire environment, where assets are, what's changing, what's risky, what needs action. Whoever builds that layer become
14:55 / 16:04
from transcript14:55 – 16:04
Sounds like just the right mix to create a scalable institutional edge without growing headcount. For hedge funds, this means validating thesis assumptions before earnings across dozens of experts instead of a handful. For private equity, it means fa
0:46 / 1:47
from transcript0:46 – 1:47
For hedge funds, this means validating thesis assumptions before earnings across dozens of experts instead of a handful. For private equity, it means faster pre IOI scans and deeper commercial diligence. And for asset managers, it means pulling real
4:28 / 5:32
from transcript4:28 – 5:32
I chatted with the head of IT recently who told me for the first time in his two decade long career, he believed that IT support was fundamentally gonna change. If all of us want this software to be doing work for us, ideally, it's doing work with at
0:01 / 1:03
from transcript0:01 – 1:03
...insights plug directly into your earnings, diligence, and PitchBook workflows with no tool switching. AI for coverage and efficiency, humans for complexity and conviction. Sounds like just the right mix to create a scalable institutional edge without
4:28 / 5:33
from transcript4:28 – 5:33
...so your primary insights plug directly into your earnings, diligence, and PitchBook workflows with no tool switching. AI for coverage and efficiency, humans for complexity and conviction. Sounds like just the right mix to create a scalable institutio
5:10 / 6:15
from transcript5:10 – 6:15
multistage reasoning test that requires a PhD in multi different languages and, like, human feedback is gonna be important in that for the next decade. I have a strong belief on that, and that was actually one of when I chose to take this job, that w
34:14 / 35:31
from transcript34:14 – 35:31
...are, you know, very technical. These require a lot of expertise.
7:29 / 8:38
from transcript7:29 – 8:38
Sounds like just the right mix to create a scalable institutional edge without growing headcount. For hedge funds, this means validating thesis assumptions before earnings across dozens of experts instead of a handful. For private equity, it means fa
0:46 / 1:57
from transcript0:46 – 1:57
...insights plug directly into your earnings, diligence, and PitchBook workflows with no tool switching. AI for coverage and efficiency, humans for complexity and conviction. Sounds like just the right mix to create a scalable institutional edge without
3:45 / 4:46
from transcript3:45 – 4:46
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