Searching...
13 results for “ai startups”
Topic4 mentions across episodes
AI startups
Concept2 mentions across episodes
Startups
and introduce this to customers. There is a challenge, though. There is a caveat that I would make. As a very new technology for an established organization, there are risks associated with any launch. That's why at Amazon, we use MLP as an acronym,
12:44 / 13:51
from transcript12:44 – 13:51
...maybe startups have outgrown a simple solution that they have in place like moving from QuickBooks to NetSuite. And AI companies like Rillit are doing exactly this. You also don't have to be constrained by the existing categories of enterprise softwa
17:13 / 18:35
from transcript17:13 – 18:35
“Why former unicorn founders have unfair advantages in the AI race”
But what do you do with a marketing department? I used to wanna run a small one with 20 people, but, oh my god, that that team would not have been able to run any or run much less build any AI machin
28:20 / 28:55
market insight28:20 – 28:55
...startups because they're bound by the rules of p and l. New startups represent very little in the form of new revenue for incumbents, but they cost money to serve in terms of marketing spend or sales or building out a new product. As a new startup yo
16:04 / 17:36
from transcript16:04 – 17:36
if you think about the value chain of venture capital from sourcing to exit, you can apply technology and machine learning and AI, to use a terminology of today, across all the different steps. No doubts about that. And I have millions of ideas of th
11:12 / 12:15
from transcript11:12 – 12:15
And sometimes that lends itself to vertical solutions and sometimes general across horizontal. And the other thing to mention is the fast shipping culture. Some of the best companies I've worked with, let it be on my angel portfolio, follow eyes one
12:00 / 13:02
from transcript12:00 – 13:02
...startups has actually grown. So startups that otherwise might not have been able with 50 or 100 people to go after a multibillion dollar seed market, which is kind of the market that we're in, can now do so because of the leverage they get with AI. A
6:49 / 7:53
from transcript6:49 – 7:53
Some of our early winners are like Lambda, Ryder, Craya, but I personally like to work with founders that essentially absorb advancements in underlying infrastructure and turn them into enterprise grade solutions that ultimately deliver real value. H
2:54 / 4:11
from transcript2:54 – 4:11
...Vanta. Compliance and security shouldn't be a deal breaker for startups to win new business.
0:00 / 1:02
from transcript0:00 – 1:02
quantum computing. Whatever we see exciting people working on, we will invest in. And at the moment, the majority of people are building an AI. But I you know, this is such an important technological shift. Mhmm. And I suppose what we are seeing as w
17:22 / 18:24
from transcript17:22 – 18:24
It's interesting because I think the outcome is actually the opposite. We've seen non obvious founders more than, legacy VCs. In fact, we feed a lot of deal flow to, legacy VCs. We've made 278 intros. Last year, I think in the last twelve months, fou
22:31 / 23:30
from transcript22:31 – 23:30
Have a podcast?
Run your podcast through Clypt
Get ranked clips, hooks, and ready-to-post copy from your own episodes. Free to try.