Michael Sakowski on Crunched: Excel-native AI analyst for finance power users that caught a £10M valuation error

room. Let's bring in Phillip from Crunch to the TVP and Ultradom. [music] Phillip welcome to the show.

What's happening?

Thanks for joining us. Please introduce yourself and the company.

Hey guys, pleasure to be on. Great to meet you. Uh Michael actually from from Crunch. We did the last minute last minute switch here.

Oh, okay. Good to see you.

And the co-founder as well CO of Crunch.

Fantastic.

Maybe I give you like a two second description of Crunch then. Um, Crunch is your Excel AI analyst built by and for power users. So, it's like this side panel chat in Excel basically cursor for the world's most popular programming language and then you just chat the natural language and it makes modeling for you.

Makes a ton of sense. Very clear value prop. I think everyone who uses Excel wants a co-pilot, but there is a company that's trying to build co-pilot and they happen to own Excel. How are you imagining this plays out? Is are you going to live in plug-in world? Are you going to live at the OS level and be screen scraping? Are you worried about sharp elbows for Microsoft? How are you how are you dealing with all that?

Ah, it's a great question. I think um Microsoft is for sure going to build a great product. They're building a co-pilot for uh two billion Excel users and they're in competition with Google Sheets, right? I think

sure

we're building a tool specifically for the top 1% finance professionals, investment bankers, private equity associates, management consultants of the world and who use Excel in a very specific way, right? So this is more of the 5 million of the Excel users, the top 1%. So that's a bit of the bit of the difference.

Uh lot of lot of big big market, big opportunity. If you build a great product, there's tons of people that that will happily pay for it. Uh there's also tons of startups as well going after this opportunity. What what do you think uh what do you think they're getting wrong or like you know uh or or is this just going to come down to actual like product quality and and working super closely with these power users to make something that that actually integrates into their uh everyday Excel life.

Yeah, absolutely. So I think we have uh plenty of startups going after this opportunity. We we don't think about competition too much, but out of the big ones with the most fraction, we're the only one with a team that has 10,000 plus real life Excel hours um in our previous jobs, me and me and my co-founder Philip in McKenzie and another finance gigs. Um and I think that really shines through in the product. Uh I think also um crunched is modeling more like a real life analyst and performing more of the real tasks that you do on the analyst floor versus like some of the bit artificial benchmarks you see around. Um so for example crunch can detect mistakes in workbooks. Um plenty of time is spent in like private equity firms and actually reviewing Excel and making sure they are correct. As much time as uh modeling from scratch, right? And then uh these professionals typically work with templates, right? and they need Crunch to fill out and augment their templates, not build like basic analysis from scratch. We can do that as well, but we're great at working with large models and and these sorts of things.

How do you think about uh the enterprise flywheel here? It seems like one of Cursor's main advantages is that um they they have a really solid data flywheel. Now um from open source developers and developers who are not in a you know enterprise level contract I imagine that the top 1% of of investment bankers consultants like on day one they're going to not want you to train on their data because it's going to be not just some code that builds a front-end website but like extremely critical financial information, private information like it is probably a higher bar to not letting that leak into a training run. So, how do you get a data flywheel going? How do you improve the product iteratively?

It's a good question, right? And and as you say, security is top concern, I think, for all of our customers. We live with like global consulting firms um but also

let's give it up for global consulting firms. They don't get enough love. [applause]

They don't get enough love. [laughter] Except here. Except here. Except here.

They just don't

I will I will defend. [laughter]

Exactly. Exactly. Well,

that's good. Um, no, but but they're obviously super concerned about their security, right? And do live public deals, right? All of this stuff. Um, and so like

uh in in in principle, we do not uh train uh the on the data of our customers and we cannot see what the prompter do, right? Yep.

At the same time, what we want to do now and just in record time closed our our fundra um we want to make sure that we tailor crunch to every single firm um as well. That's great. Um um and then um when we tailor it, we have discussed with a few customers like the opportunity to like for some of the large organizations, they do enough modeling work on a global base that is possible to like tailor do some finetuning and tailor to their specific organization. Um but as well we come in in a forward deployed manner, right? and and do customization whether that is formatting or or solving for their specific workflows and linking into their templates. um how like the SIMs that they get, how can we link that into their specific LBO template and then transfer that from like the simple LBO to the advanced LBO and and these sorts of custom.

What's the biggest deal uh Crunch has uh supported?

The biggest deal we have supported, that's a good question. I can tell you about the the

You don't need to name the company. Yeah, you don't need to name the company.

It was a $500 billion company. They were doing a $1.4 trillion deal. They were doing about 20 billion in revenue. Not going to say who it was. [laughter]

Exactly. Exactly. No, but I can tell you a real story about a mistake we caught though. Crunch has this uh error uh detection system. Okay.

Um and on a live deal for an associate at one of our private equity clients uh in London um used the sort of crunch mistake detection system to uh to identify or like scan his one of his previous models on a real transaction and identified a mistake in the working capital that overvalued the deal by 10 million pounds. So,

wow. That one is uh

You got You saved his job.

Send him an invoice for 5 million right now. He just saved him 10. I give me 50% of that. That's your seed round right there.

Exactly. Exactly.

Well, congratulations [clears throat] on a fantastic demo day. Thank you so much.

Yeah. Great. Great to meet you, Michael.

We'd love to talk to you tomorrow.

I live for Excel Asians. I'm so excited about this category. It just feels like

I would love to. Thank you. Um well, have a great rest of your day. We will talk to you soon. Great hanging, Michael.

Goodbye.

All right, thanks guys.

Numeral.com.

What $500 billion company could that be?

Numeral.com compliance handled. Numeral worries about sales tax and VAT compliance so you can focus on growth. Uh speaking of growth, uh there's some there's some folks putting Menllo Ventures in the truth zone. uh enterprise large language model API market share has been falling for open AI. It's been climbing uh amongst anthropic according to Menllo Ventures. Ev Randall puts it in the truth zone over at Benchmark uh multi-time TVPN guest Ev Randall. He says people are quoting this Menllo Ventures chart and extrapolating from it like it's official data from the Federal Reserve or something. It's a small sample survey conducted by an investor inanthropic. Please calm down. Uh I like that he's pouring some some cold water on this. Um

this was from uh November 3rd. Yes. Too. So

at the same time, does is it possible that OpenAI's enterprise large language model API market share is falling? Sure. You know, they were the only game in town when they launched. [laughter] Uh and so you would expect their market share to fall a little bit over time. Uh will be interesting to see. we will get more data on this. All these companies are going to be public in a couple years and so we'll know exactly how it's breaking down. But uh until uh until that happens, we will return to our