Daisy Intelligence

“Since then, we raised with a couple of significant super angels, about four and a half million dollars so far, and we have venture debt, a company called Espresso Capital in Toronto, who's been a fantastic partner.”

“We're looking kind of at a ten million plus raise.”

“Yeah, we're kind of at four million in ARR”

“You know, we're the only company using reinforcement learning and outside of engineering, and that really delivers huge value.”

“Our sell cycles kind of six to 12 inch months, you know, it depends, you know, the larger customers take longer, the smaller ones go fairly quick.”

“Annual contract value is two and a half times kind of customer acquisition costs.”

“Typically we're working in companies at the small end that are a hundred million. And most of our clients are kind of in the 1,000,000,002 billion dollar range. And then we have some really large clients who are in the ten billion dollar plus range.”

“So it gives us, it's expensive capital, but it gives us a non-dilutive capital and gives us flexibility to negotiate with VCs who, you know, we are not running out of money as we're having these conversations.”

“And for us, if we don't deliver 10 times that return, we tell our customers we're going to quit and move on because we're really selling net income growth is what Daisy sells. And we've been able to do that so far with all of our customers.”

“On average, they're paying, you know, 250,000 to 500,000 a year in that range.”

“If we make a retailer more efficient and more profitable, they won't bank the money. They'll invest it in lowering prices.”

“We've grown, I mean, our revenue has grown, you know, kind of -10% is what I'd say, even though we lost kind of two or three customers.”

“And if they execute our recommendations, we've been able to double their net income, which is massive and unheard of.”

“We envision if we get to about 50 to 60 customers, we think we'll be in the, you know, close to a billion dollar valuation, and we're already at, kind of, 17 today, so it doesn't seem like a stretch that over the next three years we could, we can get to that, …”

“We grew a hundred percent in the last year, so we've done kind of basically triple, triple, and it, and it'll be, you know, close to a double by the end of this year, so, and we're really chicken in the egg.”

“If you're looking at purely financial metrics, like typical SAS companies, then we're maybe 30 to forty million in value today.”

“Total customers, we have a total of 17 customers today.”

“Well, we, we've been able to get a minimum of three percent top line sales”

“Yeah, I own in the 20, 27% of the company, which is still great.”

“We use the exact same math at every single customer.”

“So the plan next year is to, you know, grow revenue by more than five million in ARR, right? So Right. We're going to grow it from, you know, six to 12.”

“Yeah, we're burning today, you know, we're both 300 K a month, you know, so we dialed it back from the 500.”

“Our ACV is like half a million and up.”

“I mean, we've grown our client total company revenue by three to five percent, which, you know, on a base of you know, our largest customers, it's more than a billion dollars in annual revenue.”

“There was no cap on it, so it'll just be a discount to the next round”

“I mean, it's like 15 and a quarter percent like interest and there's no dilution. It's no equity.”

“No retailer will ever admit to us that you did this, right? Like, because if they do that, it's negotiating leverage.”

“So we're simulating the future, and you don't necessarily have to have ever done it in the past. It doesn't need a labeled example, so the historical data just lets us calculate seasonality and, ah, you know, elasticity, cannibalization, halo, pull forward, an…”

“Yeah, we've raised about twenty million in total.”

“So we, you know, we raised like five million A couple of weeks ago. So that's our runway, you know, for another. 18 months.”

“Last month recurring revenue was 500 K a month.”