 to the Cube, we are at the O'Reilly Fluent Conference, it's live, in San Francisco at the Hilton Hotel, so everybody's just finishing lunch, there's a lot of buzz and noise here in the background, but we're going to move on, and one of the things that we like to do on the Cube is we talk to the practitioners and we're excited about startups, right? Because startups is where innovation is happening, it's where people are doing new and exciting things and they actually had a startup competition here at the show, so we have with us here James Ferguson, the CEO of Quickly, which, if you can see on the screen, is spelled an interesting way. Well, that's quite easy, Jeff. Kilowatts, KW, IQ, Intelligence, Lee, Quickly, Fast. Oh, awesome, all right, great. So it spells energy intelligence. Okay, great, so welcome to the Cube. Thank you very much, great for you to have us here. Absolutely, and obviously you have an accent, so you came from far away. From Switzerland, actually. From Switzerland. Yeah, native to England, yeah. Okay, great, so what brought you, besides the competition, what brought you to Flune, what's the value of coming to something like this? First of all, if you can get in touch with the really top guys, with the technologies, you need help, they'll give it to you. It's very open, very friendly, very supportive. It also confirms that our infrastructure stack makes sense. We've got a great CTO, I'm a real rock star. Couldn't be here, sadly, but he actually put the application in so we've got to be there, and to then win is, that's for him, it's great affirmation, you know? What's his name? He's Andreas, Andreas Muller. Andreas, shout out for Andreas. Give him a wave to the camera, hopefully he's watching, is he in Switzerland also? Yeah, well, he's on the border off in Germany. Okay, great. So one of the big things we're talking about, obviously, is social and mobile and collaboration, all that stuff's going on, but the new thing, and we've talked a lot about here, is the internet of things and the industrial internet and having sensors on all these devices and this ubiquitous connected network and obviously a lot of horsepower in terms of the CPUs and the bandwidth and how that's changing the world. And you guys are right in the midst of that, so why don't you tell us a little bit about what's going on with quickly and what you guys are up to and what did you show here at the startup? Okay, a little bit of background. We've been doing consultancy in the energy game for a long time in buildings, so trying to help people save energy, that's simple. Commercial buildings. Yeah, big commercial buildings. Tower of London was our first client with a new product, which is fantastic. Interesting commercial application that happened in the Tower of London, I think, right? But our real audience is typically people like Honeywell, who've now signed us as a supplier, who they do energy performance contracting. There's a lot of the heavy lifting, number crunching that we can automate for them. That makes it easier rather than them spending days on spreadsheets. So they're not adding customer value if they're pouring over a spreadsheet, but it used to be have to develop applications and deliver them on a PC. But with the new technologies, you can really build real engineering products actually in the browser. And you can also use techniques like WebGL with the visualization tools. So I'm seeing stuff in data that I've not seen before, purely because I can see it better. So it's just a change of game in the last couple of years. So is your software, so you deliver software? Yep. And is it in the cloud? Yep, software as a service. Software as a service. And does it connect to devices? I mean, how does that work in terms of the energy management? Typically, bigger outfits have their meters managed. So basically, a utility company will be taking half the half alley reads, for example, and taking off into the cloud. So smart meters you may have heard of. It's the technology of reading things at high resolution. We then get independent weather data. It has to be independent because otherwise, if you're trying to diagnose the patient, the kid puts his thermometer in his own mouth. It's about it being independent. So independent data, bring the two together. And then anything that happens in the building, because it's an energetic process, running a boiler or a chiller or something like this, it's reflected almost like in ripples in this external fabric that you can think of encompassing the building, being the energy in and the weather, which determines the weather out. The energy out, if you like to say. It's pattern recognition basically. So what are the kind of ROI opportunities that this affords people? It can be crazy. We did some work with a supermarket chain where we were talking six-week payback, and I mean, that's just unheard of. And what are you doing for them? What's controlling thermostats? Or are you just identifying crazy stuff? Yeah, absolutely. It's the anomalies. There it doesn't make sense. So, I mean, a simple example for the domestic burden they'd understand this is, let's say you get a power cut, and you've got to reset your VCR, and I'm an old guard here, you know, old days, but you reset it. We were talking about VCRs earlier in the show, so flashing 12, 12, 12, 12. Yeah, exactly. You go and reset that because it's in your face. Okay. But somewhere up in the loft or down in the basement, there's an old water boiler there, and it's time clock stopped, and now it's heating at a wrong time a day, because it didn't get fixed. And more, I suppose, more relevant to big buildings is things like the daylight saving time change. All the control systems out there, there's great control equipment, but it's got to be programmed, and if people haven't specified it, it doesn't change. And so you're heating for nine hours instead of eight hours in the day, and that's like 7% saving off the bat for nothing. I mean, it's a few minutes' work to fix that. And does your software just collect the data and deliver back in an easily digestible or in a way to analyze it? Or do you guys also do the analysis and actually come back with suggestions on it? Absolutely. I mean, we're getting to a point now where we take this weather data and energy data, and that's all we know about the building, but we can identify the sorts of plant in there, how they're being controlled, algorithm problems with the controls. And if you're, I mean, let's say you're one of the big chains. Like, for example, a Starbucks or something like this, you've got thousands of outlets. You can't put an energy consultant on site in every one of those every day. Right, right. But what you can do is you can look for anomalies and say, okay, today we've got 10 sites that have gone crazy. Let's go fix those. Or we've got a problem with an external temperature sensor. Let's send a guy with a ladder. Rather than sending a consultant down and then he has to work out what's wrong and then send another, you're talking $2,000 bucks, whatever a day costs for no gain if you can actually brief them up front. So you're getting that information back to corporate to the facilities guys. You're giving them something to match on. Yeah, typically for the energy manager or facility manager will have that responsibility. Yeah, it's interesting. We were at the Splunk show last year and one of their funny examples of kind of intelligence in the industrial internet was apparently someone in Japan figured out that one of the ways to measure the health of a building was the data coming off the elevators. And you could tell whether people were getting ready to move out, you know, business was bad, not energy health, but you know, tenant health by the patterns that you could identify in these elevators. We'll see crazy stuff. I mean, in the simplest of cases, you're a pub in England, of course, we live in pubs very much. Yeah, we like pubs. There's a lot of beer drinking going on here too. Yeah, it's not bad either, great event, great things. But for example, you know, people will complain maybe in winter it's got a bit cold and just the bar manager will go and turn the thermostat out. And then same sort of time of year, but in the spring rather than, sorry, yeah, spring you call it rather in the fall. Right, right, right. People will open the door to get cold. They'll leave the heating on and the door's open and then some suddenly, you know, maybe June, July, someone will say, why is this radiator still hot? You know, we've got the door open and the windows open and this is still hot. Oh, I forgot. Right, right. And that forget, I forgot. It can be, you know, difference between profitability or loss. Right. For a small enterprise, you know, a small pub or restaurant or whatever. It can be straight on from bottom line, of course. Right, so talk a little about, right, where affluent software development, talk about, you said you were in consulting for many years, so you've been in the game. To my sins. How kind of the software development environment has changed as well as the infrastructure that actually I guess can help convince you to leave the consulting world and actually build a product because of this opportunity. So how has that changed and how has that affected your ability to really deliver value to your clients? Okay, I mean, there's a long back story and I don't want to bore people there. Well, it's all right. We've got a few minutes. Okay. You give us the medium version. Cambridge University, the government in the UK gave us a grant to see if it was possible to work out automatically what was wrong with control systems. And so we were going into the Cambridge colleges where we were given sample test sites to work on and literally walking around with floppy diskettes full of data and it got to the point where they were mailing us the diskettes and we were driving to look at the plant rooms and actually having looked at an on Excel spreadsheet or whatever, we realized that we knew what we were going to see because it obviously represents it. So, and this is the first step of pattern recognition. Right, right. And then we thought, well, most of these control systems then weren't connected to the net, so getting data was a problem. Ah, but okay, energy meter readings. Because it's a commercial contract with your utility company, everyone has it at some level and the resolution's been getting it better. We can get weather data anywhere in the world now. Any, you know, whether it's humidity in Singapore or then three year history or whether it's available now. So, if you like, the resources were always available but the technologies to make them happen were really, it was really hard work. But now with the new tool chains and that's the really big change, we can do the analytics in the background on a server using language call R. That's real pattern recognition. And then the wiring it together to get it to the client through the browser. It's all the guys here that are presenting on the tools. We're using those tools and they do most of the job for us. So, we're, you know, standing on the shoulders of giants if you know what I mean. Right, right. So, you touched on a little bit in, again, industrial internet that's coming in terms of big data. And, you know, how are you either using or planning to use a much larger array and quantity and frequency of data to really add more value into this opportunity? Actually, well, value is where it comes from. I mean, and people don't really think about this but if you think $1.5 trillion per year, that's our energy waste in buildings. And you and I, maybe it's a couple of hundred bucks but when you start looking at your schools, your universities, your public buildings, it's $1.5 trillion a year. The biggest player and arguably the most competent would be Honeywell. They're doing, in their energy performance contracting a hundred million turnover over 10 years. So, they're beginning to scratch the surface of the possibilities. They can only serve the big guys. Right, right. You know, the really big buildings. We feel that it should be that every coffee shop should be able to get good, timely, relevant advice that they can understand. They don't, not everyone's an energy manager. Right, right. But hey, go and adjust that, further start that time clock. That'll make you more comfortable and cost you less. Right. Performance goes up. Maybe you just answered this question, but you know, we're open source folks. You know, we love helping everybody out. So, just a little, it'll kill some of your business. But give the folks out there, just kind of what's the easiest, simplest, you know, take care of it right out of the gate. It sounds absolutely crazy, but check your time clocks. I mean, certainly after a daylight savings change, you know, spring and fall, just check you've moved your time clocks. If you're not there, a lot of people say, well, hang on, if I let it cool down then heat it up, won't that use more to let it cool down and heat up? If you can let it cool down and you're heating, let it cool down. If it's in summer and you can let it get hot because you're away on holiday, let it get hot and then cool it down. And we'll save energy that way. All right, good tip. It's good for the environment. It's good for the pocketbook, as they say in the ads. Well, James, thanks for coming along. So just one last final question. So where are you guys in the state of the company? What's happening next? Give you a little plug. Okay, that's great, thank you. We've, well, we were final at Loweb in Paris, which is great, and now we've just won here, which is... Did you win? Yeah. Oh, you're the winner. Hey, that's great. I should say we're one of the three winners. Okay, one of the three winners. So that's all right. That's a really great tech here. Kind of a democracy. That's all right. So that's good for credibility. Investors can see the risks are coming down and we're real, you know, incredible and so on. Right, right. But we're beginning to get to revenue with our bigger clients, some of the big utility companies in Europe. As I mentioned, Honeywell, we're a supplier now for them. And as we get to traction, we're going to be raising a seed round of about a million. Okay. And that should get us on that first step and hockey stick after that. Awesome, awesome. Hopefully there's some great investors out there or even more importantly, customers that take advantage. Again. Investors at quickly.com. Yeah, quickly.com, not spelled as we spell it. There you, he's got the T-shirt. All right, great. Well, James, thanks a lot for coming on theCUBE. Thanks for your time, Jeff. So again, we're at the O'Reilly Fluent Conference in San Francisco, the Hilton Hotel, taking you out to the conferences, finding the smart people, the winners of the start-up competition, ask them the questions that you would like to ask them and really help them bring the conference to you. We invite you to participate. Again, the hashtag for the confluent, for the conference. I'm having a hard time with that. It's fluid. Something in the lunch today. It's hashtag fluent conf, hashtag fluent conf. So join in on Twitter. We invite you to participate. We'll be back with our next guest after this short break. Thanks for being on theCUBE. Thank you.