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Tamecco Inc. | Entity website

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Tamecco Inc. | Entity website

Frequently Asked Questions 1How does a loyalty program help local businesses? According to the 80/20 rule, 80% of a store's revenue is generated from 20% of its customers, i.e ...


Tamecco Inc. | Entity website

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Tamecco Inc. | Entity website

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News Article | April 4, 2014
Site: sg.finance.yahoo.com

Marketplaces and ecommerce startups seem to be hot favorites in our list of who got funded last week. Congratulations! Japanese home design marketplace Suvaco announced it raised about US$1.18 million from Fuji Startup Ventures and Mobile Internet Capital. The Tokyo-based startup lets users browse and search real portfolio photos to find the best interior or exterior design to suit them. Suvaco partners with 200 home construction companies that make up a library of more than 8,000 examples. India-based ecommerce site Teabox announced it has secured US$1 million in funding led by Accel Partners India, along with some cash from Singapore’s Horizen Ventures. It aims to put India on the world map by shipping direct to tea drinkers around the world. Singapore startup acceleration company JFDI announced it has raised S$2.7 million (US$2.1 million) investment round led by Infocomm Investments, a government-linked investment firm, with support from SpinUp Partners in Russia, Fenox Venture Capital in Silicon Valley, as well as private investors like Vijay Saraff, Paul Burmester, Thomas Gorissen, and undisclosed investors from the Philippines. JFDI is also looking for more and is beyond the halfway mark towards its goal of raising US$4.7 million. The money will be invested into startups that will join its three bootcamps this year. It will put in S$25,000 (US$19,700) in cash investments per team for between five to 20 percent of equity depending on maturity of the startup. (Techlist Profile) Chinese Cryptocurrency exchange OKCoin announced it closed a US$10 million funding round led by Ceyuan Venture Capital, followed by Mandra Capital, Venture Lab, and several angel investors. It also revealed it actually closed the round late last year. According to its vice president, the company is currently seeking a Series B fund to expand overseas. Singapore and Silicon Valley-based startup Nitrous.IO has raised a US$6.65 million round led by Bessemer Venture Partners. The syndicate includes 500 Startups, Crunchfund, Facebook co-founder Eduardo Saverin, Golden Gate Ventures, and Viki CEO Razmig Hovaghimian. (Techlist Profile) Singapore-founded dating app Paktor has raised US$500,000 pre-Series A round that values it at US$6.5 million. Participants include a group of Hong Kong-based angels as well as a private investor that was involved in the previous seed round. (Techlist Profile) Beijing-based mobile gaming company FunPlus has completed a US$74 million series B funding round. The investment was led by Orchid Asia Group, GSR Ventures, and Steamboat Ventures. It will be used to ramp up hiring and help crank out at least two more titles by year end. Chinese mobile commerce retailer Maimaibao announced it received an undisclosed amount of funding led by Tencent, followed by MediaTek and Sequoia Capital. Sohu IT speculates this round is worth around US$100 million. Prior to this, the company raised US$65 million since 2006. The money will be used to develop a new smartphone model under its Big Q brand. Chinese software maker Smartisan has secured RMB 150 million (US$24 million) in funding to help the small, largely unknown startup launch a smartphone. Smartisan Luo Yonghao stated publicly on his Sina Weibo account that its first ever phone will be unveiled on May 20. The smartphone will cost around RMB 3,000 (US$487). Tokyo-based startup Translimit announced it has raised 10 million yen (US$100,000) from Genuine Startups and Skyland Ventures. The funds will go towards launching a mobile quiz app called BrainWars, with social competition features. Jakarta-based game studio Touchten Games raised Series B funding from CyberAgent Ventures last November. It recently announced that it has completed its Series B round. The funding amount was not disclosed, and is raised from Japanese animation studio TMS Entertainment, Singapore’s UOB Venture Management, and Indonesian incubator Ideosource. (Techlist Profile) Bangalore-based online jewelry retailer Bluestone has raised US$10 million from Kalaari Capital and other investors. The company has previously raised US$5 million in funding from Accel Partners and serial entrepreneur Meena Ganesh. Customer loyalty app startup Tamecco has recently received 100 million yen (US$983,000) investment from Osaka-based Yume no Machi SoZo Iinkai. The latter is also the company behind Japan’s leading food delivery site Demaecan. Just last month we announced Bangalore-based mobile payment startup raised US$8 million. It makes a Square-esque gadget that attaches to a smartphone and allows retailers and merchants to process credit card transactions on their phones and has recently announced that it raised an additional “minority investment” from American Express. Are you fundraising? Let us know how we can help you at Techlist. The post 14 startup funding rounds in Asia last week appeared first on Tech in Asia.


News Article | March 1, 2012
Site: in.reuters.com

YUME NO MACHI SOUZOU IINKAI CO LTD:Formed capital and business alliance with Tamecco K.K. on March 12.To acquire 190,549 shares in Tamecco for 99,150,108 yen through private placement on March 13, to hold 13.9 pct of voting rights (190,549 shares).To cooperate in development and operation of marketing system based on artificial intelligence as well as introduction of Tamecco in stores.


News Article | April 15, 2015
Site: www.techinasia.com

The inaugural Tech in Asia Tour: Road to Singapore – a nine-city search in Asia for the best startups to showcase at our upcoming Tech in Asia Singapore 2015 flagship conference on May 6 and 7 – has concluded. The tour recorded a total of 1,192 attendees, 55 startups, and nine winners. During the month of March 2015, we traveled to Jakarta, Hanoi, Hong Kong, Bangkok, Tokyo, Taipei, Seoul, Kuala Lumpur, and Bangalore in search of the best startups. Founders competed in each leg of the tour by pitching to a live audience and panel of investor judges. The champions of each tour won themselves free flights and accommodation, conference passes, and a startup booth at Tech in Asia Singapore 2015. These nine winners will be exhibiting at the Bootstrap Alley, where they get the unparalleled opportunity to test products and receive feedback from over 3,000 tech-savvy early adopters around Asia. Catch them at our conference and enjoy 10 percent off passes, valid till April 19. As we mark the end and success of our first-ever Tech in Asia Tour: Road to Singapore, we have our judges, sponsors, and partners to thank. Their time and efforts have made this tour possible, and we will strive to make Tech in Asia Tour: Road to Tokyo bigger and better – stay tuned for more updates!


Almost everyone has a favorite restaurant or local business that they frequent, where the waitress knows your order before you even sit down and the clerk tips you off about a new shipment or upcoming sale. Many shoppers carry physical loyalty cards or coupons when they head to the mall, and an increasing number of people are utilizing brand-specific apps or online mailing lists to catch wind of special offers. What if you could receive all of the benefits that come with being a “regular” with a single mobile app? Tokyo-based startup Tamecco is trying to achieve just that, while also promoting discovery and providing deep analytics and artificial intelligence-powered targeting for the businesses themselves. “Amazon provides personalized content and recommendations in the online shopping space,” Jonah Oh, the startup’s CEO, tells Tech in Asia. “Tamecco focuses on bringing that same kind of personalization for shoppers to the physical world, in brick and mortar shops.” “Amazon gets information from a user’s browsing or shopping history, and it’s easy to get that from cookies and shopping cart data,” Oh adds. “But it’s much more difficult to find out these things in the physical world, like where you went window shopping versus where you actually went in and bought something.” Tamecco leverages AI and machine learning to provide targeted coupons, discounts, and other perks for its users’ favorite or most-frequented brick-and-mortar stores. As long as the app is installed, launched at least once, and a user has given permission for location services, alerts are sent automatically from the startup’s proprietary hardware – similar to iBeacon, but compatible with both iOS and Android-powered mobile devices. Tamecco will continue to work until the user uninstalls it. “As the user experience is our utmost important design factor, Tamecco really focuses on keeping the application’s impact to the user and their phone to a minimum – including battery impact, data usage, and other phone services,” Oh explains. For the retailer, Tamecco can analyze a variety of things based on a user’s location, such as high and low-traffic areas or how close a customer got to the cash register without making a purchase. It can also tell when a user is a first-time visitor to a specific shop, and perhaps offer them a one-time discount or a free cup of coffee for new customers. If you used to eat or shop somewhere but haven’t made a purchase in a while, Tamecco might send you a special coupon to entice you to return as you walk by. Services that track your movements and gather data about your personal habits often throw up red flags for the privacy conscious. Tamecco couldn’t exist without gleaning such information, and Oh stresses that data collection is always anonymized. “It’s never you,” he says. “It only knows that there’s this person in their 20s or 30s who tends to hang out in this area. Individual behavior also feeds into the group consensus, so we can follow trends within groups. Our AI engine learns by understanding your behavior patterns, and your individual movements help shape ideas about the larger public.” As users make transactions, Tamecco aggregates the data in real-time to pick up on trends. It combines merchant POS data, geospatial data, organic engagement with the app itself (i.e. redeeming a coupon), and AI-driven engagement (personalized and/or time-sensitive offers sent via push notifications). “On top of all this, the AI engine can also determine strong indicators of an individual’s highly-probable behavior to enrich gaps in explicit data,” Oh says. “Even if you use cash for your transaction, there are many ways that Tamecco would be able to link you to that transaction.” All the while, Tamecco’s machine learning algorithms consider how relevant an offer is on a per-person basis. If sushi is trending, and you don’t eat sushi, it doesn’t make sense to send you a coupon for a sushi restaurant. Similarly, if you’re a man, you probably wouldn’t care about a nail salon discount. Tamecco hopes that its AI will keep customers engaged, as no one likes getting spammed with offers they have zero interest in. Oh gives a simple example: Imagine that you pass by stores A, B, and C on your way to work. You occasionally shop at store A, eat at store B, but never go to store C. Another user also visits A and B from time to time, and similarly avoids C – but they often visit store E around the corner. Tamecco would likely send offers for stores A and B, and might also generate a coupon for store E – but only if its AI determines a match between whatever that shop offers and the user’s individual profile. At present, Tamecco’s partner retailers are mainly in the food and beverage space. Yoshinoya, Japan’s largest beef bowl and sushi conglomerate, is a major partner. The service has already been integrated with about 300 of the firm’s restaurants in Japan’s central Kanto region, and is planning to expand its service to more than 2,200 locations nationwide by the end of 2016. Why is food and beverage a great jumping off point for Tamecco? “Restaurants and cafes have perishable products that need to be thrown away at the end of the day, so they can run spontaneous campaigns where a drink purchase gets the user a free donut,” Oh says. Apart from the food and beverage sector, Tamecco has also partnered with the popular ReRaKu massage chain, which has approximately 150 locations around Tokyo and its suburbs. The startup also inked a deal with Tokyo’s Galaxy Theater, the most famous musical theater in the Japanese capital. On the Tamecco roadmap are businesses varying from museums and golf resorts to dental clinics and juku cram schools. Further down the road, the startup is also keen to scale its technology to Southeast Asia, particularly Indonesia, Malaysia, and Singapore. If retailers consider the Pareto principle that about 20 percent of repeat customers produce 80 percent of sales, using a targeting system like Tamecco makes sense. If a business can target repeat customers, rather than attempting a catch-all scheme akin to handing out physical coupons on the street, it can grow its revenue exponentially. In that regard, Tamecco is more like an intelligent loyalty card than a simple discount platform like Groupon. In fact, Oh says that Tamecco is the exact opposite of Groupon. “The Groupon way is to pack a bunch of people in a room, throw a rock in, see who it hits, and tell them about [a deal]. If the deal is for a men’s shoe store and it hits a woman, it becomes noise that she wants to filter out. The next time she gets hit by a rock, she won’t even turn around to see where it came from.” As far as building a loyal following, Oh cites the following example: “If you go to a barber once a month you’re a great customer, but if you go to a coffee shop once a month, you’re not a great customer. Sending you a reminder to get a haircut isn’t useful, but if we know what day the barber shop is slow, we can offer a percentage off if you go on that day. The shop gets a sale and the customer gets to feel like a VIP. Even if you’d have gone there anyway, this approach creates brand loyalty.” The end goal, Oh explains, is to have users who receive an offer and think to themselves, “How did they know I wanted this?” Tamecco is also using its technology to help businesses without physical locations. Yumenomachi, a listed company on the JASDAQ that operates popular food delivery portal Demae-can, enlisted Tamecco’s AI to increase its online content engagement with consumers. Oh explains that the company would send a huge number of email magazines each day. “On their very best day, maybe half would get opened. Of that, maybe half would actually click a link. Then a half of that – again, on the best day – actually transact on the web portal. That’s down to an eighth of recipients.” Tamecco used its AI to analyze things such as which items customers order the most often, how often they ordered, what areas were generating the most orders, and what kind of trends emerged when examining trends in the food delivery domain at large. In the end, the startup was able to reduce the number of email magazines by more than 30 percent. Despite casting a smaller net, the startup was able to increase the open rate by targeting recipients with tailored offers. “Between January and April, we increased actual transactions by a double-digit percentage,” Oh says. Tamecco offers flexible payment options for partner merchants. Some opt for fixed membership fees, while others opt for a revenue sharing model. In the case of revenue sharing, Tamecco doesn’t get anything unless they increase traction. The service is completely free for individual users. Oh, a former investment banker at Citigroup Capital Markets, has cultivated a diverse 10-member team – about half Japanese and half non-Japanese – and a star-studded board and advisory panel that includes Koichiro Tsujino, the former CEO of Google Japan, and Paul Kuo, the former CEO of Credit Suisse Japan. With a computer science degree under his belt and fluency in Java, C, C++, Prolog, Lisp, Cobol, Fortran, Assembler, and “several other old-school” programming languages,” Oh wrote the first prototype of Tamecco himself in early 2012. He ran it on his iPad and showed it to Tsujino, who was immediately interested. The CEO went to work, taking as many meetings as he could to secure the first 50 merchants. With the AI still in development, Oh recalls helping a client analyze how many people who took its paper loyalty cards were actually using them: “We had a backup staff at our headquarters who’d view the security cameras that ran during lunch and business. She’d spend four hours a day reviewing the footage with two hand clickers – one for how many customers entered the shop and one for how many used the stamp card.” In May that year, the beta version of Tamecco went live. In the beginning, users had to scan QR codes to opt in to offers. Oh and his co-founders kicked in their own money to launch the MVP themselves. Oh says that Tamecco’s current monthly active users number between 30,000 and 40,000, with the number increasing 15 to 40 percent month-on-month over the last five and a half months. He connects the higher end of that monthly growth to the rapid implementation of Tamecco service with nationally-branded merchants like Yoshinoya. Oh adds that another important figure is the startup’s total digital reach, including the 6.5 million monthly active users on Yumenomachi, and the 500 daily transactions at each of Yoshinoya’s 300 beef bowl outlets in Tokyo alone. All of Tamecco’s nationally-branded merchants are using the startup’s wireless signal technology. About half of the local mom-and-pop shops using it are still using QR codes, but Oh expects to completely transition them to signal tech by the end of 2015. While some may consider the existing, and very fragmented, loyalty space in Japan to hold a number of potential competitors – such as Rakuten Super Points, T-Point, Ponta, and myriad merchant-specific apps and physical point cards – Oh considers each of those services to be potential collaborators. “[They] can simply join the Tamecco ecosystem, as in the case of our current merchants, or directly implement our technology onto their own apps or platforms,” he says. “ Either way works, as it helps our AI engine’s predictive models to get even better.” Tamecco was completely bootstrapped throughout its first year, then raised approximately US$1 million from a combination of personal investments by team members, Kuo, and other high net worth angels in the tech and finance world. A second seed of roughly the same size was provided by Yumenomachi in March 2014. The startup is currently gearing up for a sizable series A round. “It’s not just about raising money, it’s important to find the right partners whose wheels are aligned in the same direction as ours,” Oh says.


News Article | August 11, 2015
Site: ignition.co

This App uses AI to give you just the Coupons and Discounts that you really want Almost everyone has a favorite restaurant or local business that they frequent, where the waitress knows your order before you even sit down and the clerk tips you off about a new shipment or upcoming sale. Many shoppers carry physical loyalty cards or coupons when they head to the mall, and an increasing number of people are utilizing brand-specific apps or online mailing lists to catch wind of special offers. What if you could receive all of the benefits that come with being a “regular” with a single mobile app? Tokyo-based startup Tamecco is trying to achieve just that, while also promoting discovery and providing deep analytics and artificial intelligence-powered targeting for the businesses themselves. “Amazon provides personalized content and recommendations in the online shopping space,” Jonah Oh, the startup’s CEO, tells Tech in Asia. “Tamecco focuses on bringing that same kind of personalization for shoppers to the physical world, in brick and mortar shops.” “Amazon gets information from a user’s browsing or shopping history, and it’s easy to get that from cookies and shopping cart data,” Oh adds. “But it’s much more difficult to find out these things in the physical world, like where you went window shopping versus where you actually went in and bought something.” Tamecco leverages AI and machine learning to provide targeted coupons, discounts, and other perks for its users’ favorite or most-frequented brick-and-mortar stores. As long as the app is installed, launched at least once, and a user has given permission for location services, alerts are sent automatically from the startup’s proprietary hardware – similar to iBeacon, but compatible with both iOS and Android-powered mobile devices. Tamecco will continue to work until the user uninstalls it. “As the user experience is our utmost important design factor, Tamecco really focuses on keeping the application’s impact to the user and their phone to a minimum – including battery impact, data usage, and other phone services,” Oh explains. For the retailer, Tamecco can analyze a variety of things based on a user’s location, such as high and low-traffic areas or how close a customer got to the cash register without making a purchase. It can also tell when a user is a first-time visitor to a specific shop, and perhaps offer them a one-time discount or a free cup of coffee for new customers. If you used to eat or shop somewhere but haven’t made a purchase in a while, Tamecco might send you a special coupon to entice you to return as you walk by. Services that track your movements and gather data about your personal habits often throw up red flags for the privacy conscious. Tamecco couldn’t exist without gleaning such information, and Oh stresses that data collection is always anonymized. “It’s never you,” he says. “It only knows that there’s this person in their 20s or 30s who tends to hang out in this area. Individual behavior also feeds into the group consensus, so we can follow trends within groups. Our AI engine learns by understanding your behavior patterns, and your individual movements help shape ideas about the larger public.” As users make transactions, Tamecco aggregates the data in real-time to pick up on trends. It combines merchant POS data, geospatial data, organic engagement with the app itself (i.e. redeeming a coupon), and AI-driven engagement (personalized and/or time-sensitive offers sent via push notifications). “On top of all this, the AI engine can also determine strong indicators of an individual’s highly-probable behavior to enrich gaps in explicit data,” Oh says. “Even if you use cash for your transaction, there are many ways that Tamecco would be able to link you to that transaction.” All the while, Tamecco’s machine learning algorithms consider how relevant an offer is on a per-person basis. If sushi is trending, and you don’t eat sushi, it doesn’t make sense to send you a coupon for a sushi restaurant. Similarly, if you’re a man, you probably wouldn’t care about a nail salon discount. Tamecco hopes that its AI will keep customers engaged, as no one likes getting spammed with offers they have zero interest in. Oh gives a simple example: Imagine that you pass by stores A, B, and C on your way to work. You occasionally shop at store A, eat at store B, but never go to store C. Another user also visits A and B from time to time, and similarly avoids C – but they often visit store E around the corner. Tamecco would likely send offers for stores A and B, and might also generate a coupon for store E – but only if its AI determines a match between whatever that shop offers and the user’s individual profile. At present, Tamecco’s partner retailers are mainly in the food and beverage space. Yoshinoya, Japan’s largest beef bowl and sushi conglomerate, is a major partner. The service has already been integrated with about 300 of the firm’s restaurants in Japan’s central Kanto region, and is planning to expand its service to more than 2,200 locations nationwide by the end of 2016. Why is food and beverage a great jumping off point for Tamecco? “Restaurants and cafes have perishable products that need to be thrown away at the end of the day, so they can run spontaneous campaigns where a drink purchase gets the user a free donut,” Oh says. Apart from the food and beverage sector, Tamecco has also partnered with the popular ReRaKu massage chain, which has approximately 150 locations around Tokyo and its suburbs. The startup also inked a deal with Tokyo’s Galaxy Theater, the most famous musical theater in the Japanese capital. On the Tamecco roadmap are businesses varying from museums and golf resorts to dental clinics and juku cram schools. Further down the road, the startup is also keen to scale its technology to Southeast Asia, particularly Indonesia, Malaysia, and Singapore. If retailers consider the Pareto principle that about 20 percent of repeat customers produce 80 percent of sales, using a targeting system like Tamecco makes sense. If a business can target repeat customers, rather than attempting a catch-all scheme akin to handing out physical coupons on the street, it can grow its revenue exponentially. In that regard, Tamecco is more like an intelligent loyalty card than a simple discount platform like Groupon. In fact, Oh says that Tamecco is the exact opposite of Groupon. “The Groupon way is to pack a bunch of people in a room, throw a rock in, see who it hits, and tell them about [a deal]. If the deal is for a men’s shoe store and it hits a woman, it becomes noise that she wants to filter out. The next time she gets hit by a rock, she won’t even turn around to see where it came from.” As far as building a loyal following, Oh cites the following example: “If you go to a barber once a month you’re a great customer, but if you go to a coffee shop once a month, you’re not a great customer. Sending you a reminder to get a haircut isn’t useful, but if we know what day the barber shop is slow, we can offer a percentage off if you go on that day. The shop gets a sale and the customer gets to feel like a VIP. Even if you’d have gone there anyway, this approach creates brand loyalty.” The end goal, Oh explains, is to have users who receive an offer and think to themselves, “How did they know I wanted this?” Tamecco is also using its technology to help businesses without physical locations. Yumenomachi, a listed company on the JASDAQ that operates popular food delivery portal Demae-can, enlisted Tamecco’s AI to increase its online content engagement with consumers. Oh explains that the company would send a huge number of email magazines each day. “On their very best day, maybe half would get opened. Of that, maybe half would actually click a link. Then a half of that – again, on the best day – actually transact on the web portal. That’s down to an eighth of recipients.” Tamecco used its AI to analyze things such as which items customers order the most often, how often they ordered, what areas were generating the most orders, and what kind of trends emerged when examining trends in the food delivery domain at large. In the end, the startup was able to reduce the number of email magazines by more than 30 percent. Despite casting a smaller net, the startup was able to increase the open rate by targeting recipients with tailored offers. “Between January and April, we increased actual transactions by a double-digit percentage,” Oh says. Tamecco offers flexible payment options for partner merchants. Some opt for fixed membership fees, while others opt for a revenue sharing model. In the case of revenue sharing, Tamecco doesn’t get anything unless they increase traction. The service is completely free for individual users. Oh, a former investment banker at Citigroup Capital Markets, has cultivated a diverse 10-member team – about half Japanese and half non-Japanese – and a star-studded board and advisory panel that includes Koichiro Tsujino, the former CEO of Google Japan, and Paul Kuo, the former CEO of Credit Suisse Japan. With a computer science degree under his belt and fluency in Java, C, C++, Prolog, Lisp, Cobol, Fortran, Assembler, and “several other old-school” programming languages,” Oh wrote the first prototype of Tamecco himself in early 2012. He ran it on his iPad and showed it to Tsujino, who was immediately interested. The CEO went to work, taking as many meetings as he could to secure the first 50 merchants. With the AI still in development, Oh recalls helping a client analyze how many people who took its paper loyalty cards were actually using them: “We had a backup staff at our headquarters who’d view the security cameras that ran during lunch and business. She’d spend four hours a day reviewing the footage with two hand clickers – one for how many customers entered the shop and one for how many used the stamp card.” In May that year, the beta version of Tamecco went live. In the beginning, users had to scan QR codes to opt in to offers. Oh and his co-founders kicked in their own money to launch the MVP themselves. Oh says that Tamecco’s current monthly active users number between 30,000 and 40,000, with the number increasing 15 to 40 percent month-on-month over the last five and a half months. He connects the higher end of that monthly growth to the rapid implementation of Tamecco service with nationally-branded merchants like Yoshinoya. Oh adds that another important figure is the startup’s total digital reach, including the 6.5 million monthly active users on Yumenomachi, and the 500 daily transactions at each of Yoshinoya’s 300 beef bowl outlets in Tokyo alone. All of Tamecco’s nationally-branded merchants are using the startup’s wireless signal technology. About half of the local mom-and-pop shops using it are still using QR codes, but Oh expects to completely transition them to signal tech by the end of 2015. While some may consider the existing, and very fragmented, loyalty space in Japan to hold a number of potential competitors – such as Rakuten Super Points, T-Point, Ponta, and myriad merchant-specific apps and physical point cards – Oh considers each of those services to be potential collaborators. “[They] can simply join the Tamecco ecosystem, as in the case of our current merchants, or directly implement our technology onto their own apps or platforms,” he says. “ Either way works, as it helps our AI engine’s predictive models to get even better.” Tamecco was completely bootstrapped throughout its first year, then raised approximately US$1 million from a combination of personal investments by team members, Kuo, and other high net worth angels in the tech and finance world. A second seed of roughly the same size was provided by Yumenomachi in March 2014. The startup is currently gearing up for a sizable series A round. “It’s not just about raising money, it’s important to find the right partners whose wheels are aligned in the same direction as ours,” Oh says.

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