Tag: AWS Startups Blog

How SupWiz is Revolutionizing Customer Service with AI

How SupWiz is Revolutionizing Customer Service with AI

supwiz uses ai to improve customer service experiences

Take a second and think of an aspect of a business that really frustrates you. An aspect that you, and every other person, seems to have negative experiences with. What comes to mind?

Despite the variety of possible answers, the majority will likely have an underlying commonality: poor customer experience. Long hold times, answering the same questions over and over, weaving your way through a phone maze to find the right person to talk to. It’s annoying but seemingly unavoidable—at least for now.

Founded summer 2017, SupWiz is making that poor experience a thing of the past by delivering a customer service AI platform with e.g. virtual agents and chatbots that can understand customer request in the domain language of a given company and resolve issues to deep integrations such as resetting WiFi routers.

But what does that mean? These days it seems like every company is boasting their application’s “AI” abilities, when in reality what’s under the hood and behind the scenes, is far from cutting edge. In a field that has a lot of hand-waving, SupWiz stands out through a team with deep technical expertise and experience.

All companies have a founding story. Whether it’s having a difficult time calling a cab or trying to make extra money by renting out an extra bedroom, they must start somewhere. For SupWiz, this path traces its way back to academia. It wasn’t that long ago, when the now team of 20, was just a few researchers looking to make their next move, per Søren Dahlgaard, Co-founder and Chief AI Officer at SupWiz.

“The origins of SupWiz came from a desire to make an impact outside of academia. At the time, Mathias Bæk Tejs Knudsen (CTO and co-founder of SupWiz) and I were grad students completing our PhDs in computer science, with a focus on algorithms at the University of Copenhagen. Although we really enjoyed our time in academia, we felt that many of the projects that were being worked on would never have real-world applications.”

So the two of them teamed up, with a goal of building something real. One issue arose though, as both had deep expertise in the AI field, but lacked the experience of launching and scaling a startup. For this and more, they turned towards one of Dahlgaard’s academic supervisors Stephen Alstrup. Prior to his time as a professor, Alstrup co-founded and served as CEO of Octoshape – a video streaming optimization startup that was acquired by Akamai in 2015.

Headshots of the co-founders of customer service AI startup SupWiz

From left to right: Mathias Bæk Tejs Knudsen, Søren Dahlgaard, & Stephen Alstrup, Co-founders of SupWiz. Photo by Maiken Kestner.

Having secured a team with both deep technical expertise and founding experience, they were ready to make the jump. The next step? Figuring out what industry to jump into. While some founding stories are told as serendipitous events—like being frustrated with how difficult it was to call a cab – SupWiz’ story falls more in-line with their academic research background. The team took it upon themselves to attend conferences and ravenously read reports to understand where the largest opportunities were laying. One such report came from Gartner, which stated that 89% of companies believed that customer experience is their primary basis for competition. With a market selected, the team was ready to go.

But what does SupWiz do? Applying their years in the AI academic world, SupWiz set out to build a better customer experience for large companies. As Dahlgaard puts it, “When you look at the customer service industry, it’s really surprising how much of the work is currently being handled manually. Not only is that not very cost effective, but our technology can actually outperform the current manual methods in many ways. There is also a lot of repetitive work in this line of business, which is a perfect application for computers and AI to optimize.”

So that’s where the startup operates. For each new client, SupWiz first train its internally developed algorithms on the company’s existing data tuning it to the specific domain language. The customization is needed as e.g. ISP’s have different communication styles than banks, which have different styles than airlines – and so on. Once that’s done, the team deploys its AI platform to automate portions of the customer service process. This changes depending on the need of the company, but can for example include virtual agents and chatbots to automatically handle customer requests, identifying the right knowledge article for service agents, or automatically routing tickets to the right teams.

Dahlgaard points to this approach of training company-specific language models as a key differentiator for the startup. Leveraging that deep technical knowledge of SupWiz’ team consisting of 85% PhDs within AI, statistics, and computational modeling, SupWiz’ AI platform is able to understand highly domain-specific language and outperform the current methods used for customer service, automatically resolving 75% of customer requests.

And as for the customer service representatives that currently handle these tasks? They’re actually huge fans of the SupWiz, as it takes away the boring part of the job and allows them to focus on more interesting things.

Customer-wise, the 2-year-old startup works with companies across a variety of industries, including finance, insurance, telcos, and pharma benefiting millions of end-users in more than 149 countries. If you have a lot of inbound volume for your customer service department, then SupWiz is happy to chat. That said, the nature of their product and services typically means that the startup ends up working with companies that have dedicated customer service teams of 10-20 people and up.

To power its AI solution, SupWiz turned to AWS. The team was able to build their own framework from the ground up, which includes heavy use of AWS dedicated machine learning and GPU heavy computers. They also leverage Kubernetes to help deliver the SaaS application at scale. “AWS offers the best-suited infrastructure for our demanding machine learning algorithms in the right geographical regions, making it the perfect fit for SupWiz” notes Dahlgaard.

So, what’s next for the startup? Scalability, according to Dahlgaard. “As of now, each new customer requires a bit of hand holding. To grow globally we will need to make that process a bit more automated.” If the past two years are any indication, it’s not hard to imagine the company will have continued success in its field, and, hopefully, will decrease the amount of time we all spend frustrated at customer service reps.

from AWS Startups Blog

How Bustle Leverages AWS Lambda to Help Editorial Teams Scale

How Bustle Leverages AWS Lambda to Help Editorial Teams Scale

Bustle Media Group, a New York City-based company with eight brands under its umbrella, leverages AWS services to efficiently deploy content across its various brands. Nita Sitaram, Senior Director of Product Management, Zahra Jabini, Director of Product Engineering, and Tyler Love, CTO, sat down to explain how services like AWS Lambda help their editorial teams templatize and implement changes at scale while building and maintaining brand specificity.

from AWS Startups Blog

Imagining ‘Borderless Entertainment’ with Blockchain Startup SELF TOKEN

Imagining ‘Borderless Entertainment’ with Blockchain Startup SELF TOKEN

SELF TOKEN, a digital entertainment blockchain startup based in Taiwan, aims to create an “immersive entertainment ecosystem,” beginning by creating Asia’s first blockchain warfare film, The Last Thieves. Co-founder and CEO Jack Hsu, who also directed the film, explains how Self Token will release its own cryptocurrency, SELF, in tandem with the release of the movie. SELF will allow users to redeem tickets for The Last Thieves, as well as food and drinks at partnering restaurants and bars, thereby giving moviegoers an immersive experience. Hsu and the movie’s chief economic advisor, Dr. Tom Lam, sat down to tell us more about how the token works, why their blockchain technology is relevant, and what their vision is for the future of the Asian entertainment industry.

from AWS Startups Blog

Startups Helping Startups: Will You Help Another Entrepreneur?

Startups Helping Startups: Will You Help Another Entrepreneur?

As Reid Hoffman says, starting a company is like “jumping off a cliff and building an airplane on the way down.”  It’s hard. Very, very hard! And being an entrepreneur can be one of the loneliest places on Earth, especially when you’re staring down a challenge that you’ve never seen before and don’t know who to turn to.

That’s why AWS and Masters of Scale are partnering to create this unique opportunity for startups to help startups.  Think of AWS as the convener and yourself as having a piece of the puzzle that just might help another entrepreneur—someone very much like you—solve a BIG problem on the road to being, possibly, the next billion-dollar company.

Would you help if you could? Of course you would! We’re just making it easy. Below, please find some of the advice Masters of Scale listeners have been writing in to our entrepreneurs:

Entrepreneur #1: Eddy Lu

Eddy, the CEO and Co-Founder of GOAT (That’s “Greatest of All Time”), has a built a legendary marketplace for re-selling premium sneakers. That’s a very big business—and also a global one. International sellers kept joining the GOAT platform, wanting to sell, but Eddy knows that a global marketplace isn’t something you just step into like a self-lacing shoe. He needed to buy some time to get his platform ready and insure a seamless, delightful buying experience, despite the differences in laws, language and logistics across borders. So he made a waitlist for sellers outside the US. And that waitlist? It’s 35,000 members long. Eddy’s tried country-by-country solutions, but he’s not satisfied. Eddy’s challenge: To scale his infrastructure globally and meet that demand, with a holistic (not piecemeal) solution. Your challenge: To help him get it right, wherever a seller might be on the planet.

“Create a virtual inventory. The virtual inventory allows sellers to list their shoes from any region. Use the current AI method to authenticate the shoes. The virtual location allows everyone to sell everywhere no matter where is the warehouse is.”

– Julius Ho

“It seems to me that Eddy’s challenge is something many other retailers and even manufacturers face: how to handle the myriad of challenges in shipping across borders. It may be a platform option to provide this capability as a service.”

– Jose Solera

Entrepreneur #2: Chris Costello

Chris Costello founded Blooom to help ordinary Americans manage their single biggest retirement investment—their 401(k) retirement accounts. And if that just made your eyes glaze over, congratulations: You now understand Chris’ challenge. Blooom offers online financial advice for 401(k)s aimed at people who can’t afford their own financial advisor. (And that’s most of us.) His company has passionate early adopters, but the mainstream Americans who could most benefit from their work are the ones least likely to find them. Chris’ challenge: To reach beyond his base to find the customers who’d benefit from using Blooom but don’t know about it yet. Your challenge: To advise Chris on how to move beyond early adopters, and help more people realize their retirement dreams.

“One idea: recruiting events on campus and ambassadors. [The] retirement plan starts early, and these college kids are a great pool for outreach given their savvy-ness in tech! Also a win-win to get talent along with brand awareness.”

– Candice Li

“Two things: 1. Solve your Catch 22 (people won’t pay until they see value; won’t see value until they pay). Align with orgs that pay (e.g. library, coworking). 2. Attach to concrete events so people think of 401k when the event occurs (e.g. “first job”).”

– Chris Daming

“I think investment in 401ks should be taught in high school . School board funds should give each student (11th/12th grade ) a nominal amount of funds. Maybe $.100-200. Profits go to the school and their favorite activity to sustain both. Develop curriculum.”

– Melvin Cohen

 

Check out Masters of Scale for future epidoes—or to write in with your own advice—in our Startups Helping Startups series. 

from AWS Startups Blog

How Deep Imaging is Using Cloud Computing to Boost Oil and Gas Production Performance

How Deep Imaging is Using Cloud Computing to Boost Oil and Gas Production Performance

Deep Imaging uses cloud computing to optimize the performance of its oil and gas wells

Oil and gas operators are feeling the pinch. “Their wells are underperforming, so they can’t get enough oil out of the ground and they are missing financial forecasts,” says Josh Ulla, Chief Development Officer at Deep Imaging. “The scary thing is they often don’t know the root causes of what’s leading to well underperformance.”

Analytics are the life blood of the business world at large, but for the most part, they haven’t yet taken a strong hold in the energy industry. That’s where startups like Deep Imaging Technologies, which provides real-time fluid tracking services to the oil and gas industry, are coming in.

Founded in 2008 and based out of Tomball, Texas, Deep Imaging provides diagnostic tools in the oilfield so operators can identify the location and source of their problems in real-time, fix them, and get back to producing by tracking fluid movement in the reservoir during frac’ing, flowback and other types of injection. We recently spoke to Ulla, who joined the Deep Imaging team earlier this year, about wanting to improve the U.S.’s onshore production performance and how they’re using cloud computing.

What overall trends are you seeing in your industry and sector?

As the energy industry faces increasing pressure to improve their economics, we are seeing a shift to greater acceptance of incorporating new technology into workflows across the board to improve processes.

How do you fit into the oil and gas ecosystem?

We are the only company that identifies the what and where the problems are that are causing shortfalls in oilfield production. We identify frac hits, bad cement, plug failures, open zippers and other subsurface problems.  With this information operators can fix what’s wrong, get back on track and improve profitability.  Additionally, our diagnostic tools are a direct measurement of where fluid is actually placed—it’s precise and there is no guessing about what the results mean.

For example, we want our clients to feel extremely informed about the realities of their projects, so they can make the right decisions at the right times, improving day-to-day workflows, future project planning and overall bottom lines.  AWS cloud computing allows us to process very large data sets quickly so we can deliver results to clients in real-time.

What is the biggest challenge that you’ve faced in your current role and how did you overcome it?

A big (successful) challenge was advancing our frac diagnostic technology to deliver results in real-time.  To do this we are introducing on-site mobile units, automating data collection to collect results faster and processing on-site. We also are incorporating machine learning with human oversight to process results, increasing speed and accuracy. It has been an intensive process with a very successful outcome.

What’s one unique thing that most people don’t know about what your company does?

Most people don’t know that clients can also use our diagnostic tools to determine which products they use work, and which don’t, so they can improve their purchasing plans.  For example, we show them if a plug is failing, and if a certain type of plug fails, let’s say 20% of the time, then they know that it’s an inferior product and they should switch to a different plug for future projects.  It’s about tightening the ship—Identifying and addressing what’s not working.

from AWS Startups Blog

Enabling Cloud-Native App Builds with KintoHub

Enabling Cloud-Native App Builds with KintoHub

Developer workflow KintoHub enables developers to build cloud-native apps. Founder Joseph Cooper shares how trying to find the sweet spot between a gaming API development platform and GitHub eventually led to KintoHub’s creation. Cooper also talks through how customers use KintoHub,  how many startups he has founded, and what his thoughts are on the Hong Kong startup scene.

from AWS Startups Blog

Temi China and the Rise of Personal Robots

Temi China and the Rise of Personal Robots

Temi is a personal robot that hopes to revolutionize communication. CEO Gal Goren shares how temi’s autonomous nature allows for an improved user experience, like hands-free video calling or tight subject matter focus. He also walks through the depth of its integration with Amazon Alexa, what its use cases are, and why the time for temi is now.

from AWS Startups Blog

Castbox CEO on the AI-driven Future of Podcasts

Castbox CEO on the AI-driven Future of Podcasts

China and US-based startup Castbox, unofficially known as the Netflix of podcasts, allows users to stream live podcasts, engage with speakers, and upload their own premium content. Founder and CEO Renee Wang explains how the app works, who its main users are, and where she sees the podcast industry heading in the future.

from AWS Startups Blog

From Voice Messaging to Data Aggregation: How Measurable AI Keeps Its Founders Moving Forward

From Voice Messaging to Data Aggregation: How Measurable AI Keeps Its Founders Moving Forward

Diagram of Measurable AI platform providing real time sales and retention customer insights

Any entrepreneur worth her salt will tell you that to stay relevant in the tech marketplace, you need to be agile. Smart business leaders know to follow consumer demand, finding ways to use their expertise and experiences to tap into new product territories. After all, the failure rate for startups is roughly 80 percent—if you’re not constantly looking for ways to improve, you might as well bid your business career a fond farewell.

Heatherm Huang, founder of MailTime, and now Measurable AI, knows this well and has stayed ahead of the curve in his entrepreneurial endeavors, starting in 2011 with TalkBox, the world’s first push-to-talk messaging app. “I believe a push-to-talk feature is now already in every messaging app,” he explains, “but we were the first ones to do it.” The technology caught on quickly. “After two months, we became the number-one messaging app in China and in some countries in Southeast Asia.” That kind of innovation and rapid growth didn’t go unnoticed on the corporate stage, either. Huang explains that as result of TalkBox’s mass popularity, the company “got all these tech giants trying to acquire us, including social giants like Tencent.” The team declined the offers, and TalkBox was ultimately outpaced by subsequent voice-messaging apps. Still, the story of the company’s meteoric rise was so illustrious, it inspired a novel and a popular Chinese television series <Entrepreneurial Age>, known as the Chinese version of HBO <Silicon Valley>.

Ever on the move, by 2015 Huang had launched MailTime, an app designed to bring the ease and clarity of chat conversations to email. “In the year of 2014–15, it was the messaging trend, right? But people still need to use email, so we made email like chat. That’s how we got the first million users,” says Huang. In MailTime, email content appears in chat bubbles, stripped of the cumbersome metadata that usually accompanies it. Communications become conversations rather than threads, and recipients are easily looped in to ongoing chats. As Huang explains, “Email is actually the best protocol to do that, because with an email ID, you can actually reach anyone in the world. You don’t need to worry about what service the recipient is using.”

MailTime received glowing reviews, but rather than rest on their innovative laurels, Huang and his team began looking for ways to make the most of their product. They knew that given its expansive user base, MailTime was already managing a wealth of real-time information, and this sparked the idea for Measurable AI. Huang explains that nowadays when people buy consumer products online, including in-app purchases and subscriptions, they usually receive email receipts. “Basically, we aggregate all the email receipt data, like transactional data in the email receipts, make sure everything is anonymized, and then we turn it into consumer insights.” Plus, Measurable AI allows users to opt into this process, and those who do are compensated for the use of their data. “We launched a cryptocurrency called Measurable Data Token that we use to reward users for contributing,” Huang says. The result? Of their millions of users, over half have signed up.

While TalkBox and MailTime reconfigured the landscapes of voice messaging and email correspondence, respectively, Measurable AI is building a platform to provide its clients with hyper-current information about sales trends and product retention rates—information that’s in high demand by stakeholders but can otherwise take companies months to compile and release. “These days we are focusing on China, as well as Southeast Asian countries like Indonesia, Vietnam, Malaysia, Singapore,” says Huang. “We want to deliver what the clients really need.” Given his track record,it looks like he’s on to something big. The question is: What’s next?

from AWS Startups Blog