Category: Startups

Scale or Fail: How to Build Processes and Mechanisms the Amazon Way

Scale or Fail: How to Build Processes and Mechanisms the Amazon Way

Founders discussing how to scale their business like amazon

Photo by Austin Distel on Unsplash

Guest post by Richard Howard, AWS Startup Business Development 

“Scaling” is a term that’s ubiquitous in the startup world. Founders are always talking about how they scaled up their infrastructure to cope with a spike in usage or why they scaled up their hiring after a big round of fundraising. On the flip side, founders also bemoan having to let people go because they couldn’t “scale with the business.”

Despite founding my own startup several years ago, I ironically learned how to scale as a business development manager at Amazon, a little company that employs over 500,000 people. I want to share my journey with you, as not understanding the basics of scaling can be the death of your startup.

I started at Amazon’s Web Services division (AWS) roughly three years ago after six years at various startups, including my own. All of those startups were at the very early stages when I joined—a time when the axioms “Getting sh*t done” and “Done is better than perfect” are most apt.

When I started, the AWS EMEA Startup team really did operate like an early-stage startup. There were around 12 of us, sprinkled throughout EMEA to cover all of the startups on two and a half continents. We were encouraged and goaled on meeting as many startups as possible in order to help them and influence them to use AWS. Our jobs were incredibly broad and somewhat ambiguous and I loved it. It was the perfect combination for a former CEO.

When the team and our ambitions grew, we needed to become more “Amazonian” and create processes and mechanisms that meant that we could work with the ever-increasing number of startups in a more scalable way.

Because of my years of just getting it done, I was stuck in the old way of doing things. It was comfortable, and I loved meeting and helping entrepreneurs. What I’d failed to realize, however, was that to be really successful and help as many customers as possible, I needed to scale the impact I was having.

How does this apply to founders? The endorphin rush that you get from successful one-to-one customer interactions won’t sustain your startup, no matter how great it feels in the moment. You need to constantly be thinking about how to inject scalability into what you’re doing.

Set a breaking point

Startups are all about having hypotheses and testing them out. It makes sense to do things that don’t scale at the beginning. Brian Chesky went to New York to take photos for early Airbnb customers. Whilst it might not make sense just yet to process-ize what you’re doing, you should give yourself a target—whether that’s total number of users, growth numbers, revenue numbers, or something else—that is the point at which you’ll remove yourself from the process and make it truly scalable. And you should be thinking the whole time about what this process will look like when it’s implemented in a scalable way. How are you actually going to do it? Do you need to hire more people? Can it be automated? Can you outsource it?

Apply trial and error

Despite how much you think about what your new process is going to be, it’s unlikely that you’ll hit a home run straight away. Don’t feel too married to the new process if some of it isn’t working. Experiment, iterate, and improve until you’re truly happy with how it’s working. Also, know that even though your latest plan may be working well at the present, it might need changing all over again when you hit that next growth curve.

Expect discomfort

It feels great to speak to customers directly and get immediate and actionable feedback. But doing that is only going to feel great right up until the point that your startup dies. I was lucky that I was at Amazon when I learned this lesson and could take my time. If you’re running your own startup, you don’t have that kind of time.

If you really love the direct interaction with customers, putting a layer of process between you and them will feel unnatural and it’s going to make you feel removed from what you used to think of as the ‘pulse’ of your business. But it is absolutely critical if you’re going to scale up successfully.

Keep your hands dirty

Adding scalable processes doesn’t mean you stay away from getting your hands dirty and can never speak to customers ever again. It just means that you’ve recognized that to truly service as many customers as possible and grow your company, you’re going to need to stop doing everything so manually. Don’t worry though: your startup is never too big for you to still occasionally get involved in the nitty gritty. After all, if Deliveroo Co-Founder and CEO Will Shu can still make deliveries every fortnight, you can do some heavy lifting as well.

Conclusion

Pulling yourself away from customers can be a scary proposition for any founder. It’s where you really have to trust the people you’ve hired to relay the passion for the product that you have. But if you’re going to scale and become the kind of company that you want to be, then it’s imperative to do it. Building processes and mechanisms are just part of your startup growing up. This applies across the board from customer interactions to hiring to infrastructure.

The need to scale up on these things is a sign that something is going right at your startup. Embrace it. If you implement the processes in the right way, it can be an incredible growth engine in itself and allow you to focus less on the day-to-day and more on the future. And remember, just because you’re scaling up doesn’t mean you should’t get your hands dirty every now and then.

from AWS Startups Blog

Hospitality, Innovation, and Alexa: A Chat with Volara’s David Berger

Hospitality, Innovation, and Alexa: A Chat with Volara’s David Berger

 

In January 2016, entrepreneur David Berger was getting badgered with questions by a guest staying at one of his Airbnb apartments. Frustrated, he told a colleague that Amazon Alexa, the virtual assistant that had been launched over a year prior, should be the one answering his guests’ questions on voice command. The idea stayed with Berger, and after some initial research and development, he developed his first such product —  named Volara – and installed it in his own apartment. His guests loved the experience of engaging with his solution. “They got what they wanted more efficiently, and they were bothering me a whole lot less,” says Berger. “It was then that I realized I had a business that could provide a demonstrable ROI.”

Today, Volara – led by Berger as its CEO and Founder – is building voice interfaces for leading hotel technologies, while providing hotels the software to manage conversations with their guests at scale. Volara is also the Official and Exclusive Partner of Marriott for pilots of voice technologies. We recently spoke to him about how his company innovates, what trends he’s seeing in the hospitality industry, and why he considers Volara a security company first.

Give us the elevator pitch for what your company does.

Volara, the voice hub for the hotel industry, is providing real time conversation management and secure integrations atop Amazon Alexa for the hotel industry. We’ve turned Alexa into a business tool for hoteliers. Our goal is to manage Alexa devices in every hotel across the globe, breathing new efficiencies in hotel service and delighting guests at every turn. Recently, we surpassed 10,000 devices under management, developed 40 powerful technology integrations, and established partnerships with the largest hotel brands in the world, including Marriott International, Viceroy Hotels & Resorts, Two Roads Hospitality (now part of Hyatt) and Melia Hotels.

What trends are you seeing in your industry?

Guest expectations are continuously increasing and hoteliers are being asked to do more with less. Voice technologies like Amazon’s Alexa enable hoteliers to serve guests more efficiently driving new revenues for the hotel and building loyalty with travelers. Recent usage data tells the story: 82 percent of weekend guests and 60 percent staying on weekdays are engaging with Volara’s voice assistant solution. If a guest engages once, he or she is likely to engage eight more times during that night. On our client’s properties , thirty percent of all guest requests for items and services are now being made available through Volara-powered Amazon Alexa devices.

How do you collaborate with your customers?

The better we understand our customers’ business objectives, the better we can tailor our technology solutions to achieve those objectives. For example, in collaboration with the Motif Hotel Seattle, Volara built a staff-facing set of interactions that enable hotel staff to do their jobs more efficiently. In collaboration with the Fairmont Scottsdale Princess, we enabled live interactions between top tier guests and the professionals at the hotel who serve them. In collaboration with the Westin Buffalo, we brought guests personal music playlists to the guestroom further differentiating service that this hotel offers. Building atop the AWS platform has given Volara the stability and ease of management that is required in today’s fast-moving technology landscape.

What AWS services are you using and what benefit are those services providing to you?

Volara leverages a host of AWS Services, including hosting and fleet management APIs that enable precise control over Alexa devices within our management.

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

I often describe Volara as a security company first and a voice solutions provider second because our technology provides the enterprise-grade software that establishes the guest privacy protections and data security that the largest hotel enterprises in the world require. Volara ensures that recordings of guests are never associated with their personally identifiable information. It ensures that all recordings of guests are deleted within 24 hours – a distinct difference from the management of user recordings in the consumer environment. It also ensures that any hotel technologies that enhance the voice-based experience are securely integrated, that is, there is no leakage of hotel proprietary data.

What do you wish you knew when you were starting your company?

Creating a new category of technology (particularly in the hotel enterprise) requires an education cycle that is different from consumer technologies. It takes time and elbow grease, but the reward –being recognized as a business-critical partner for the largest hotel enterprises in the world – is worth the effort.

from AWS Startups Blog

How to Make Your First Technical Hire (If You’re A Non-Technical CEO)

How to Make Your First Technical Hire (If You’re A Non-Technical CEO)

Photo by NESA by Makers on Unsplash

Guest post by Richard Howard, AWS Startup Business Development 

When I founded my startup in 2014, I was the very definition of a non-technical CEO. As somebody who’d been in finance and then in commercial roles at a couple of startups, engineering, to me, was basically witchcraft. Luckily for me, my co-founder, who I had worked with for over a year at a different startup, was a great engineer. Together, our skills balanced out and because we knew and trusted one another, we were able to approach our startup did so as equals.

Looking back, I totally lucked out with my co-founder, but have since heard dozens of stories of non-technical founders that either couldn’t find a technical co-founder, or worse, picked the wrong one. I wanted to write a guide for those that weren’t as lucky as me. How do you build a product and hire technical talent when you’re a non-technical founder?

Don’t be that person

There are lots of places, like Workinstartups or techcofounder.com where you can try and find a technical co-founder. What you don’t want to be is the person that posts something like “I have a great idea for a business. Just need a CTO to build the product.” You might as well write, “I have a great idea for a book. Just need someone to write it.”

How much more attractive would it be to instead say to a potential CTO, something like: “Got an MVP built, , and  first customers are onboarded and spending money. Now looking for somebody to help build out additional features and scale up the product.” Good engineers have hundreds of potential options of places to work. If you want them to work with you, you’re going to have to show that you can get stuff done whilst they are writing code.

Get something built

Reid Hoffman famously said that if you’re not embarrassed by your first product, you released it too late. At the very early stage, you’re not trying to prove that you have a beautiful product. You’re trying to prove that there is a market for the solution that you want to build. Prove that in any way that you can, even if it’s with basic tools. For example, I met a non-technical CEO last year who built a whole business on Whatsapp and Excel by himself. He proved that there was a market for his solution and now that solo founder has a team of eight.

If you really do need to build something at least somewhat technical to prove your thesis, don’t be afraid of hiring a freelancer or an agency. Just beware that you get what you pay for, quality-wise, so look for recommendations from people that you trust and set up milestone payment plans. If you don’t have any good recommendations, you can find freelancers on Upwork or Fiverr. Price isn’t always an indicator of quality, but when it comes to engineers, the cheapest are usually the cheapest for a reason.

Don’t give away the farm

You’ve now built some variation of an MVP and got some paying customers on board. Great! Now it’s time to make that engineering hire. One mistake that non-technical founders make in this situation is getting so excited that any engineer would work for their company, they perform less due diligence than they would for any other hire. They also give away more seniority and equity than they should. Don’t skip over calling references just because you want someone in the door.

It’s also important that you’re realistic about the level of the engineer that you’re hiring. Your first hire shouldn’t automatically be made your Chief Technology Officer, unless they actually deserve that title. Engineer, Senior Engineer or Lead Engineer is a perfectly acceptable title depending on their experience. A CTO is a senior position that will (if everything goes well) have a lot of direct reports in the future. Is this person ready for that? Also, every engineer you hire in the future is going to have to go through some kind of coding assessment. As someone who is non-technical, you won’t be able to administer this yourself. But if you have a friend that is an engineer, it would make sense to ask them to perform this function for you to assess the skill level of this potential hire.

You can lose a lot of time with a bad engineering hire, particularly if you give them co-founder/CTO status. Make sure any equity you give has a standard four-year vesting period and if you don’t think the person is ready to be CTO, be honest with them as to why. And if you think they deserve it, show them a path towards getting there.

Conclusion

Being a non-technical startup CEO of a startup puts you at a disadvantage at the very early stages because you can’t just put your head down and build product. Accept that fact and supercharge what you can bring to the business,  whether that’s sales, marketing, or fundraising. Be realistic in assessing any engineering hires against the role they will perform if you grow to be a 50-a 50 person company. And finally, if you can prove that there’s a market for your solution without building something too complicated, do it. And do it now.

from AWS Startups Blog

How OAG Analytics Leverages AI and Machine Learning to Optimize the Profitability of Oil and Gas Wells

How OAG Analytics Leverages AI and Machine Learning to Optimize the Profitability of Oil and Gas Wells

OAG analytics well drilling

The U.S. surpassed Saudi Arabia as the world’s largest oil producer, while also achieving the lowest emissions levels in 25 years due to natural gas replacing coal fired power plants. The Permian Basin in West Texas is the largest unconventional oil field in the U.S. and is on track to produce more oil than Iraq by 2020. Because of our abundant supply of natural gas, the United States is now also the leading exporter of natural gas to other countries that still run on coal, expanding our role in rapidly reducing carbon emissions on a global scale. A thriving energy sector in the United States will have positive implications worldwide. Unconventional development combines horizontal drilling with multi-stage fracking and helped set the U.S. oil & gas industry on a trajectory to fulfill 58% of global fuel demand growth by 2020. Unconventional development also introduced more complexity into planning and operating wells, requiring new tools that analyze more data to maximize profitability.

“Full-stack unconventional oil and gas fields, like the Permian, are massively complex systems,” says Luther Birdzell, founder and CEO of OAG Analytics. “Drilling miles deep and miles across the earth, pumping millions of pounds of sand suspended in tens of thousands of barrels of fluid at high enough rates and pressures to break up solid rock generates a lot of complex data and, when done well, a lot of oil, gas, and dollars.”

The logistics of planning a single well are very complex. Field development planning exponentially increases that complexity with decisions such as where to drill, how many wells to drill, well design, cost, and space between wells. Advanced analytics and cloud compute enable oil and gas companies to evaluate more scenarios to improve drilling unit economics.

“Many upstream experts over the past six years have shared that there are 3,000 to 5,000 variables that affect the production of an oil and gas well,” says Birdzell. “In the best case scenario, we have 300 useful columns of data, and it’s usually closer to 50. Most geophysicists and engineers know the approximate order of the top eight to ten production drivers, OAG helps them quantify and isolate the contribution from each of these drivers, creating new subsurface insights. AI and machine learning identify new opportunities to de-risk the subsurface, increase production, and reduce D&C costs by finding complex relationships within the data that we humans cannot.”

In 2013, Birdzell saw an opportunity for AI and machine learning to deliver unprecedented value to the oil and gas industry. He formed OAG Analytics to create an AI platform that enables oil and gas companies to use more of their data to help solve critical problems like well spacing.

“Our mission is to facilitate collaboration between data scientists and oil and gas subject matter experts,” says Birdzell. “These teams have data trapped in different silos, relying on legacy desktop software to help them analyze different pieces of the puzzle.” The OAG-Amazon SageMaker integration enables customers to unify their datasets and create proprietary analyses using virtually unlimited compute. “Standardizing on SageMaker creates an ideal collaborative environment with our customers. It enables them to get value from these complex technologies quickly with out-of-the-box OAG AI Apps including Well Spacing and Predictive Maintenance and the option to add their own proprietary IP in the future. This unique balance of power and extensibility helps customers break down data silos and improve strategic decisions that impact their balance sheets and reserve reports.”

Unlike consumer-centric AI and machine learning applications, think Google ads and Amazon product recommendations, that automate billions of trivial decisions per day, large oil and gas companies typically make hundreds of decisions per year that impact billions of dollars. “Fields are commonly delineated into 1-2 square mile drilling units, each of which costs approximately a hundred million dollars to develop,” says Birdzell. And in today’s tighter commodity market, the margin for error in capital allocation is dangerously thin. “Until recently, companies relied heavily on trial and error to improve well spacing, which was good enough at high commodity prices. The current low price environment is tightening capital and rewarding innovation.”

Birdzell compares these market conditions to the breaking of the dot-com bubble in the early 2000s, when investors started restricting their investments to companies with a credible path to profitability. It’s an apt comparison, and Birdzell should know: He got his start as a software consultant to Fortune 500 companies in what he calls “the last wave of dot-com development.”

Birdzell learned a crucial lesson: If you want to create value in a high-stakes environment, you have to empower your customers. “It’s about democratizing solutions to critical problems,” says Birdzell. “If you can take something really complex and make it point and click, you can create new markets. Done correctly, this approach scales across large enterprises and maximizes value creation.”

This is especially important for the oil and gas industry, which has historically been slow to adopt new software technology. But Birdzell points out an important caveat to that claim: the industry has also been fast to follow. “EOG and Anadarko are two examples of companies that have proven the value of applying AI to oil field economics by building their own platforms. OAG takes the years of development and tens of millions of dollars of cost out of the equation, enabling companies to get more value more quickly. OAG has helped several of the top 20 U.S. operators use AI to improve their economics. This success is gaining attention and motivating more companies to ask if OAG can help them too.”

from AWS Startups Blog

Movable Ink Helps Marketers Leverage Data and Overcome Content Bottlenecks

Movable Ink Helps Marketers Leverage Data and Overcome Content Bottlenecks

Guest post by Dee Anna McPherson, Senior Vice President of Marketing at Movable Ink

Every day, we upload 1.8 billion digital photos. We like 4.2 billion Instagram posts And by 2021, video will make up 82 percent of all internet traffic. There’s no doubt about it: in this “Instagram Era,” visual is the language that moves people.

Dee Anna McPherson

Consumers crave those visual experiences at every marketing touchpoint. But not just any visual experiences: consumers expect visuals that are unique and relevant to them across every channel and every moment. And that leaves marketers with a huge—and all too common—challenge.

Leverage data-powered visuals to overcome the content bottleneck

Marketers understand the impact of unique visuals. For them, the challenge is creating those visuals for their customers at scale. Most marketing teams don’t have the time or resources to create countless variations of their campaigns. They could either create personalized experiences for small segments in a non-scalable way, or they could create generic experiences for a broad audience.

This is where Movable Ink comes in. We help marketers create compelling visual experiences based on all data relevant to the customer that is unique at every moment of engagement. To do this, we make it possible for marketers to easily source, integrate, personalize, and reformat content for email, web, and display from a variety of brand, product, social, and third-party sources.

The types of data can include products that customers have recently browsed on the brand’s website, real-time pricing and inventory, customer preferences, and much more. Depending on a customer’s behavior, preferences, or contextual triggers (like location or weather at the moment of open), Movable Ink can automatically generate the appropriate creative from any of these sources at the moment of open. This process incorporates large and unpredictable amounts of data from a wide variety of sources, making the scale, elasticity, and connected nature of AWS a logical fit. To meet these challenges, Movable Ink migrated its entire production environment to AWS in 2015, taking advantage of multiple regions and availability zones to provide redundancy, resilience, and scalability. As a result of the partnership between AWS and Movable Ink, we’ve seen $15,000 in cost-savings per month, and a performance increase of 50%.

With our platform being hosted on AWS, we store millions of files and serve them to hundreds of millions of users. This makes it incredibly easy for our clients to quickly deliver and scale these email experiences to their end consumers.

These moment-of-open capabilities are a necessity for elevating the customer experience. For example, imagine seeing a great low fare on a flight, only to click through to the website to find that the low fare has already expired. Not the best experience. Movable Ink can pull in pricing and inventory at the moment-of-open so the customer always sees accurate, up-to-the-second information.

Under Armour Product Recomendations

Under Armour Product Recomendations

Activating data is another challenge we help our clients overcome. Our client, Under Armour, is a great example of this. Under Armour needed to not only activate their customer data, they also needed a way to use that data in their campaigns that would allow them to create personalization at scale. By partnering with Movable Ink, they were able to use their website as a content source and pull data directly from their ecommerce site where customers were interacting in real-time. Now they can automatically generate personalized creative for each customer at the moment of open. Their product recommendation campaign, which pulls personalized product recommendations for each customer based on recent purchases, saw a 132% lift in engagement.

And that’s just one of the many ways Movable Ink helps companies leverage their data to overcome the content bottleneck and create personalized visual experiences at scale.

Use automation to streamline campaign production

Because Movable Ink generates personalized creative automatically, one of the biggest benefits our clients see is streamlined campaign production. Not only can these marketing teams better leverage their investments in data, but the time they save on production also allows them to focus on higher-level, strategic campaign planning.

Sam’s Club, for example, used to have a manual production process that could take up to 16 hours to deploy a single campaign. Once they partnered with Movable Ink, they reduced that production time to under four hours. Now the marketing team can get campaigns out the door faster and have increased flexibility to meet the company’s ever-changing business needs.

Partnering together to ensure client success

Overcoming the content bottleneck is a widespread challenge for marketers, who are expected to meet their customers’ needs at every touchpoint. It’s a tall order for sure, but it’s something we help our clients achieve every day. Our partnership with AWS helps ensure that email campaigns reach their consumers in the most reliable, secure and efficient way possible. To learn more about Movable Ink and our partnership, email us at [email protected]

from AWS Startups Blog

OMQ Is Automating Inefficiency Out of Customer Service

OMQ Is Automating Inefficiency Out of Customer Service

OMQ signage at their officesCustomer service can be tricky and tedious—both for those trying to get answers and those trying to provide them. More often than not, a person who calls or emails a business for help with its product or service has a question that has been answered many, many times before. And yet, there can be a great deal of inefficiency standing between the customer and what will turn out to be a simple, preexisting answer: long wait times, badly designed websites, and the endless variation in ways that people ask about and describe identical problems.

Matthias Meisdrock became acutely aware of these problems at his first job where, he says, he “heard the company’s service employees in the office next door answer the same customer questions with the same answers over and over again.” That experience “gave rise to the idea and goal of developing a software that would automate these service processes.”

In 2010, Meisdrock and Sven Engelmann founded OMQ GmbH with the goal of creating artificial intelligence software capable of understanding and responding to customer inquiries in real time. The Berlin-based startup developed its technology in cooperation with several partners, including the German Research Center for Artificial Intelligence and the Universität Heidelberg, with whom they worked on AI projects focused on natural language understanding and deep learning.

No matter what industry a company is in, OMQ’s software is designed to assist with customer service through multiple communication channels. Describing the product OMQ Contact, Meisdrock says, “As soon as a customer enters a question in the input field, suitable answers appear in real time next to the form. In this way, the customer’s question is automatically answered before it is sent to customer service.”, providing fast support and frequently avoiding the need to generate a customer service ticket. Similarly, OMQ Reply provides a self-answering email system that recognizes recurrent request and answers them automatically. The answers are entered in a ticket and marked as closed.

As the AI fields more requests, it gets better at recognizing when vaguely or confusingly phrased inquiries are in fact common questions to which it has an answer. Meanwhile, OMQ Help functions as “a dynamic FAQ,” moving answers to the top of the page according to what questions customers are currently asking most often (say, during a seasonal promotion), and guiding visitors to solutions via an intelligent autocomplete navigation system.
The OMQ Chatbot automatically asks queries if there are several possible answers or connects the customer with a service agent if the question is too individual. The holistic OMQ System uses the same knowledge for all communication channels and all products learn from the requests and feedback of the other products.

OMQ is still actively following the latest AI research and looking for innovations to integrate into its products. Most recently, it began implementing an attention-based transformer model, which is pre-trained on general text data and then fine-tuned for customer service data, allowing it to classify new, previously unseen requests without explicit training. Meisdrock says that, as a lean startup, OMQ has “worked without the help of investors since its inception” and “takes great care to quickly introduce and establish the software on the market,” gaining and maintaining customers through testing and iteration. With over 100 clients and 930,000 processed requests per month, Meisdrock says that OMQ is moving toward its vision of “answering every kind of service request only once, or [in other words] automating 100 percent of customer service.”

from AWS Startups Blog

How Unicheck Helps Academic Integrity Thrive 

How Unicheck Helps Academic Integrity Thrive 

Diagram example of how the unicheck platform prevents plagarism

Serhii Tkachenko, CEO of Unicheck, likes to think of the plagiarism prevention software as the ideal “topping” for any learning management system’s basic “pizza.” While learning management systems—such as Canvas, Blackboard, Brightspace, and Google Classroom—are platforms where students and educators can perform all course-related tasks and communication in one place, adding Unicheck makes the learning and teaching experience even better and more effortless.

“Our main goal is to automate all manual tasks for students and educators and give them more time for learning and teaching,” Tkachenko says. Unicheck accomplishes this by automatically checking every submitted assignment for plagiarism, providing a comprehensive similarity report in just four seconds per page. Instructors can then view the percentage of similarity between a student’s assignment and online sources (including open access journals and repositories), as well as the institution’s internal database (which includes other current class submissions).

The “Uni” in Unicheck is meant to get you thinking: United, Unique, Universal. But the company was originally known as Unplag when it was founded in Ukraine in 2014. At that time, Tkachenko says, “We started this development but we were rather technical driven, without any community, without the communication with our customers. It was super hard to sell our software even if it was free.” After rebranding itself as Unicheck in 2017, he says, “we changed our vision, our mission—and our mission right now is to create community-driven software that makes students well educated. Our vision is to help to support institutions worldwide to make their level of academic integrity thrive.” Once the company began implementing that new vision and mission in its development and marketing, it grew by 300%.

Such rapid growth was what pushed Unicheck to move to the public cloud in order to stay ahead of its competitors and continue meeting the demands of a higher volume of customers. “When you have like 100 customers,” Tkachenko says, “it’s super easy to check all students’ submissions, but if you have 1 million students, it’s hard to have really great availability in terms of checks. Our competitors, when students submit a paper, provide results in 24 hours, and we understand that, for our customers, is super long. We provide results in five minutes.”

Although it currently serves 1.5 million students and 100,000 educators from over 1,100 institutions in 69 countries, Tkachenko emphasizes that Unicheck’s customers are not institutions, but people: students, educators, IT staff, and administrators, each with different needs that Unicheck fulfills.

For example, for IT staff, Unicheck provides a seamless integration and 99.9% system uptime. For administrators, who often have strict budgets, Unicheck strives to keep its software cost efficient. For students, Tkachenko explains, “we are trying to develop software that is easy to use and help them with their writing skills. We’re trying to work with citation and reference, and help them find improperly cited material and show them how to cite it properly. For educators, we are trying to save time for them [so they can] create a really great educational process.”

Tkachenko clarifies that the purpose of plagiarism prevention software is not merely to catch cheaters so they can be penalized. Instead, they want to help educators identify and find a solution for “problematic students” early on. Often, Tkachenko says, these students “are not trying to cheat because they want to cheat. It can be that they don’t like this course, they don’t have enough time, they have some problems at home, and that’s why they’re trying to cheat. [For] educators, the main task is to speak with the student, realize the problem, and solve the problem,” in a way that benefits both the educator and the student. It’s this supportive, win-win mindset that makes Unicheck the “topping” that students and educators alike can enjoy.

from AWS Startups Blog

How Sisense and Periscope Data Are Helping Data Builders Grow in New Directions

How Sisense and Periscope Data Are Helping Data Builders Grow in New Directions

Guest post by Erin Winkler-McCue, Lead, Platform Partnerships & Strategic Projects @Sisense

Answering questions with data is no longer just the responsibility of a small team of data professionals. It’s become a shared responsibility between multiple departments—and that’s true for companies of all sizes in every industry from every part of the globe. As a result of the data revolution, every job has become a data job, every team a data team, and every company a data company.

As data continues to gain momentum, every company has embarked on its own journey with data analytics. Different organizations collect and analyze different types of data to answer their own unique questions and no two are alike. Over time, as these companies have increased their analytics capabilities, they are making decisions that shape how they create value from all that business data.

A short overview of data maturity

Generally speaking, as our team surveys the landscape after the recent data explosion, we’ve seen two pretty distinct paths for teams to grow their data operations. Once a baseline is set where data from disparate sources is combined into a single source of truth, companies are choosing to prioritize either deeper data analysis or wider access to insights.

Some companies have gotten a taste of the value provided by central or hybrid data teams and are eager to bring in more data science resources. These teams are looking into ways to use the most cutting-edge data techniques to answer questions that no one even knew could be asked until the last few years.

For other organizations, the value of analysis is in translating data into actions for individual lines of business. Operationalizing data-driven insights to stakeholders, customers, and the world at large is an important part of this process, but it’s also crucial to give those audiences the power to access datasets and dive into the information about their work.

These two approaches aren’t opposed. They’re complementary, as far as the value they provide to a business. It’s important to understand that expansion in either width or depth is still positive growth and neither direction is objectively superior. Ultimately the choice about which direction to mature goes a long way toward determining which questions a business can answer with data and who will benefit from those answers once they are found.

Sisense + Periscope Data: merged to accelerate

Until recently, it’s been incredibly difficult to advance business data analysis in both directions at once. The teams at both Sisense and Periscope Data heard this feedback in communications with customers. Our customers told us that it takes a full-time data team and a hodgepodge of solutions crafted into a workflow to do just one right; moving forward on both fronts would drastically increase the amount of resources needed and it’s not realistic to take on that project.

It’s in the Sisense DNA to be customer-focused. Our company’s leaders were eager to grow their data operations wider and deeper. It’s well acknowledged that stacking more gizmos into an already-full grab bag of point solutions is not a sustainable way to achieve that growth. With our recent merger, we wanted to build something for customers that allowed them to manage that bidirectional evolution all in one place.

Historically, Sisense offered a BI tool that was perfect for enabling business users to upload their own data to analyze via a friendly drag-and-drop interface. Periscope Data was a tool recognized as extremely powerful for advanced analysis, with support for SQL, Python, and R all in the same environment. After a little consideration, both leadership teams concluded that merging the two products together was a natural step in building the tool that data-hungry teams at both customer bases were craving.

Unifying data builders of all types

No matter how mature a company is with their analytics, we’ve entered an age where data is the primary input for every project on every team. Builders of all data abilities are using their business data to shape the future for their company.

With Sisense + Periscope Data, businesses will receive a single end-to-end analytics platform, capable of benefiting every builder. The data scientists and engineers instantly gain complete control over more sophisticated analysis projects. They can use powerful querying languages that are in their toolkit and translate those insights on to citizen data scientists via actionable AI-powered apps.

With the combined product, every builder is using the tools that they are uniquely suited to wield and creating new things with data that will give them a serious competitive edge over their competition. This merged platform brings together the best technology for every use case and makes it easier than ever to democratize insights mined from complex data.

This full-spectrum platform was a part of the pre-merger roadmap for both companies, so joining forces accelerates how quickly that dream turns into reality. We’re thrilled to see what our customers can create with a powerful analysis and a true collaboration-focused tool. We keep a very close eye on how the builders at Sisense and Periscope Data create value out of their data, and we just gave them a vastly upgraded toolkit! With the power to grow their data capabilities wider and deeper at the same time, the landscape for builders is wide open and ready to be conquered.

from AWS Startups Blog

In Case You Missed It: AWS Summit 2019 in New York City

In Case You Missed It: AWS Summit 2019 in New York City

Throughout 2019, AWS held free Summits around the world aimed at bringing the cloud computing community together to connect, collaborate, and learn. From San Francisco to Bejing, thousands of technologists gathered at these day-long events to hear from AWS leadership, as well as to meet and network with the wider industry.

At many of this year’s Summits, the AWS Startup Team set up dedicated theater and technical spaces for founders and entrepreneurs. Dubbed “Startup Central,” these areas featured a walk-up bar where attendees could gain insight from expert AWS Solutions Architects, as well as a stage for members from the local community to give talks on interesting technical challenges they’ve faced and overcome.

Below are the startup talks from at the AWS Summit held on July 11th, 2019 in New York City. From using ML and Amazon SageMaker to analyze financial documents to leveraging Lambda in a variety of ways, the talks were wide-ranging and drew quite the crowd.

Giving Users Shell Access and Feeling Good About It

Leveraging an AWS Stack to Predict Patient Risk

How AWS Enabled Timehop to Quickly Spin Off a New Line of Business

Active Learning on Kubernetes and Amazon SageMaker

 

Data Wrangling: How Abacus Insights is Democratizing Healthcare Data

How Frame.io Develops Complex Security Workflows in the Cloud

How Amenity Analytics Does NLP and ML Using Serverless Infrastructure

AWS Lambda for All the Things

from AWS Startups Blog

Regulation Solutions: FMG Suite Reduces Risk for Financial Institutions

Regulation Solutions: FMG Suite Reduces Risk for Financial Institutions

In 2019, it’s a cliché to point out that consumers are constantly surrounded by marketing. Texts, tweets, DMs, and emails fill our ever-connected, internet-driven daily lives, and businesses—including the financial services industry—have found their way into all those spaces. In fact, the 2018 Putnam Social Advisor Survey found that social media is significant to the current marketing efforts of 86 percent of financial advisors, and 92 percent of the surveyed advisors said they gained new clients through social media, an enormous increase from 49 percent just five years prior.

Headshot of Scott White CEO of FMG Suite

Scott White, CEO, FMG Suite

Given the ubiquity of all that contact and the public-private virtual spaces in which it traffics, consumers expect streamlined accountability from businesses. FMG Suite, a marketing technology company based in San Diego, has positioned itself to meet those expectations for the financial sector. “We occupy a unique position in the industry as it relates to solving marketing technology challenges for their enterprise clients,” says CEO Scott White. “Our marketing technology platform was built from the ground up for financial advisors and their broker-dealers.” FMG Suite builds websites, runs email and social media campaigns, and provides marketing coaching and support for over 40,000 financial advisors. And because the company is laser focused on finance, it knows how to work through the backend complexities of financial marketing: regulations.

“Marketing in regulated industries is hard. This is particularly true in the financial services industry,” explains White. “Between guidelines from FINRA, the SEC, and other US regulatory bodies, financial organizations looking to market their products and services must navigate through a morass of rules and regulations.” And as regulatory agencies have adapted their approaches to cover the expanding avenues through which businesses communicate with consumers, financial advisors must meet strict standards governing emails and social media interactions. Breaking the rules comes with serious repercussions: in 2018 alone, FINRA collected $61 million in fines and barred or suspended over 800 brokers across the United States for violations.

FMG Suite was created to provide comprehensive marketing tools custom-fit for the financial industry, and this gives the company a leg up in designing solutions to meet regulatory needs. “We understand the importance of helping marketing, compliance, and information security functions within organizations work together through systematic innovations based on technology,” says White.

One particular hurdle for financial institutions is that they must maintain an auditable accounting of their marketing emails, which is trickier than it sounds. “Each client could potentially receive a different version of an email based on variables as simple as first name, or as complicated as credit scores and financial profiles,” notes White. “As the ability to automate the personalization of emails increases, this problem becomes even more chronic, and the systematic risk increases with every email sent.” He goes on to explain that “FMG Suite’s goal in trying to solve the email journaling issue was to build a solution that gave broker-dealers the ability to search, reconcile, and retrieve all email communications sent through FMG Suite’s marketing platform.”

The result? “FMG Suite successfully launched an industry-first email reconciliation system on top of its flagship marketing suite,” says White. Plus, FMG was able to design its solution efficiently, at scale, and without breaking the bank (so to speak). It’s good news for financial advisors, and it helps protect consumers, too.

from AWS Startups Blog