Isabel Alexandre

Meet CODE_n finalist LeanCiti

Eran Aloni

Eran Aloni is the CEO of LeanCiti

In line with the vision of a “Smart City,” LeanCiti enables people, municipalities, and communities to share any type of city-related data about resource consumption within a social network. The platform, created by the Israeli startup LeanCiti, uses big data to help cities and its residents make informed decisions, plan ahead, and use resources optimally. It is applicable in a variety of scenarios, from renewable energy production to water consumption, the reading of smart meters, or the measurement of greenhouse gas emissions. 

The startup was one of the CODE_n14 finalists and had the opportunity to present its project during the five days of CeBIT. In today’s interview, we talk to Eran Aloni, CEO of LeanCiti, about smart cities, their big data solutions, and how they experienced the time spent in the CODE_n hall during CeBIT.

Could you briefly explain how the smart resources platform LeanCiti works?

LeanCiti collects data from smart meters and smart devices that monitor energy consumption and production in smart city environments. We use social networks to change consumption behavior and study patterns, and also allow consumers, producers, and cities to share, compare, and define goals.

How do you encourage usage and get people involved with the platform?

Social engagement, environmental awareness, and gamification.

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Isabel Alexandre

Meet CODE_n finalist AutoGrid System

AutoGrid System is based in Silicon Valley, more precisely, in Redwood City, California. The American startup organizes the vast and growing amount of energy data produced from an increasingly networked and automated grid. With deployments of smart meters, distributed generation, and other grid sensing technologies reaching critical mass, the electricity supply chain now has to deal with greater data volumes than ever before. And AutoGrid is here to work on this problem, improving the production and consumption of electricity.

Amit Narayan, founder and CEO of the startup, explains to us a bit more about how the company connects big data and the energy industry. He also talks about their experience at CODE_n during CeBIT.

Amit Narayan

Amit Narayan, founder and CEO of AutoGrid System

How does AutoGrid use big data, predictive analytics, and cloud computing to optimize the electrical grid?

Autogrid organizes the world’s energy data using Internet-scale, secure cloud computing to process the petabytes of information produced in an increasingly networked and automated grid. AutoGrid employs big data analytics to generate real-time predictions and implement programs for electricity generators, providers, grid operators, and their customers to optimize the use of assets across the grid and manage costs through a comprehensive Energy Data Platform (EDP)™

Apps built upon EDP™ are powered by forecasting and optimization engines, managing functions such as:

  • End-to-end Demand Response with our Demand Response Optimization & Management System (DROMS)
  • Home Energy Management through our customer portal, which Schneider is white-labeling as their Wiser product
  • Peak Charge Management for facilities with Energy Cost Optimizer (ECO), an app co-developed with NTT DATA

Who can use AutoGrid’s platform and how?

Anyone along the electricity value chain can use AutoGrid’s platform and apps, including utility companies, power retailers, ESCOs, facilities, and customers. Apps on the Electricity Data Platform (EDP) are Web-based. Users can subscribe via a Software as a Service (SaaS) model. Additionally, resellers can license the technology. Silver Spring Networks is reselling our DROMS app as their own product, as “Demand Optimizer” within their Utility IQ suite.

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Isabel Alexandre

Meet CODE_n finalist Avansera Oy

“Can you see the future? It is in your hands.” That is how Avansera Oy presents itself. The Finnish startup, that combines historic behavioral data with calculated future intent, can predict what consumers will buy.

Cormac Walsh, CEO and Founder of Avansera Oy, talks in today’s interview about how Big Data can benefit the Fast-Moving Consumer Goods companies and retailers. As one of the Top 50 finalists, he also tells us his experience at CODE_n’s hall during the CeBIT.

Cormac Walsh

Cormac Walsh is the CEO of Avansera Oy

Why create a startup like Avansera Oy?

There is a strong need from the Fast-Moving Consumer Goods (FMCG) industry to see what shoppers are doing in the physical world; this is the core of the need for our customers. To provide the necessary context, let us look at the current market analysis business. Consumer behavioral data is collected through online activity related to online activity, or through questionnaires and focus groups. These approaches are limited in terms of reach and accuracy. Online data collection related to online behavior misses the behavior in the physical world, whereas traditional questionnaires and focus grouping have low accuracy and are very expensive (non-scalable).

In Avansera Oy, we deal with both of these issues. By providing accurate and scalable consumer digital services specifically relevant to the physical world, we can offer a high-value service at a lower price point than the traditional competition.

In an average week in the EU, there are over 600,000,000 grocery trips, not much of this physical data is currently being collected. At Avansera Oy, we want to collect as much of it as we can, and use it to benefit industry and society.

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Janina Benz

CODE_n at CeBIT 2014 – a review

Weisshaar and Kram designed the artistic concept with 12 meter-high terapixel displays everywhere

Weisshaar and Kram designed the artistic concept with 12 meter-high terapixel displays everywhere

The time we spend each year at CeBIT is always a professional and personal highlight. As the CODE_n team descends on Hall 16, our thoughts are occupied by the artistic design, the people behind the startups, and the upcoming award show. We will never forget the moment when we walked into the hall for the first time – wow! 12 meter-high terapixel displays everywhere. At this point congratulations have to go to Weisshaar and Kram for their outstanding artistic concept. There could never have been a more appropriate concept to showcase the 50 most innovative startups from all over the world and their big data solutions.

We’re proud to say that 17,000 people visited the CODE_n hall this year. This excitement was also reflected by the press, venture capitalists, bloggers, and visitors in general. In total, there were 50 startups from 17 countries, creating a palpably entrepreneurial spirit. Everyone was just thrilled by the atmosphere. More…

Isabel Alexandre

Meet CODE_n finalist Intelie

Intelie uses advanced trend analysis and information correlation technologies to help businesses achieve their strategic goals by avoiding possible mistakes. The Brazilian startup created Intelie Live, a platform that can process large amounts of data in real time and correlate them to create business scenarios.

Ricardo Clemente is the founder of Intelie

Ricardo Clemente is the founder of Intelie

In today’s interview Ricardo Clemente, founder of Intelie, talks about their big data solutions, the startup landscape in Brazil and, of course, their impressions about participating at CODE_n and CeBIT this year!

What differentiates Intelie from its competitors?

We have two main differentiators. The first one is related to the technology perspective. Our platform is able to analyze huge amounts of data in real time with low consumption of memory and infrastructure. Therefore, the company is able to perform correlated analysis and get information in real time by using our distributed correlation engine (PIPES). The second differentiator is on the business side. We have developed several segmented solutions per target industry. Thus, we build indicators, alerts, and visualizations for a certain industry, such as e-commerce, retail, oil and gas, insurance, telcos, finance companies, etc.

How can big data change the way companies work today?

Our solution improves the way that people work. The current data analysis culture is based on historical data only, using BI and Analytics tools. We would like to speed up this way of thinking. With our solution, managers make the most of their huge amounts of data and become proactive. They can immediately identify failures or business opportunities and act on them. Managers cannot rely only on daily or even weekly reports. For example, if I am working in e-commerce, I should be immediately informed if my conversion rate is too low or if many payments were blocked during fraud analysis. These blocks may be incorrect and I might be losing money. We have examples for all industries I just mentioned. Our job is to educate the market and show the importance of faster thinking and operational intelligence.

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Isabel Alexandre

Meet CODE_n finalist Science Rockstars

For the Dutch startup Science Rockstars, good science is the key to great business. That’s why they created PersuasionAPI, an SaaS-based API for e-commerce marketing teams. The software acts on powerful insights into the actual behavior of individuals, helping companies increase customer loyalty and conversion.

Maurits Kaptein

Maurits Kaptein is Chief Science Officer of Science Rockstars

The startup is a pioneer in persuasion profiling. And what is this? According to an article about the technique and its creators in Wired magazine, persuasion profiling doesn’t just find content your customers might enjoy, it figures out how they think. The chief science officer at Science Rockstars, Maurits Kaptein, was one of the doctoral students in communications who conducted the research about persuasion profiling at Stanford University. In today’s interview he talks about these studies, the foundation of the startup and their first product, the PersuasionAPI.

Could you briefly explain what persuasion profiling is and the main conclusions of your research on the technique?

A persuasion profile is a collection of estimates on the effect of persuasive strategies and the associated uncertainty. At least, that’s the scientific definition. Basically a persuasion profile captures the sales arguments that a customer is susceptible to. The profile is updated continuously as the customer interacts with a website. By using persuasion profiling you can make sure you select the right sales pitch for the right customer.

What led to the setting up of Science Rockstars?

Science Rockstars initially grew out of my PhD work (at Eindhoven University and Stanford University). We were gradually shifting towards a first viable product in 2012, only in our spare time, and we launched the company in August 2012 when we went live with our first Beta customer Booking.com. We started pulling together to form this great team to grow beyond research into an actual product. And finally, it’s ready!

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Isabel Alexandre

Meet CODE_n finalist SOMA Analytics

Stress is a global health issue and SOMA Analytics aims to use big data to tackle it. A German startup based in London’s TechCity, SOMA Analytics builds evidence-based mobile health programs to increase the emotional resilience of employees, thus reducing the risk of stress, anxiety, and depression.

The startup is part of Healthbox, an accelerator program that’s supported by leading universities, researchers and clinicians in the fields of sleep medicine and occupational psychology. In today’s interview with Johann Huber, CEO and co-founder of SOMA Analytics, we talk about the way forward for the company and the amazing benefits big data can bring to the health sector.

Johann Huber

Johann Huber, CEO and co-founder of SOMA Analytics

SOMA Analytics used to be a smartphone app to help people measure stress and depression. Now the startup changed its business model to target the B2B market. Why did you make this move?

Through several tests with consumers and companies we learned that we can provide much more value for the individual if we offer our solution in a B2B context. From research we also know that in most cases work is the main cause of stress. Our solution now helps employees and employers.

Could you briefly explain how the SOMA Analytics 21-day program works?

You install our app on your phone and it starts by itself – no other devices such as wristbands or endless questionnaires are required. The app measures parameters such as sleep quality and emotions experienced during phone calls with scientifically validated algorithms. We combine these measurements with further parameters, and, based on these readings, each individual receives personalized tips and feedback on how to reduce the impact of stress. For example, by the end of the program the customer knows exactly how long he should sleep to be optimally refreshed, or if he should go to bed early or late. In addition, he also sees which of the contacts he calls is likely to put him in a relaxed or stressed mood. The user can then apply the feedback he gets and immediately sees the impact on his measurements.

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Isabel Alexandre

Meet CODE_n finalist Kreditech

Sebastian Diemer is the CEO of Kreditech

Sebastian Diemer is the CEO of Kreditech

Kreditech uses Big Data and complex machine-learning algorithms to enable faster and better credit decisions. The technology developed by the German startup identifies and scores individuals online and decides over instantly paid out loans. All based on the processing of 10,000 data points in real-time.

In today’s interview, we talk to Sebastian Diemer, founder and CEO of Kreditech. He tells us how the startup uses technology to provide banking products to customers in emerging markets, allowing unbanked people with no credit bureau history to get credit. He also tells us how they are getting prepared to present their Big Data solutions at CODE_n and CeBIT.

Could you briefly explain what Big Data scoring technology is?

Our technology takes into consideration every piece of information that can be obtained about a person. We then analyze the results with statistical methodologies collected from our self-learning technology. Several thousand individual data points are merged into one big mosaic picture within seconds. It is not about single stones being red or green but the shape of red or green areas, illustrating the importance of coherence among several different data pieces.

What sets Kreditech apart from its competitors?

In comparison to other financial service providers and established credit bureaus, Kreditech only does live scoring. That means that we rate a customer’s creditworthiness by only looking at his or her current financial status instead of historical data. We gather information at the moment the application is submitted. Unlike FICO or Schufa, we neither retain the data afterwards, nor do we sell it. Our unique sophisticated credit scoring process uses the powers of machine learning algorithms and Big Data infrastructure to allow us to analyze more than 10,000 data points in less than one minute. That is what is unique about Kreditech.

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