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Growing up on an organic farm in the mountains made me realize early on that taking care of animals, the forest, and the environment has a direct effect on their well-being. It is extremely gratifying to see life flourish through your personal effort. Every action has a reaction; therefore, it is our responsibility to treat animals fairly, take care of the land, and always put the environment first.

When running a business, the results of our personal or business actions might not always be plainly visible. However, they are there and affect the world around us positively or negatively. Many people, including myself, nowadays strive to work for a company that is aiming to create a positive impact in the world, whether through its products or by taking on social or environmental responsibility. In fact, the majority of people (62%) actually want to work for a company that has a positive impact in the world, and 50% would even work harder if their work benefits others. I can certainly relate to this as I find it very motivating to work for a company that cares about the people and the community.

I joined MOSTLY AI because I believe in its mission of protecting people's privacy and promoting a positive change throughout the industry. Startups have always fascinated me as they can disrupt an entire system and become a major force when promoting change or, as in this case, creating sustainability. According to George Serafeim in a Harvard Business Review article, there is significant evidence that sustainable companies are the future. They not only deliver innovative approaches to products and business models, but they can also change the way things work, including how we combat climate change. They attract better talent and outperform companies with low sustainability levels in terms of performance and financial returns on investment. Therefore, so-called environmental, social, and governance (ESG) investing as a means to sustainable value creation is on an upward trend. Creating a sustainable business can increase your business value significantly.

MOSTLY AI recognizes the importance of taking on responsibility not only for our people but also for the environment. As it is impossible to have zero emissions, we aim to be at least carbon neutral. When the environmental initiative became a topic, I was eager to join the efforts of making MOSTLY AI carbon neutral and shortly afterward became our Climate Officer. In this role, I became directly responsible for measuring our climate impact and initiating measures to decrease our carbon footprint.

We have already taken very important and efficient steps towards sustainability and continue to work on making MOSTLY AI the greenest possible version of itself. Here are the steps we have taken so far, and we hope that our efforts will motivate others to follow in our footsteps.

Be part of a community that helps and supports you on your mission.

Working in a startup means that there is a high workload and a lot of things to keep track of on a constant basis. Joining a community that supports you during this mission can make progress way easier and keep you on track with your environmental objectives.

MOSTLY AI joined Leaders for Climate Action (LCFA), an entrepreneurial community that drives efforts to combat climate change. LFCA has created a network of leaders throughout the industry to make the fight against climate change their common goal. So far, over 900 companies have joined, and they have reduced over 360,000 tons of CO2. It goes without saying that these numbers are huge, and it proves that one company alone cannot achieve much, but bringing all of us together can make a real difference.

By joining LFCA, we were able to focus on the initiatives that really matter, have experts in the field support us in our mission, and be a part of a like-minded community of entrepreneurs. If you are reading this article, I assume that you are already passionate about the environment, and I encourage you to put joining this initiative as an action item on the agenda of your next team or management meeting.

You can't manage what you can't measure.

The first step towards becoming carbon neutral is knowing the actual emissions your company produces every year. There are many calculators out there that can help you assess your personal and company-wide carbon footprint, such as the WWF or the Federal Environment Agency calculators. This process is a bit tiresome, but there are a lot of insights you will gain from it. Not only will you consciously evaluate all the past years' bills regarding your environmental impact, but you will also experience eye-opening moments when discovering the largest drivers of emissions. Just to mention one example: an economy flight from Vienna to New York causes emissions of about 4 tons of CO2. To put this in perspective, it is more than double what a family car emits in a year. It is critical to evaluate the factors driving your company's emissions before taking decisive action to reduce them.

Reduce travel whenever possible.

As mentioned above, travel is one of the biggest factors when it comes to CO2 emissions. During the COVID-19 pandemic, travel has pretty much decreased automatically. There are lessons to be learned and questions to be asked when life returns to "normal." One of them is: "Do I have to go to this meeting in person, or can I make a video call instead?" Switching to video conferencing whenever possible is a simple but effective step towards reducing unnecessary emissions.

At MOSTLY AI, our employees are flexible in how and where they work. This means that Zoom and Hangouts are our most important means of communication, particularly during the pandemic. Our workforce is encouraged to use environmentally friendly means of transportation. This includes our 'trains over planes rule,' which means that public transportation is always the preferable choice—unless, of course, you can walk or bike to your meeting.

Traveling by public transport or train whenever possible has a significant impact on our carbon footprint. The same is true for commuting to work. At MOSTLY AI, everyone can work remotely, thus preventing emissions caused by commuting. Nevertheless, if people prefer to work from our centrally located office in Vienna, they usually commute by means of public transport; a yearly ticket is provided by the company.

Change starts within your team.

Your team is the driving force in this process. Ask them to actively participate in making your company greener or, in other words, more environmentally friendly. This can involve transport to the office but also being privately active in reducing their carbon footprints.

With the support of our team, we've made a few changes within our office. One of them was to go completely paperless by introducing electronic signatures. If it's necessary to print, we use 100% recycled paper. Recycled paper is comprised of 100% waste paper and therefore saves both water and resources. Producing it takes two to three times less energy. Moreover, we've introduced a proper waste separation system and ask our employees to minimize waste in the first place. Since half of all plastic products are designed to be used only once, stressing the importance of minimizing plastic waste can lead to a significant drop in the use of plastic (bottles, food delivery packaging). This movement has been extremely smooth and successful. Everybody recognized its importance and was eager to participate.

Take a close look at your current vendors.

As an artificial intelligence and machine-learning tech startup, one must not dismiss the emissions associated with using electricity to train the underlying models. Training neural networks requires high computing power because multiple calculations have to be simultaneously carried out. Therefore, cloud computing and the associated data centers are major environmental concerns. In fact, a single data center can take more power than a medium-size town. Measuring the direct impact of emissions caused by cloud computing is impossible at this point. There is a great lack of data from the respective cloud providers and a huge need for more regulation and environmental controls. Despite this lack of transparency, the big cloud providers are starting to become more environmentally friendly. AWS aims to achieve 100% renewable energy by 2025 and Google Cloud Platform (GCP) is already 100% green. It is up to all of us as startups and big companies to demand green energy and more transparency from service providers.

A first step to achieving this requires looking at your own current service providers. MOSTLY AI switched to a green energy provider that obtains 100% CO2-free green electricity from renewable energy sources. Switching to renewable energy sources can have a significant effect on reducing the CO2 footprint and saving natural resources such as fossil fuels.

Moreover, don't forget to encourage your employees to be energy conscious at work. Remind them to switch off lights, computers, AC, heating, etc. when not in use, and to be active in looking for ways to reduce their personal carbon emissions. If you take things one step further, you can install motion detection lighting systems in office hallways and rooms that are less frequented. Moreover, turning off your camera in video calls could cut energy consumption by 96%.

Offset it with certified partners ONLY.

Climate neutrality is an environmental policy goal that aims to reduce emissions caused by companies through production and consumption so that they don't have any influence on the climate. This is based on the assumption that the climate system can buffer a certain amount of greenhouse gas emissions without having any significant impact. Products, services, or companies can be climate-neutral if, after determining CO2 balance, the emissions are offset.

For the climate, it is not important where greenhouse gases are emitted or avoided as they are distributed evenly in the atmosphere. For this reason, emissions that were caused at one place can be offset by saving at another. Developing countries are often the most affected regions when it comes to CO2 emissions. (Kyoto Protocol) Therefore, carbon offset projects aim to promote sustainable development in the most affected areas in the world. Through forest protection, reforestation, and renewable energy, these projects (among others) significantly reduce carbon emissions and counteract global warming.

Such projects must meet internationally recognized standards such as the Gold Standard or the Verified Carbon Standard (VCS). The Gold Standard is among the leading standards to define the quality of a carbon offset project. If you are looking into offsetting projects, always require one of the above standards to make the most out of your initiative.

To achieve a basic carbon-neutrality, we have addressed our direct carbon emissions with an organization called natureOffice Gmbh. They help reduce carbon emissions via forest ecology projects in Africa and South America in combination with regional forest ecology projects in Austria, Germany, and the Netherlands. While the actual offset of our emissions takes place in Brazil, our local environment is supported through the important work of the mountain forest project in the Montafon. It can be tracked here.

Change starts today.

Having an environmentally responsible business in 2021 leads to healthy, productive, and forward-thinking employees without jeopardizing growth and profitability. Companies like ours are the future, and we believe that by implementing environmentally conscious efforts early on, we can create long-term sustainability.

At MOSTLY AI, we believe in creating a positive impact on the world around us through our products and the people working with and for us. We strongly believe that it is our responsibility to act and promote a sustainable working culture. We believe that it is everyone's responsibility to act consciously and to do the right thing for ourselves, the people around us, and for our planet. Change starts today but doesn't stop there. In the future, we plan to reduce our carbon footprint further by optimizing our business processes to further reduce emissions. Change starts now!

Eager to find out more about MOSTLY AI's carbon reduction measures? Then take action now!

Every team needs a captain, and we just got a pretty cool one. Besides being a seasoned engineer, Kerem is an experienced sailor and captain, bringing unique insights from the sea.

So, what did you learn from sailing?

First and foremost, you need to respect mother nature. You need to know your own and your boat’s limits so that you do not cross the line of bravery into misery. And if you respect nature and know yourself, there is no limit to the joy you can take from the sea.

You need to know the environment you are in (learn the weather forecast, check charts for debris, read the wind, wave, and clouds), make sure that your boat is in the best condition, be always on the watch and take your decisions accordingly.

The sea does not allow you to relax. You have to be alert even on anchor. You need to check if the changing wind will make you lean towards the rocks.

You have to think ahead, be prepared: make sure you have spares for critical equipment, have your Plan B ready, and run it in your head before starting every action. Be innovative enough to create a Plan C on the fly if both Plan A and B fail (and they will).

The boat can only travel fast and safe if the whole crew is in synchronicity. Since the captain is the one accountable for the safety and the course, his job is to make this synchronicity in the crew happen and, at difficult times, takes the difficult decisions.

You can apply each of these rules of the sea in the business world. A good captain has all the traits of a good business leader.

What are you most proud of in your career?

The most obvious answer and the most relevant in our start-up context is the company we founded in 2001 in Turkey. It was a software start-up specializing in CRM and Business Process Management Software. We became the market leader in our domain,  outperforming the “usual suspects.” In the year 2009, we sold the company to the telecom giant Ericsson, and it opened up new frontiers both for me and for everyone in the company.

But if you want to know the real answer, I was the proudest when young colleagues we hired fresh from university grew within our company. When they bought their first car, their first house, when they had their first child.

Why did you decide to join a synthetic data start-up?

I think that you need to experience both start-ups and corporations in your career. I have to say that I learned unbelievably lot during my time in the corporate world. I have experienced three-digit million Euro contracts, projects with hundreds of people, took executive leadership trainings in renowned universities, and most importantly, learned to work in a multicultural environment.

In the midst of these experiences, I always thought, “If I had all this know-how before, in our start-up, we could have done much better!”. These moments made me realize that my passion lies in start-ups. Furthermore, AI was an area I had a personal interest in, and here I am!

What do you wish for in 2021?

My wish for 2021 is to help more and more customers in their data privacy journey, creating the market of our niche with them. This is the prerequisite and enabler for our engineering team to innovate and create.

If you ask me, what my “selfish” wish for 2021 is, I would say that I wish for the pandemic to be over, so we can all meet in our office, work face to face, chat over coffee, and enjoy our perfect location in the heart of Vienna.

UPDATE: MOSTLY AI SaaS has been discontinued

Instead, we made the world's best synthetic data platform free forever for generating up to 100K rows per day.

Today I am thrilled and proud to announce the launch of MOSTLY AI SaaS. This milestone speaks of our growth as a company, which we wouldn’t have reached without our devoted team of world-class experts and our dedicated customer base.

We achieved yet another first in the industry. It’s 2.5 years ago that we launched the first commercially available AI-powered synthetic data solution for the enterprise. Shortly after, we pioneered a synthetic data solution for behavioral data assets, something that is still unmatched in the industry.

Imagine being able to derive insights from your customers’ bank transactions or their online shopping behavior and create products that genuinely address their needs. With MOSTLY AI's synthetic data platform, it is possible to create synthetic data copies of these behavioral datasets that retain the structure, correlations, and time dependencies of the original data while safeguarding the privacy of your customers.

Bringing AI-powered Synthetic Data to the masses

With our SaaS release, we make these state-of-the-art capabilities available to companies of all sizes and budgets. We significantly evolved our business practices to reach the maturity required to make this leap.

Firstly, we have taken great care to ensure that we are fully GDPR compliant and that your data is safe with us. These measures include the usage of industry best practices, professional frameworks, and security policies. You can find more detailed information here

Secondly, your synthetically generated data comes with an automatically created Quality Assurance report. It’s generated by algorithms that test for privacy is the resulting data dissimilar enough that original subjects cannot be re-identified?, and accuracy does the structure, correlations, and time dependencies of the original dataset still hold up? 

You don’t need to take our word for it. We open-sourced these privacy and accuracy metric definitions so we can offer the transparency and security that you demand from us. You can find them in this GitHub repository.

Try what it can do for you - securely and free of charge

I invite you to try the free version to experience the power of our synthetic data platform. There's no credit card needed to benefit from the full functionality of MOSTLY AI SaaS. And while you do so, we would love to hear your thoughts and feedback. Please do not hesitate to reach out to us as we are always eager to listen to and learn from our users.

Lastly, I wanted to say a big thank you to everyone on the team who has been working on this release! This is yet another milestone for MOSTLY AI, and I look forward to building out our capacities in the cloud. Expect to hear more from us later this year!

Tobi

Contact us to discover your synthetic data use cases!

I met Michael, Klaudius, and Roland in 2018 and as the conversations got deeper, my desire to become a part of MOSTLY AI grew steadily. In May 2019 I started working for MOSTLY AI, first as an external consultant and soon thereafter as the company’s Chief Operating Officer. The last year has really flown by and it’s impossible to adequately recap the many highlights and accomplishments we have had at MOSTLY AI without going beyond the scope of this post. Let me just share that on a personal level it has been deeply satisfying and impactful. In my career of almost 15 years, I’ve held many different positions and worked for a variety of fantastic organizations. I don’t need to think for a second to say that the year at MOSTLY AI has been the most thrilling and fulfilling professional year for me so far.

My previous roles were always centered around starting new or building and growing businesses. I’ve either done this as a consultant, intrapreneur, or with my own start-ups. It’s great to see how all these experiences have now put me in a sweet spot to help take MOSTLY AI to the next level. We have a multitude of things we are working on including feature upgrades to our core product MOSTLY AI's synthetic data platform and the launch of our SaaS offering which I’m particularly excited about. We can’t wait to share all of this with the world in the months and years ahead.

I look very much forward to working for many more years with the outstanding and growing team at MOSTLY AI, our clients, partners, and investors on shaping the synthetic data revolution together. While times right now are challenging for everyone, it’s amazing to see how well we cope with the situation as a team and company.

Let’s do this together! #gosynthetic

Tobi

PS: I also look forward to writing on this blog more frequently. Watch out for posts about the business side of synthetic data, our company, and all things scaling a deep-tech start-up.

Fig. 1: From left to right: Tobias Hann with Roland Boubela, Michael Platzer and Klaudius Kalcher – the three Co-Founders of MOSTLY AI

And is it really possible to securely anonymize the location data that is currently being shared to combat the spread of COVID-19?

To answer these and more questions, SOSA’s Global Cyber Center (GGC) invited our CEO Michael Platzer to join them on their Cyber Insights podcast for an interview. For those of you, who don’t know SOSA: it’s a leading global innovation platform that helps corporates and governments alike to build and scale their open innovation efforts. What follows is a transcript of the podcast episode.

William: Wonderful, now Micheal, when you think about the broad array of cybersecurity trends that are unfolding today – ranging from new threats to new regulations – what is really top of mind for you in 2020?‍
 

Michael: Thanks for having me! We are MOSTLY AI and we are a deep-tech startup founded here in Europe while preparing for GDPR. Very early on, we had this realization that synthetic data will offer a fundamentally new approach to data anonymization. The idea is quite simple. Rather than aggregating, masking or obfuscating existing data, you would allow the machine to generate new data or fake data. But we rather prefer to say “AI-generated synthetic data”. And the benefit is, that you can retain all the statistical information of the original data, but you break the 1:1 relationship to the original individuals. So you cannot re-identify anymore – and thus it’s not personal data anymore, it’s not subject to privacy regulations anymore. So you are really free to innovate and to collaborate on this data – but without putting your customers’ privacy at risk. It’s really a fundamental game-changer that requires quite a heavy lifting on the AI-engineering side. But we are proud to have an excellent team here and to really see that the need for our product is growing fast.

William: Very interesting! Now, we know that location data is among our most accessible PII – we kind of give it out all the time via our mobile device. In the wake of the coronavirus, we are seeing calls to use our location data to track the spread of this pandemic. Is it possible to really effectively anonymize and secure our location data? Or can this data just be reverse engineered? Could using synthetic data help?

Michael: Yes definitely, and we are also engaging with decision-makers at this moment in this crisis. Location data is incredibly difficult to anonymize. There have been enough studies that show how easy it is to re-identify location traces. So what organizations end up with is only sharing highly aggregated count statistics. For example, how many people are at which time at which location. But you lose the dimension at the individual level. And this is so important if you want to figure out what type of socio-demographic segments are adapting to these new social distancing measures, and for how long they do that. And is it 100% of the population that’s adapting, are social contacts reducing by 60% or is it maybe a tiny fragment of segments that is still spreading the virus? To get to this kind of level to intelligence you need to work at a granular level. So not on an aggregated level, but on a granular level. Synthetic data allows you to retain the information on a granular level but break the tie to us individually. We just, coincidentally, in February wrote a blogpost on synthetic location traces – so before the corona crisis started – because we were researching this for the last year. It’s on our company blog and I can only invite people to read it. Super exciting new opportunities now to anonymize location traces!

William: That is exciting – and it sounds as if it could be very helpful, especially given what we are all going through! Now, Micheal, there is an expanding list of techniques to protect data today; from encryption schemes, tokenization, anonymization, etc. Should CISOs look at the landscape as a “grocery shelf” with ingredients to be selected and combined or should they search for one technique to rule them all?

Michael: Well, I don’t believe that there is a one-size-fits-all solution out there. And those different solutions really serve different purposes. It’s important to understand that encryption allows you to safely share data with people that you trust – or you think that you trust. Whether that’s people or machines, at the end, there is someone sitting who is decrypting the data and then has access to the full data. And you hope that you can trust the person. Now, synthetic data allows you to share data with people where you don’t necessarily need to rely on trust, because you have controlled for the risk of a privacy leak. It’s still super valuable, highly relevant information. It contains your business secrets, it contains all the structure and correlations that are available to run your analytics, to train your machine learning algorithms. But you have zeroed out your privacy risk! In that sense, synthetic data and encryption serve two different purposes. So every CISO needs to see what their particular challenge and problem is that needs to be overcome.

William: Well Michael, we’re coming up on our time here. Are there any concluding remarks or anything you would like to add before we hang up?

Michael: Well, we just closed our financing round so we’re set for further growth both in Europe as well as the US. We’re excited about the growing demand for data anonymization solutions, also for our solution. Happy to collaborate with innovative companies, who take privacy seriously. And of course, I wish everyone best of health and that we get – also as a global community – just stronger out of the current crisis.

We proudly present the free version of MOSTLY AI's synthetic data platform and warmly welcome you to try it out.

What does MOSTLY AI's synthetic data platform do?

MOSTLY AI enables you to automatically transform your privacy-sensitive big data assets into highly realistic and accurate synthetic datasets. The benefit is, that synthetic data is fully anonymous and thus exempt from data protection regulations. This results in as-good-as-real data, that is free to use, share or monetize. So with MOSTLY AI's synthetic data platform, you are finally able to freely innovate with one of your most valuable resources – all while avoiding the financial, regulatory or reputational risks of a privacy violation!

How does our synthetic data platform work?

MOSTLY AI's synthetic data platform leverages state-of-the-art generative deep neural networks with in-built privacy mechanisms to automatically learn the patterns, structure and variation from an existing dataset. Once the training is completed, it allows you to simulate an unlimited number of highly realistic and representative – but completely anonymous – synthetic customers. Thereby, you are able to retain all the valuable information in your data assets, while at the same time rendering the re-identification of any individual impossible.

How does the free version compare?

The free version of MOSTLY AI's synthetic data platform comes with the same powerful core technology as the enterprise version: our fully automated Synthetic Data Engine. This will enable you to generate synthetic data based on a provided actual dataset and to experience the magic of generative AI in action. Try it out today and persuade yourself of its quality, its flexibility and its ease-of-use.

Automatically generated quality assurance reports allow you to easily compare
the quality of your synthetic data (blue) with the original (grey).

But keep in mind, that it is a free version and that some usage restrictions apply. While the enterprise version of MOSTLY AI's synthetic data platform supports multiple tables and extremely large datasets with millions of rows and hundreds of columns, we limit the input for the free version to a single table with 50.000 rows and 50 columns. Furthermore, you won’t have the same flexibility as with our enterprise version to configure the training or the generation process. And as we operate this demo on a low-cost cloud infrastructure, the compute time will be significantly longer than for production setups.

Lastly, since it is a demo version, you must not use it to upload any personal or sensitive data. But no worries – if you don’t have a suitable dataset at hand, just go to Kaggle and choose a publicly available dataset you like. Or, if you are looking for even more convenience, simply select one of the datasets already provided on the demo site to start your first synthesis run in a matter of seconds!

With that being said, we warmly welcome you to generate synthetic data and to start your own personal journey with this groundbreaking technology. We are very much looking forward to your valued feedback and are here to answer your questions, should any arise.

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