Yandex Blog

Yandex Data Factory and the Next Industrial Revolution: Steel, Oil, & AI

Jane Zavalishina is the CEO of Yandex Data Factory, a spin-off of Yandex founded in 2014 to provide machine learning solutions to enterprises. In this post, Jane explains how YDF’s business has evolved since its launch, and why industrial AI is now in focus of its strategy.

Since its inception, Yandex Data Factory (YDF) has pioneered an innovative way to create value for companies by applying our expertise in machine learning and artificial intelligence (AI) to help solve their business needs. YDF arose as a solution to the problem many businesses faced at the peak of the big data craze. Essentially, businesses had begun amassing huge amounts of information, but were struggling to extract tangible value from this data.

The solution, of course, is in machine learning. Our parent company, Yandex, was an early leader in machine learning technology and today, machine learning powers 70 percent of Yandex’s products and services. We realised that wherever large stores of data exist, so does the opportunity to use that data to reach measurable business improvements. The same algorithms that power Yandex’s services, can be used to help other businesses improve their operations, revenues and profitability.

Over the past two years, we have worked with a number of companies across multiple industries on various successful projects. Together with our clients, we discovered the best use cases where machine learning can be applied to increase the efficiency of existing processes in a measurable way – be it predicting demand for a retail chain, or using computer vision to cut moderation costs for online service. Along the way, we accumulated a huge amount of expertise on merging data science with business.

One such case included our work with Magnitogorsk Iron & Steel Works (MMK), that marked one of the first ever collaborations of its kind between a technology company and steel company. MMK, one of the world’s largest steel producers, wanted to reduce its production costs while maintaining the same high-quality product. YDF developed a machine learning-based service that recommends the optimal amount of ferroalloys—the ingredients needed to produce specific steel grades. Our predictive system demonstrated the reduction of ferroalloy use by an average of five percent, equating to annual savings of more than $4 million in production costs, while consistently maintaining the same high quality of steel.

Similarly, we are now optimising the operations of a gas fractionation unit for a petrochemical company. Our solution recommends the fractionation unit parameters for maintaining the best performance and energy savings, decreasing costs in the process. Last week, we also signed a collaboration agreement with Gazprom Neft, an integrated oil company. We plan to apply our technologies to well drilling and completion, and other production processes. These successful efforts demonstrate the high potential for collaboration between artificial intelligence and industrial manufacturing.

The industrial sector – responsible for one-third of global GDP – has proven to be the ideal vertical, perfectly positioned for the effective application of our technologies. The industrial sector has become YDF’s focal point through the combination of our own successful application of predictive analytics with industrial data and the fit of the industry. Put simply, manufacturers know the value of optimisation at their hearts. Industrial manufacturing is also a unique cultural fit. They value measurements above opinions, they have perfected integrating new technologies in the existing processes, and they know how to estimate their effect through properly designed experiments.

For decades, the cornerstone of competitiveness in manufacturing has been centered on the optimization of existing processes, reaching for each tenth of a percent of efficiency in each step. And when all traditional optimisation means have been applied, the next efficiency leap of five to ten percent is often prohibitively expensive and equally time-consuming. These improvements typically consist of equipment upgrades with multi-million dollar investments, years spent on construction, rigorous training and implementation, and a lengthy delay before seeing any tangible financial return. Compared to this, receiving the same level of optimization via machine learning in a matter of months with minimal upfront investment is nothing short of revolutionary.

These long-term benefits extend far beyond a simple profit and loss sheet, and can help conserve both human capital and natural resources. By training machines to focus on the mundane, routine decisions that keep a factory running, artificial intelligence and machine learning allow human employees time to tackle more important tasks. By applying these technologies to oil and gas, companies not only achieve time and material savings, they can also reduce their energy consumption by up to 25 percent.

Our AI-enhanced models create endless opportunities to add value to the manufacturing industry. These benefits are especially noticeable in process manufacturing, where materials and mixtures – metals, chemicals, etc. – are produced. Essentially, these are also the industries responsible for the highest resource consumption.

The AI revolution in manufacturing is happening right now, and we are thrilled to be leading the charge. As this future becomes a reality, we’ll be there – at the forefront – blazing new trails in the industrial sector and delivering far-reaching effects for both the companies we work with and the larger communities they serve.

Yandex.Taxi Unveils Self-Driving Car Project

Yandex’s on-demand transportation service Yandex.Taxi unveils its autonomous car project. The prototype of a self-driving car the company has developed is a step towards a comprehensive set of driverless technologies for application across a wide range of industries.

The driverless car incorporates Yandex’s own technologies some of which, such as mapping, real-time navigation, computer vision and object recognition, have been functioning in a range of the company’s services for years. The self-driving vehicle’s ability to ‘make decisions’ in complex environments, such as busy city traffic, is ensured by Yandex’s proprietary computing algorithms, artificial intelligence and machine learning.

“Self-driving cars are set to revolutionalise the way we commute within a matter of a decade,” says Dmitry Polishchuk, head of Yandex.Taxi Self-Driving Project. “At this point in time, there are dozens of companies around the world building their own driverless cars, but only a few of them have components crucial for turning this project into reality. These components include a stack of reliable technologies and algorithms, engineering expertise and resources, and access to the market for self-driving vehicles. Yandex.Taxi, with the backing of Yandex, is one of the few players who can boast of possessing all of the above.”

Yandex.Taxi’s effort in developing the self-driving car technology aims at creating a fully-fledged autopilot functionality, which is described as Level 5, according to the currently universally accepted classification system for automated vehicles. This system classes all self-driving cars into levels from 0 to 5, where Level 0 means a person has full control over the vehicle, and Level 5 involves no human intervention.

Yandex.Taxi will push on with experimenting and honing the self-driving technology, together with improving maps, navigation and route planning implemented in this project. Tests on public roads are expected to kick off next year.

With Yandex.Taxi test-driving the self-driving service, Yandex looks forward to partnering with car manufacturers and other companies interested in taking the autonomous car technology to the road.

Yandex Partners with Micromax, the 10th Largest Mobile Company, Heightens Device Differentiation with AI-Powered Yandex.Zen

Yandex.Zen, an AI-powered personally targeted content feed based on the interests of each individual end user, was built to help mobile users on the go and in the moment with contextually relevant information. Through partnerships with Yandex.Zen, smartphone manufacturers can provide this personalized experience for their users to set their devices apart.  Today we are glad to announce we are enhancing device differentiation for another global partner, Micromax Informatics, the world’s 10th largest mobile brand.

The AI and machine learning that powers Yandex.Zen provides smartphone users with suggested stories, articles and videos in their local language based on their personal tastes and choices through a user-friendly interface. The result is a superior end-user experience gained from a device that stands out from other Android devices.

Yandex.Zen will be incorporated into Micromax's AROUND experience, which integrates shopping, travel and food services in one window. Micromax, well-known as India’s largest mobile brand, helps users navigate a number of shopping and dining tasks on their devices. The Yandex.Zen integration brings an additional layer of personalization to the AROUND experience, delivering users contextually relevant information and entertainment content in Hindi, Telugu, Tamil, and English.

By complementing the AROUND experience with Yandex.Zen, Micromax offers users with a truly comprehensive and empowering mobile experience. Yandex.Zen’s feed will run as a news category alongside the leisure category (where users can order food and comparison shop), and the travel categories (used for hailing taxis, checking transportation schedule, or booking accommodations. 

Artem Fokin, Yandex VP for Business Development, says of the partnership: “We are proud to be working with Micromax to help enhance the user interface of its devices through AI, for improved user experience and ultimately to achieve device differentiation within a crowded marketplace. Yandex’s software allows cult brands in the market to truly understand and engage with their consumers as the digital landscape continues to evolve.”

Mr. Rahul Sharma, Co-founder, Micromax Informatics echoed Fokin’s comments: “At Micromax, our emphasis is to drive innovations through software and services that simplify the user experience and create much values for them. A large chunk of our efforts are now  concentrated on introducing products and services which act as solutions to the needs of our customers, empowering them with the latest technological innovations and eventually becoming an extension of their lifestyle.” He continued, “Given the fact that, personalisation, flexibility and simplicity are key for consumer engagement, the partnership with Yandex will help our users stay updated with news and articles as a personal news feed and have an enriched device experience.”

Yandex’s expertise in machine learning, neural networks and artificial intelligence are key components for Yandex.Zen’s simplified end user experience that help partners like Micromax achieve its goals for customers. Yandex.Zen supports multiple integration options as a part of Yandex Browser or Yandex Launcher and as a separate SDK for third party deployment.

At Yandex we believe in delivering compelling customer experiences directly to our users through our suite of intelligent products or services as well as to our partner’s customers via mobile applications such as Yandex.Zen. We are proud to say the daily Yandex.Zen usage currently stands at 20 minutes per day, on par with the average time users spend on social networks. Over the past year, Yandex has expanded our reach, keeping users informed and entertained with personalized content on their devices and delivering high-quality software for our partners. Micromax is among a respected group of smartphone manufacturers benefiting from our global partnership program, including Wileyfox, ZTE, Posh mobile and others. We look forward to the positive impact of Yandex.Zen on Micromax devices and welcome new opportunities with global partners.

To learn more about Yandex.Zen, visit

Celebration of Choice – A letter from Arkady Volozh, Yandex CEO

In this blog post, I would like to share my reflections on the landmark settlement between Google and the Russian Federal Antimonopoly Service (FAS) (you can read the FAS press release here).

Today is an important day for Russian consumers as Google has agreed to take significant steps that open up its Android platform in Russia.  Under the terms of the settlement, 55 million Russian Android users will be offered a choice of search engines on their mobile devices.  Smartphone manufacturers will also have more freedom to select the apps that they preinstall on devices.

Several years ago, it became clear that the closed nature of Google’s Android inhibited our ability to provide a search option for Russian users on the most popular mobile platform.  Google required Android smartphone manufacturers to ship devices with Google search as the default search engine and to place the Google search widget on the default home screen.  Google also limited the placement of competing applications on Android devices. These factors created limits for how smartphone manufacturers could access the essential Android App Store - Google Play. These requirements made it challenging for search providers and other competing applications providers to pre-install their services on Android phones. Android was limiting options for users, smartphone manufacturers, and competitors – and all together restricting innovation. Yandex requested that FAS initiate an investigation into Google’s business practices. In 2015, FAS found Google’s practices to be anti-competitive and in violation of Russian antitrust laws.

As one of the largest internet companies in Europe, and the leading search and mobile applications provider in Russia, access to platforms is critically important for Yandex. Technology platforms make it possible for us (as well as other companies) to continue a rapid pace of innovation. But this is only possible if those platforms are sufficiently open to foster competition by allowing access to third-party developers. We are excited to have reached a solution that restores these necessary elements to ensure a more dynamic and competitive ecosystem.

I am thankful to the Federal Antimonopoly Service for applying the law in a manner that effectively and efficiently restores competition to the market for the benefit of Russian users.

I also want to thank Google, not only for their cooperation, but also for recognizing the value of openness. We have always thought Google plays a constructive role in the Russian market.  Competition breeds innovation. It’s our desire to participate in a market where users can choose the best services available.

For the past 20 years, it has been our mission to help users better navigate the online and offline world.  When I founded Yandex in 1997 with Ilya Segalovich, Elena Kolmanovskaya, and others, we shared a vision for the way search technologies would help people find information on the Internet.  Over the years, our machine learning capabilities have grown, and with it our aspirations. Our mobile services, maps, eCommerce, classifieds, and on-demand transportation services have expanded our ability to help users on the go and in the moment with contextually relevant information.

I’m excited, together with the entire team at Yandex, to continue building products and services that deliver exceptional customer experiences. With open platforms, our future is bright. With choice, the possibilities are endless.


From Point A to B: Inside Yandex.Taxi's Booming Ride-Hailing Business

Our on-demand transportation service, Yandex.Taxi, is committed to providing high quality and convenient transportation options for its passengers. We have always believed in offering both passengers and drivers cost effective choices to meet their needs and recently built in even more options.  Yandex.Taxi rolled out a new feature with Yandex.Maps that shows passengers the best pick-up location to save travel time and reduce their fares. 

Yandex.Taxi shows users when its more convenient to change their pickup location so their taxi can reach them faster and continue on a more direct path to the passengers’ final destination.  For instance, by walking through an underpass and moving to the other side of the street in Moscow, a passenger can save five minutes on their trip time and close to a dollar on their fare.

In order to find the best options for passengers, Yandex.Taxi analyzes all possible routes to the selected destination, traffic, and the number and location of available taxis. If there is a better pickup point for the passenger, the app will show passengers how to get there and how much time it will save by walking to the pickup spot.  Yandex.Maps provides pedestrian routes, including sidewalks, underpasses, footbridges, and other pedestrian areas to show the user how to reach the pick up spot. 

Combined these technologies offer options that help both drivers and passengers reach their destinations more efficiently.  "At Yandex, our focus has always been offering the best possible options for our users. Through a unique blend of technologies from Yandex.Taxi and pedestrian routing from Yandex.Maps, we are glad to significantly reduce the time and cost of travel. We are glad to be the only company offering such options to the Russian market," — said CEO of Yandex.Taxi Tigran Khudaverdyan.

Yandex.Taxi’s commitment to high quality service and convenient options has led to significant growth over the last year.  Yandex.Taxi completed 16.2 million rides in December 2016 alone, growing at an annualized rate of 452% from December 2015 to 2016. Last year Yandex.Taxi also reached the significant milestone of 100 million total rides.

Tigran Khudaverdyan explains, “I’m incredibly proud of the growth Yandex.Taxi has seen in 2016, seeing revenues grow 135% YoY on an annual basis and the number of rides increase 5.5 times from 2.9 million in December 2015 to 16.2 million in December 2016.  This year we continued to focus on providing high quality and efficient service for passengers but also on entering new markets to help meet transportation needs.”

Yandex.Taxi was first established in 2011, and has since become the leading on-demand app in Russia and CIS states. Last year entered 36 new cities and 5 countries. Today, our service operates in 56 cities across Russia, Belarus, Armenia, Kazakhstan, Georgia, Ukraine. We have over 120,000 drivers and 1200 taxi services and dispatchers.

Yandex.Taxi is incredibly eager to see what the rest of 2017 has in store and we plan to continue expanding our reach and ensuring we’re offering the best possible service for our millions of customers.

Celebrating International Women’s Day

International Women’s Day is a global celebration dedicated to women’s achievements inside and outside of the workplace. With 17 offices across nine countries, we’re proud to recognize the Yandex women around the world helping us build the next generation of intelligent products and services powered by machine learning.

Gender diversity is a vital part of Yandex culture, starting with our educational programs that encourage young girls’ interest in math and technology. Yandex Director of Human Resources, Lena Bunina, elaborates: “We are delighted to see young women joining our educational and academic programs as we believe it is crucial to stimulate their interest in STEM. We want to encourage the young women to explore their career options in technology.”

The overall makeup of Yandex employees displays another area of our commitment to gender diversity.  More than one in three Yandex employees is female and 19% of all technology roles are filled by female employees. “We believe that diverse perspectives and backgrounds foster innovation, idea development, and ultimately, inventions of the best products. They also help us make better decisions as a company,” says Mikhail Parakhin, Chief Technology Officer. And while Yandex’s gender diversity figures are comparable with other global technology companies, Yandex continues to seek opportunities to close the gap between male and female employees. “We insist on equal opportunities for everyone, as it applies to hiring, promoting and rewarding employees,” Bunina says.

We spoke to a handful of female leaders at Yandex to celebrate this occasion and are excited to share excerpts of their insights.  Among a few thousand other female employees, these women have made serious strides not only for Yandex, but for women in tech who are charting new territories in the development of machine learning applications that deliver superior experiences for consumers across the globe.

What led to your interest in working in technology? Can you think of a specific moment that made you realize you wanted to pursue a career in technology?

Milena Djuricic, Vice President Business Development

My career in technology came about organically as technology has always been an important part of my life. As a primary student in Yugoslavia, I participated in a school-wide programming pilot, which served as an experiment to implement programming classes across our country. In the mid-80s, we were learning how to program in Basic using huge metal machines and black and white monitors. It was a time of very primitive personal computing when the Commodore 64 was the dream of every school kid. In the early 90s, I received my first email address through an account on European Academic and Research Network (EARN). I remember being so happy to be able to exchange messages with my high-school friends who left our war-torn country and were living all around the world.

Maria Orlova, Head of Geoinformational Products

In 1998, my dad bought us our first personal computer when I was 13-years-old. During the first month, I managed to break the computer twice and it wouldn’t even start.  My dad, a lover of scientific approaches, then got me an excellent book about Windows 98, to both fix our computer and learn the basics of computer science.  As I read it, the idea of the Internet was so exciting that I literally could not sleep. I remember establishing my first mailbox on Yandex at my first trip to the Internet cafe around that same time. I was only 14 then and I didn't know why Yandex would need me, but I was sure I needed to be part of Yandex. Now I’ve been working for Yandex for 9 years! 

Tell us about your role at Yandex. What drew you to this role?

Jane Zavalishina, CEO Yandex Data Factory

I started working for Yandex in 2000. The most interesting thing for me over the past 17 years has been the opportunity to build something new, something nobody really knows how to build. There’s no recipe for success with some of these innovations and of course, the opportunities are so big. So today, as CEO of Yandex Data Factory, I have exactly that—we are working in a new and rapidly developing field of practical ML applications for traditional businesses. As we’re headed towards a fourth Industrial Revolution, AI is going to play a huge role in these changes.

Anna Veronika Dorogush, Head of MatrixNet

 I started at Yandex two years ago and am the head of the team developing algorithms and infrastructure for machine learning. Our team works on Matrixnet and other tools, which are widely used all over Yandex. I really love my role and I have a wonderful team! More than anything else, I enjoy my workdays that are spent working on code.  With my professional growth, I have taken on other less technical responsibilities, and now spend more time attending meetings, conducting job interviews, creating plans and collaborating with other Yandex teams. Despite being the less technical aspects of my role, they are still interesting and important parts of my job.

What is your hope or vision for women in technology in the future?

Olga Erykalina, Head of International Search

“Throughout my 10 years of professional development in Internet media and technology companies (which included two maternity leaves), I have never experienced any limitations or drawbacks related to my gender. I hope everybody who’s starting a career now will be able to say the same in the years to come.”

Jane Zavalishina, CEO Yandex Data Factory

“New technologies create new opportunities. When something really new and promising appears, traditions, expectations or attitudes don’t yet exist. We are in an industry of constant innovation and experiments, which has created a professional space that welcomes diversity and unique contributions from everyone who can help move tech forward. For that reason, I feel this is an industry of equal opportunity and I strongly believe we will continue to see more women in tech in the near future.”

We thank our female employees for their contributions today and everyday! Their diverse perspectives help us build the best possible products for our users.  Milena Djuricic, Vice President Business Development explains, “At the end of the day, if you are making a product, you want it to be useful for everyone and used by all. Both male and female perspectives are important contributions. For that reason, diversity is crucial and companies that understand that are winning. As a woman in tech, it is easier for me to understand 50% of our users much better than my male colleagues. It’s easier for me to understand other women’s problems and needs and suggest solutions for their specific problem.”

Are you interested in contributing? We are always on the lookout for rising stars with diverse perspectives – check out our Jobs page for more.

Introducing Yandex’s Machine Intelligence and Research Division

Yandex proudly announces the creation of our new Machine Intelligence and Research (MIR) Division. The MIR division will function as a centralized, cross-functional unit to accelerate innovation and unify our core machine learning technologies. The MIR division will also transfer cutting-edge research from our various research teams into Yandex products and services. Yandex has tapped Misha Bilenko to head the new division, which brings together a mix of teams focusing on AI-centered technologies including:

  • MatrixNet and DaNet – Machine learning has always been at the core of Yandex consumer products and information services. In 2009, we launched MatrixNet, our proprietary machine learning platform. Today, MatrixNet is used in nearly every product and service Yandex offers. One important feature of MatrixNet is its resistance to overfitting, which takes into account a very large number of factors when ranking the relevancy of search results. DaNet is the deep neural network (DNN) framework developed at Yandex that provides state-of-the-art runtime performance for many tasks that rely on deep learning.
  • Computer Vision – People learn to recognize objects at a very young age. Machines, on the other hand, must be trained to recognize objects using vast amounts of labeled and unlabeled data. Yandex’s market-leading image recognition technology uses machine learning to detect similar images in visual search results as well as perform a number of high-end vision tasks, from automotive photo analysis for, to predicting weather patterns using satellite imagery.
  • Speech – Yandex’s SpeechKit voice recognition technology uses machine learning to help people better communicate with devices and be more productive on the go. SpeechKit technology powers voice commands for Yandex search and is also used in Yandex’s traffic information app, Yandex.Navigator, offering motorists voice activation control. The SpeechKit SDK enables businesses to easily integrate Yandex’s speech technologies in their productivity tools and virtual assistants.
  • Translation – With more than 90 languages in production, Yandex is one of very few companies in the world that has access to enough data to meet today’s high machine translation standards. Yandex.Translate uses machine learning throughout its stack, including unique technology for translating rare languages that don’t have enough written data to use classical methods, instead relying on linguistic structures from related popular languages to fill in the gaps.

From speech-to-speech translation to virtual assistants that chat with people and use cameras to see, the MIR division offers amazing opportunities for synthesis and cross-pollination within Yandex’s machine learning, computer vision, speech and translation technologies. By bringing team members from these core technologies together, the MIR division will improve Yandex’s machine and natural processing capabilities, enhancing its products and services and ultimately delivering consumers and businesses a better experience.

Under Misha Bilenko’s guidance, the unified division will be able to integrate its top research findings across all of Yandex products and services. Misha joins Yandex after 10 years of experience working at Microsoft, where he led the Machine Learning Algorithms team in the Cloud and Enterprise division, following a career in the Machine Learning Group for Microsoft Research. Misha brings a unique blend of leadership skills, research expertise and machine learning knowledge to Yandex. His leadership will be instrumental as the MIR division expands Yandex’s research efforts to experiment with new projects and achieve more long-term goals building the next generation of intelligent products and services.

Yandex Provides Hyper-Targeting Opportunities to Advertising Clients

Yandex unveiled a new service for businesses advertising their products on the company’s websites, as well as websites in the Yandex Advertising Network, at its annual e-marketing conference Yac/m. The new service, Yandex.Audience, allows companies use their own customer information to segment audiences for hyper-targeted advertising, as well as target their ads to existing groups of customers to boost upselling campaigns, improve retention, and increase average spend.

After uploading customer information, such as email addresses, telephone numbers or device IDs, to Yandex.Audience, an advertiser receives anonymised IDs identifying their customers among visitors on Yandex’s pages and the YAN websites. These people can now be personally targeted with offers relevant to their previous customer experience – a pair of shoes matching the bag they bought a week ago, or a special loyalty program to recapture lost customers. The same data can be used to identify lookalike audiences – groups of people who exhibit characteristics similar to those of the existing customers and are likely to be interested in the offers that the existing customers were interested in – and target ads to them.

Yandex.Audience is available in English and Russian. To start creating hyper-targeted ad campaigns, an advertiser needs to sign into their account with Yandex’s auction-based service for contextual advertising Yandex.Direct and enter their customer data in the .txt or .csv file. The IDs returned by Yandex.Audience can not identify any individual user, but can be used for delivering personally targeted ads.

Medium- to large-scale businesses such as retailers, banks, car dealers, insurance companies, possessing reasonably large amounts of customer data and striving for customer conversion will appreciate this service most. The amount of data required for hyper-targeted advertising starts at 1,000 records. There is no upper limit for the number of records that can be uploaded to the service, neither is there a limit for the number of types of audiences or hyper-targeted advertising campaigns.

In addition to hyper-targeting opportunities, Yandex.Audience will soon be providing tools for marketing analysis. Yandex's proprietary behaviour analytics technology Crypta, which can identify web users’ interests, age, gender, family status, and even if they have a car or a pet, based on their behaviour online will soon be added to the service. Thanks to this technology, advertisers will be able to use social and demographic statistics of their audiences to plan their marketing strategies.

Yandex Unveils First Browser with Infinite Personally Targeted Recommended Content

Yandex builds personalised content recommendation technology Zen into Yandex Browser on all platforms in 24 countries and 15 languages. Based on the latest developments in artificial intelligence research, Zen recommendation technology uses the company’s vast global web index to pick stories, images, videos and other content for each individual user and offer it them right in the new tab of Yandex Browser.

zen 3.002 (1).png

The intelligent content discovery feed in Yandex Browser delivers recommendations based on the user’s location, browsing history, their viewing history and preferences in Zen, among hundreds of other factors. Zen uses natural language processing and computer vision to understand the verbal and visual content on the pages the user has viewed, liked or disliked, to offer them the content they are likely to like. Yandex’s recommendation technology Disco, based on the company’s machine-learning algorithm, MatrixNet, helps Zen choose which suggestions to offer to the user at any given point in time. Targeted to identify the user’s personal long-term interests and cater to them, Zen also delivers content not directly related to their immediate preferences. The more the user interacts with Zen, the better are the chances that they will see serendipitously interesting content.

‘With all the vastness of information available on the internet, something genuinely interesting isn’t easy to come by. Zen helps solving this problem,’ says Victor Lamburt, head of Yandex Zen. ‘It points each user to what’s interesting specifically to them. This is the future for all web browsers: providing personal internet experience and helping people discover something new’.

The infinite personally targeted content feed in Yandex Browser gives web users an opportunity to discover something they appreciate, but wouldn’t have found it otherwise. To start exploring this new internet experience, all one needs to do is download Yandex Browser and give Zen some browsing history to work with. Alternatively, liking or disliking a few websites on Zen’s start up page will help it understand your preferences on the outset. Users can also alter the type or topic of content they are offered later on by choosing to view more of similar content, less of it, or block specific sources altogether.

Zen first appeared as an experimental feature in Yandex’s launcher app for Android in Mexico and Brazil in 2015. The average time the users spent viewing Zen’s recommended content has increased since then from only 5 minutes to 20 minutes in May 2016. Zen is currently available both in Yandex Launcher and Yandex Browser for iPhone, Android mobile devices and Windows PC and laptops.

Yandex’ personal content recommendation technology can also be easily integrated into third-party mobile applications, such as browsers or launcher apps, and offers great monetisation potential for OEMs, app developers, and mobile carriers.

Yandex Browser Pioneers Built-in DNS Security

Yandex kits out its browser with built-in domain name system protection technology to safeguard all users of Yandex Browser against DNS spoofing. This is the first time a browser comes with a DNS security technology on board.

Yandex Browser’s built-in active security system Protect provides a comprehensive anti-fraud defense against the majority of currently existing cyber-threats. It automatically checks all downloaded files for viruses, warns users about dangerous websites, and protects their passwords when using public networks.

Yandex Browser’s newly added line of defence, DNSCrypt, is a protocol that authenticates communications between a browser requesting a DNS address of a website and a DNS server offering this address. Provided by renowned DNS security expert, OpenDNS, this protocol will now be doing its job right through the browser, without user's having to purchase, download or activate a separate security product.

DNS spoofing, when your requested website is replaced with a fraudulent website somewhere server-side, or router hijacking, when your router's DNS is changed by malware, according to the industry experts, affect millions of modems and routers worldwide.

Now, instead of going to an unknown DNS resolver, all your requests made through Yandex Browser will go straight to one of 80 secure and fast DNS servers owned by Yandex in multiple locations all over the world. In addition to using a verified DNS resolver, the DNSCrypt protocol encrypts communications between the browser and the server making them impossible to intercept.

Yandex Browser with DNSCrypt is available for Windows and OS X and can be downloaded from here. To start enjoying the browser's DNS protection, turn on the DNSCrypt encryption in settings.

The option to choose a DNS resolver to communicate with your Yandex Browser will become available in the near future.