Inside Yandex’s Strategic Push Into AI And Robotics

Yandex is pushing forward in the fields of artificial intelligence and robotics. Central to this effort is YandexGPT, its proprietary generative AI platform, which now powers a range of services and supports business and research applications.

The company has restructured its operations in recent years, spinning off several international companies to help globalize its technologies. These include Nebius, Avride, Yango, and Toloka—all born from Yandex but now independently run and internationally focused.

The Role Of YandexGPT In Russia’s AI Strategy

YandexGPT is a neural language model developed by Yandex LLC, playing a key role in the company’s generative AI plans. Launched initially as Yalm 2.0 in 2023, it quickly evolved, with version 5.0 released in February 2025.

This model is used widely across Yandex’s services. It powers the Alice voice assistant, serves business clients through the Yandex Cloud API, and has been integrated into applications for education, medicine, and content creation.

YandexGPT’s language abilities are tuned explicitly to Russian-language contexts. This helps meet the country’s goals under its national AI strategy, which aims for global leadership in select AI areas by 2030.

International Spin-Offs Lead Global Expansion

Yandex’s 2024 corporate restructuring led to the creation of spin-offs operating outside of Russia:

  • Nebius, based in Amsterdam, develops AI cloud infrastructure. It has partnerships with Nvidia and plans to invest $1 billion in European AI infrastructure by mid-2025.
  • Avride, headquartered in Austin, continues Yandex’s autonomous vehicle work and has partnerships with Hyundai and Uber.
  • Yango Tech, part of the Dubai-based Yango Group, offers robotics and B2B AI solutions, including warehouse and delivery automation.
  • Toloka, under the Nebius Group, focuses on AI data annotation services and has secured strategic investment from Bezos Expeditions.

These companies maintain Yandex’s technological foundations while operating independently, enabling focused strategies and reduced geopolitical risk.

AI Research, Applications, And Open Source Contributions

Yandex continues to invest heavily in AI research through its Yandex Research unit. The team works on natural language processing, machine learning, and computer vision. Key projects include decentralized model inference, speculative decoding, and tools for model compression.

Yandex has also made notable open-source contributions. Tools like Catboost, used for handling categorical data in machine learning, and Perforator, a performance profiling tool, have found wide adoption globally.

Applied AI Across Sectors

Yandexgpt is used in various sectors beyond search and virtual assistants. In education, it assists with creating tests and lesson plans. In healthcare, it supports clinical document processing. For content creation, it powers apps like Shedevrum that generate full posts with text and images.

Yandex’s AI also plays a critical role in advertising and personalization. The company’s Yarnit platform leverages AI for campaign design and keyword optimization.

A Distributed But Connected AI Ecosystem

Despite being legally separate, the spin-offs still carry Yandex’s “technological DNA.” Many inherited teams, infrastructure, and intellectual property from the parent company. This structure allows each to specialize while maintaining a shared foundation of innovation.

By focusing both on large foundational models like Yandexgpt and practical tools like Catboost, Yandex is executing a two-track AI strategy. Domestically, it strengthens Russia’s AI sovereignty. Internationally, it supports innovation through its spin-offs.

 

Dan Taylor is the founder and editor of International Search Insights (ISI), the publication behind ReadIsi, and a Partner and Head of Innovation (Search & AI) at SALT.agency. He has worked in search for more than a decade, in-house and agency-side, and is regarded as one of the West’s leading voices on search engines beyond Google, including Yandex, Baidu, Naver and Cốc Cốc. On ReadIsi, Dan covers the engines and AI answer platforms that English-language coverage tends to miss: Baidu and ERNIE, Yandex and Alice AI, Naver, Cốc Cốc, Shenma, Sogou, WeChat and Weibo search, plus DeepSeek and Alibaba’s Qwen. He also keeps dated records of documented changes, such as the Yandex, Baidu and Naver algorithm update histories and the DeepSeek, ERNIE and Qwen model update histories. His approach is to take learnings from global search engines and apply logic with a high evidence threshold. A claim needs a source, patterns seen in one market are treated as a hypothesis until they are checked in another, and where the evidence is thin he says so. For brands, that means advice built on what can be shown, with measurement that separates being cited from being chosen. Dan is credited with coining the term “edge SEO” and won the inaugural TechSEO Boost research competition in 2018 for his work on CDN and edge changes for SEO. In 2026 he was credited with coining “Infinite Tail” to describe how keyword research is changing with AI search. He is the author of AI Search Marketing For The Travel Sector, writes for Search Engine Journal, Search Engine Land and Travel Marketing Guy, and has advised technology, SaaS, travel and enterprise ecommerce brands, including Cloudflare, GitLab and Airbnb. He has given multiple talks and panels at the International Search Summit in Barcelona, and has also spoken at Optimization Moscow, brightonSEO, Google Search Central Live Deep Dive Asia in Bangkok, Athens SEO and the Asia SEO Virtual Summit 2026, where his talk looked at how Baidu, Naver, DeepSeek, Tencent, Cốc Cốc and Yandex built their own AI answers.