GigaChat

SECURITM Launches MCP Server for External AI Access to Security Data

SECURITM has introduced an MCP server that connects external AI assistants directly to its platform data on assets, risks, tasks, and metrics. This marks the first such implementation among Russian SGRC and SOAR systems. The open MCP protocol enables natural language queries about critical assets without owners, overdue tasks, or monthly metric changes without manual data export. Supported tools include GigaChat, Yandex solutions, Claude, ChatGPT, Cursor, and compatible local models. Access remains strictly read-only through dedicated tokens with optional IP restrictions. The feature is available in paid cloud and on-premise editions and complements the platform’s built-in AI assistant.

GigaChat Creates New Continuation of Gogol's Dead Souls Under Expert Supervision

Sber's GigaChat generative AI model has produced a new version of the second volume of Nikolai Gogol's Dead Souls, which the author himself destroyed in 1852. The project involved training the model on Gogol's writings, letters, drafts, works by his contemporaries, and philosophical and religious texts that may have influenced the writer. Historians, literary scholars, linguists, and engineers guided the process to ensure the creation of original images and meanings rather than recycled phrases. Experts reviewed every fragment of the generated text for authenticity and quality. Illustrations were also produced by an AI model based on the style of Alexander Agin, who illustrated the first volume during Gogol's lifetime. Sber states the goals are to demonstrate AI as a creative and analytical tool in the hands of specialists and to attract younger readers to Russian classics. Vladislav Kreynin noted that the work does not resolve debates about the lost original manuscript.

Russia Weighs Mandatory Use of Sovereign AI Models Like GigaChat in Government Sectors

Russian authorities are discussing a draft government resolution that would require state bodies and companies to prioritize fully domestic AI models in multiple regulated areas even when they cost up to 50 percent more than alternatives. Only GigaChat developed by Sber currently meets the proposed sovereign criteria of being created by a Russian legal entity and running exclusively on Russian infrastructure. National models such as Yandex’s Alice AI would be allowed to incorporate open-source components. The measure would apply to law-making, national projects, taxes, customs, critical information infrastructure, education, healthcare and Gosuslugi services. The Ministry of Digital Development stresses that the list remains preliminary and open to further input from market participants. Industry players including Yandex and MWS AI have voiced concerns over reduced choice and potential quality or cost disadvantages for end users.

Building Secure On-Prem AI Assistants: How to Keep Corporate Data Inside Closed Contours

Many organizations hesitate to deploy AI assistants due to strict data protection rules that prohibit sending information to external clouds. The article explains how to implement AI models entirely within a company's own infrastructure, ranging from on-premise servers to fully offline laptops. It breaks down four deployment locations from public APIs to local devices and clarifies three distinct access levels: read, write, and execute. The author emphasizes that most business value comes from read-only access combined with human-in-the-loop controls for any irreversible actions. Practical recommendations include RAG over model size, quantization for local hardware, and maintaining immutable audit logs. The piece also warns that preparing clean knowledge bases often consumes more effort than the model itself.