Infosystems Jet

Ideco NGFW Novum Earns Highest Customer Rating in Quadrant Technologies Import Substitution Study

Ideco NGFW Novum achieved the top customer score of 6.9 out of 10 in the Matrix of Import Substitution 2026: NGFW research conducted by Quadrant Technologies, surpassing the market average of 6.3 and outperforming seven competing Russian solutions. The study evaluated vendors based on specialized revenue alongside 18 criteria covering product quality and functionality, with ratings provided directly by specialists who deploy and operate the firewalls in production environments. Ideco excelled in 11 parameters above seven points, including administration convenience at 7.9, technical support and partner network at 7.6, Zero Trust segmentation at 7.3, and both integration capabilities and core NGFW functionality at 7.2. Despite strong product scores, Ideco remains in the Development quadrant rather than Leadership due to lower profile revenue volume, positioning the company as a prime candidate for advancement with increased sales and large-scale deployments. Complementary testing by Infosystems Jet laboratory showed Ideco NGFW Novum passing 189 of 242 checks under Methodology 3.0 and becoming the sole participant to complete an eight-hour stress test. The broader Russian NGFW market is shifting away from emergency import substitution toward demands for real-world stability, updates, documentation, support, and usability, with product cost cited as a rejection factor by 37.5 percent of respondents.

86% of Large Russian Companies Use or Pilot LLMs While Autonomous AI Agents Remain Rare in Production

A joint study by Infosystems Jet and Smart Ranking reveals that 86% of major Russian organizations are already deploying or testing large language models, with 53% having moved generative AI solutions into full production. Adoption drops sharply for more autonomous systems: only 15% run semi-autonomous AI agents in production, while fully autonomous and multi-agent setups reach just 8% each. The primary barriers are not model availability but insufficient process maturity, data infrastructure readiness, and integration complexity, cited by 44% of respondents. Additional obstacles include server costs (58%), legal risks (56%), budget limits (42%), and talent shortages (40%). Nearly half of surveyed companies report no measurable financial return from AI projects so far, highlighting the gap between pilot success and scalable value. The research covered 52 large firms employing roughly 450,000 people in total.