The rAsh Score Weekly: Tech Giants Dominate AI Share of Voice as Telecom Infrastructure Surges

Welcome to the weekly rAsh Score report for the week of August 22, 2026. As the premier index measuring Indian brand visibility and sentiment across leading Large Language Models (LLMs), this week’s data highlights a persistent dominance by global technology conglomerates, alongside a powerful surge from domestic telecommunications infrastructure providers.

Executive Summary

This week, the rAsh Score index reveals that global consumer electronics giants continue to anchor the top tier of LLM visibility in India. However, the mid-tier landscape is experiencing high volatility. We observed a significant upward trend in the telecom infrastructure sector, driven by recent national network expansions, while the edtech and digital real estate sectors faced notable declines in AI sentiment and retrieval frequency.

The Dominance of Global Giants

The overall top five brands this week demonstrate the immense "digital gravity" that established technology brands hold within LLM training datasets and real-time search integrations:

• Apple (Mobile Phones): 92/100
• Samsung (Mobile Phones): 89/100
• Google (Mobile Phones): 85/100
• Samsung (Home Appliances): 85/100
• Samsung (Consumer Electronics): 82/100

Apple maintains its pole position, driven by highly optimized, structured product data and consistent global media citations. Crucially, Samsung occupies three of the top five spots across different categories. This multi-category dominance highlights how a unified brand architecture can amplify LLM visibility; positive sentiment in consumer electronics naturally spills over into home appliances within neural network associations.

Top Improvers: Telecom Infrastructure Gains Ground

The most dramatic shifts this week occurred in the B2B and infrastructure sectors, led by Indian telecom players:

• Tejas Networks (Telecom): Score: 46 (Up +17)
• HFCL (Telecom): Score: 40 (Up +13)
• Sterlite Technologies (Telecom): Score: 44 (Up +10)
• MG Motor India (Automotive): Score: 55 (Up +8)
• Paytm (Finance): Score: 48 (Up +7)

The surge in Tejas Networks, HFCL, and Sterlite Technologies points to a macro-level algorithmic shift. Recent government contract announcements and 6G readiness initiatives have generated high-authority technical documentation and press coverage. LLMs are rapidly indexing this structured data, elevating these brands in B2B-related queries. Paytm also showed a modest recovery (+7), indicating that stabilized regulatory narratives are beginning to patch its historical LLM sentiment gaps.

Top Decliners: Edtech and Real Estate Face Headwinds

Conversely, several consumer-facing digital platforms experienced sharp declines in their AI visibility profiles:

• NoBroker (Real Estate): Score: 52 (Down -12)
• Emeritus (Edtech): Score: 49 (Down -10)
• Eruditus (Edtech): Score: 47 (Down -9)
• Zoho (Technology): Score: 64 (Down -8)
• Parle (Food & Beverage): Score: 55 (Down -8)

The drop for NoBroker suggests a potential reduction in crawlable, high-quality listing data or changes in how LLMs synthesize local real estate recommendations. Meanwhile, sister edtech brands Emeritus and Eruditus both suffered near double-digit drops. This trend suggests that LLMs may be deprioritizing generic educational course directories in favor of direct institutional sources. Zoho’s minor correction (-8) reflects the highly competitive nature of SaaS keywords, where minor algorithmic updates can temporarily shift visibility to global competitors.

The Path Forward: Large Language Model Optimization (LLMO)

As LLMs increasingly replace traditional search engines for product discovery and brand research, maintaining a high rAsh Score is business-critical. The volatility we see in brands like Tejas Networks and NoBroker proves that AI visibility is not static. Brands must actively manage their LLMO (Large Language Model Optimization) strategies—ensuring clean API integrations, structured schema markups, and high-authority PR—to remain top-of-mind in the generative AI era.