On June 18th, Shenzhen Di Ling Intelligent Technology Co., Ltd., a leading enterprise-grade AI agent platform, officially launched its independent third-party GEO (Generative Engine Optimization) brand visibility diagnostic platform — FeiSentry. As the industry's first neutral monitoring tool dedicated to the quantitative assessment of GEO effectiveness, FeiSentry aims to address current industry pain points such as inconsistent service standards, difficulty in verifying results, and frequent data falsification. It provides businesses with objective and transparent diagnostic services for their brand's performance within the AI ecosystem. It is reported that the platform will offer free trial access to all industry enterprises starting from its launch day.
Industry Boom Marred by Chaos: Standardization is Urgently Needed
With the proliferation of generative AI, large language models are gradually replacing traditional search engines, becoming the primary gateway for users to access information and make consumption and business decisions. Data indicates that the daily call volume for mainstream domestic large models has reached the trillions. GEO, as a method for optimizing brand mindshare in the AI era, has consequently become a new, fiercely contested battleground for enterprises. However, alongside rapid industry expansion, issues of unregulated development have become increasingly prominent. Some service providers use low-cost exposure as a gimmick, employing low-quality content, mass generation, or even false sources to achieve short-term results. This not only fails to create long-term value for brands but may also leave erroneous, negative brand imprints within large models, polluting brand assets built up over years by companies. Simultaneously, the industry has long lacked unified standards for evaluating effectiveness, leading to inconsistent delivery quality from service providers and making it difficult for enterprises to verify real results. Consequently, many brands either suffer losses from missteps or adopt a wait-and-see attitude towards GEO, missing out on the brand growth opportunities presented by the AI era.
It is precisely within this industry context that the China Artificial Intelligence Industry Alliance (AIIA) initiated the development of technical standards related to GEO, aiming to steer the industry away from unchecked growth towards standardized development. Not long ago, Di Ling Intelligence formally passed a rigorous review to become an AIIA member and was invited to participate in the discussion and formulation of the technical specification for "Generative Engine Optimization (GEO) Service Capability Assessment." During the seminar, Di Ling Intelligence's AI expert Lu Yong proposed that GEO standard development should focus on three key dimensions: data authenticity, content compliance, and effect quantifiability, to establish a unified benchmark for the industry. The launch of the FeiSentry platform represents a significant step by Di Ling Intelligence in translating these standard concepts into a practical product.
Neutral Positioning and Comprehensive Capabilities: FeiSentry as the "Fair Ruler" for GEO Effectiveness
According to reports, FeiSentry is positioned as an independent third-party GEO monitoring platform. It does not provide GEO optimization services itself but focuses on objective and precise effectiveness evaluation. The platform has built a comprehensive assessment system around four core dimensions: AI visibility, narrative quality, model recommendations, and industry competitive landscape, featuring five key capabilities. First is foundational diagnostic capability: enterprises not yet engaged in GEO can input their brand name and receive a complete diagnostic report within 15 minutes, helping them establish a baseline for their brand's visibility in the AI ecosystem. Second is effectiveness verification capability: it can quantitatively verify the results of GEO services already purchased by a company, with full data supporting traceability and compliance audits, addressing the pain point of "not knowing if the money spent was effective." Third is industry landscape insight: it outputs a comprehensive panorama of AI recommendations within the relevant industry, helping businesses intuitively understand the AI performance of leading brands and the overall competitive situation in their sector. Fourth is competitor comparative analysis: it benchmarks against competitors on core metrics such as AI share of voice, first-mention rate, sentiment, and recommendation priority, helping companies clarify their competitive position. Fifth is cross-platform synergy capability: it can integrate data with Di Ling Intelligence's Chi Tong public opinion monitoring platform, forming a two-dimensional brand management system combining "pan-network public opinion risk monitoring + GEO brand visibility diagnosis," enabling businesses to achieve risk warning, quantifiable reputation, and performance tracking within the AI ecosystem.
To ensure the authenticity and reliability of data, FeiSentry incorporates three core design standards. First, it simulates real user queries through genuine user accounts, replicating the brand presentation from an ordinary user's perspective as much as possible to avoid data distortion from sampling. Second, it fully retains the original records, source links, and sentiment analysis details for every Q&A set, with all data being traceable and cross-verifiable. Third, it provides enterprise users with full access to the original monitoring data and analysis reports, ensuring complete transparency of the evaluation process. The platform currently covers mainstream large models including DeepSeek, Doubao, Kimi, Yuanbao, and Baidu AI.
Technical Foundation: Evolving from User to Industry Co-builder
The launch of FeiSentry is underpinned by Di Ling Intelligence's long-term technical accumulation and industrial practice in the enterprise AI field. As one of the earliest domestic players in the enterprise AI agent sector, Di Ling Intelligence has consistently adhered to the mission of "leveraging AI wisely to promote long-term harmonious coexistence between humans and AI." Relying on its self-developed BlackZero hybrid intelligent agent cluster technology foundation, the company has focused on high-value-added, high-complexity industrial scenarios such as legal, branding, and investment. It has developed flagship products like Contract Assistant, Brand Assistant, and Investment Assistant, and pioneered the AaaS (Agent as a Service) model, becoming a benchmark in the field of AI application commercialization through sustained profitability.
Due to its outstanding technical strength and industrial value, Di Ling Intelligence has recently garnered multiple authoritative industry recognitions. It has been selected for the 2025 Greater Bay Area High-Growth Enterprise Case Studies and the 2026 China MaaS Vendor TOP100 list, and has won awards including the "Annual Industry Leading Brand" from the Spire Awards and the 2026 AI Technology Innovation Award. The company has also established a joint AI Engineering Research Center with Henan University Shenzhen Research Institute, continuously deepening industry-academia-research collaborative innovation.
Joining the AIIA and launching the FeiSentry platform marks a shift in Di Ling Intelligence's role from a technology user to a co-builder of industry standards and a participant in ecosystem governance. Industry insiders note that the launch of FeiSentry fills a market gap for independent third-party GEO effectiveness monitoring in China. It provides enterprises with a "fair ruler" to measure GEO effectiveness and will also compel GEO service providers to improve their service quality, driving the industry's transition from unchecked growth to standardized development. In the future, with the gradual implementation of industry standards and the introduction of more compliance tools, the GEO industry is expected to foster a healthier development environment, genuinely helping enterprises seize brand growth opportunities in the AI era.
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