After Nine Years of Selling Algorithms, Can Lingdian Yoush Be Saved by the AI Wave?

Nine Years of Stagnant Revenue: The Growth Dilemma of an 'Algorithm Company'

In the A-share market, there is a category of companies that have long branded themselves with labels like 'data intelligence' and 'algorithm-driven,' attempting to ride every wave of technological advancement — yet consistently failing to deliver on performance. Lingdian Yoush (301169.SZ) is one of the most representative among them.

According to public financial reports, Lingdian Yoush's annual revenue has hovered around 300 million yuan from the period before and after its listing to the present, failing to break the 400 million yuan threshold in nine years. For a company whose core business is 'data analysis and decision support,' such a growth trajectory inevitably raises the question: how much commercial value does this so-called 'algorithm capability' actually hold?

The Business Model Predicament: Project-Based Work Can't Support Scale

Lingdian Yoush's business foundation originates from traditional market research and consulting services. In recent years, the company has continuously emphasized its transformation toward 'data intelligence,' shifting its focus from traditional research to public affairs data analysis, digital city governance, and related fields. However, judging by financial performance, this transformation has yet to produce a qualitative breakthrough.

The core issue lies in its business model — project-based To G (government) and To B (enterprise) services. This type of business faces several inherent bottlenecks:

• Long revenue recognition cycles: Government projects are subject to budget approvals and acceptance procedures, resulting in generally lengthy payment collection periods
• Poor replicability: Each project involves high levels of customization, making it difficult to create standardized products for scalable replication
• Obvious growth ceilings: Under a project-based model, revenue growth is highly dependent on labor input, and marginal costs are difficult to reduce effectively

This means that even though Lingdian Yoush packages itself as an 'algorithm company,' its underlying logic is closer to that of a traditional consulting service provider rather than a genuine technology platform enterprise.

The Era of AI Large Models: Opportunity or an Even Greater Challenge?

Since 2023, the wave of generative AI and large language models has swept the globe, and virtually every company with any connection to data has tried to capitalize on this trend. Lingdian Yoush is no exception, having publicly stated on multiple occasions that the company is actively embracing AI large models and exploring ways to integrate large model capabilities into data analysis and decision support scenarios.

However, the AI wave may be a double-edged sword for Lingdian Yoush:

The optimistic side: Large models' capabilities in natural language processing, data analysis, and report generation could theoretically significantly boost Lingdian Yoush's service efficiency. If the company can package large model capabilities into standardized SaaS products, it could potentially break through the growth bottleneck of the project-based model and achieve a transformation from 'selling labor' to 'selling products.'

The harsh reality: AI large models are dramatically lowering the barriers to data analysis. Research reports and data insights that previously required professional teams can now be rapidly generated using general-purpose large model tools. This means the 'professional moat' that Lingdian Yoush has relied upon for survival is being eroded by the democratization of technology. More critically, at the AI infrastructure level, Lingdian Yoush neither possesses the capability to develop its own large models nor holds sufficient data asset moats. Facing the aggressive expansion of giants like Baidu, Alibaba, and Huawei in the government data intelligence space, its competitive room may be further compressed.

Where Is the Inflection Point? Three Key Dimensions to Watch

To assess whether Lingdian Yoush can reach a true growth inflection point in the AI era, the following three dimensions warrant ongoing observation:

1. Can the productization rate improve?

The core metric is the proportion of standardized product revenue to total revenue. Only if the company can launch AI-based standardized data analysis platforms or tools and achieve meaningful product-driven revenue can it demonstrate substantive transformation progress.

2. Can gross margins improve?

Under the project-based model, room for gross margin improvement is limited. If the introduction of AI tools can effectively replace manual processes and enhance delivery efficiency, this should be reflected in gross margins. If gross margins remain persistently low, it indicates that AI empowerment is still at the conceptual level.

3. Can the client structure be optimized?

The revenue volatility risk from over-reliance on government clients cannot be ignored. Whether the company can expand into the enterprise market and diversify its client base is a critical indicator of its risk resilience and growth potential.

Final Thoughts

Nine years of revenue that has never exceeded 400 million yuan — this figure alone speaks volumes. In an era of rapid AI iteration, the word 'algorithm' is no longer a scarce label. For Lingdian Yoush, the AI wave could either be an opportunity to reshape its business model or accelerate the exposure of its insufficient core competitiveness.

The market will not pay for 'narratives' forever. What Lingdian Yoush needs is not more AI storytelling, but substantive growth that can be verified by financial reports. As for when the inflection point will arrive, the answer may not lie in technology trends, but in whether the company can truly complete its metamorphosis from a 'project-based service provider' to a 'product-driven technology company.'