广告
加载中

“决策大模型第一股”中科闻歌上市后首份中报:收入增长46% AI产业赋能提速

龚作仁 2026-08-27 10:48
龚作仁 2026/08/27 10:48

邦小白快读

EN
全文速览

本文公布了决策大模型第一股中科闻歌上市后的首份中期业绩核心干货信息,具体如下

1. 业绩与资本进展:报告期内公司实现收入1.73亿元,同比增长46%,毛利同比增长47.2%,毛利率提升至55%,亏损幅度同比收窄超24%,经营效率持续改善;同时公司获纳入恒生综合指数,9月生效后有望成为港股通标的,进一步拓宽内地投资渠道。

2. 业务与研发进展:公司平台订阅及API服务收入增长94%,占比提升8.4个百分点,贡献超一半收入增量;上半年新签合同3.55亿元,平均项目交付周期从2023年的185天缩短至72天;研发投入同比增长59%,已经建成贯通全环节的全栈决策AI体系,最新推出工业决策大脑,目前已累计服务超100家工业领域机构客户。

中科闻歌的发展路径和业务布局,能为品牌商布局AI赋能、优化业务经营提供诸多干货参考,具体如下

1. 产品研发与转型参考:决策AI不同于普通生成式AI,可面向企业全业务流程提供从数据理解到执行的全环节支持,填补了生成式AI的产业应用空白。品牌商布局AI可以参考该路径,围绕自身业务流程需求打造适配AI能力,同时可逐步将项目型技术能力转化为标准化可复制产品,提升收入的可持续性。

2. 商业化与落地参考:中科闻歌打造的“广泛客户覆盖、标杆场景验证、标准化高效交付”模式,大幅缩短交付周期、提升经营效率,该模式可被To B品牌商借鉴用于AI业务落地;目前决策AI在轻工制造、能源电力等场景已经验证落地效果,设备故障预警准确率可达90%,有数字化升级需求的品牌商可对接相关能力升级生产运营。

这份财报透露出决策AI领域的最新发展变化,能为切入企业级AI服务的卖家提供机会参考和模式借鉴,具体如下

1. 市场机会提示:当前决策AI正处于高速增长期,企业客户对可持续的标准化AI服务需求暴涨,中科闻歌的平台订阅及API服务收入同比增长94%,贡献了超一半的收入增量,说明该方向市场需求旺盛,是切入企业级AI服务的卖家可重点布局的赛道。

2. 可借鉴商业模式:中科闻歌摸索出“广泛客户覆盖、标杆场景验证、标准化高效交付”的商业化模式,将平均交付周期从185天压缩至72天,在保持高研发投入的同时持续收窄亏损,经营效率不断提升,该模式值得To B领域的卖家参考学习。

3. 前景提示:目前决策AI产业落地尤其是工业领域已经有多个成熟标杆案例,头部企业已经打通资本渠道,获得充足资金支持技术研发和市场拓展,赛道整体处于上升期,对卖家来说是明确的增量机会。

这份财报为工厂推进数字化智能化转型提供了明确方向和干货参考,具体内容如下

1. 生产端AI赋能已有成熟落地方案:中科闻歌的决策AI已经深入工厂实际生产流程,可覆盖订单管理、生产排程、染色优化、质量检验等核心生产环节;在能源电力领域,其开发的设备预测性维护方案故障预警准确率达90%,可有效支撑设备运维决策,降低生产风险,这些落地案例证明AI已经能切实解决工厂生产端的实际问题。

2. 可对接的商业机会:当前决策AI服务商正在加快拓展工业场景,头部玩家已经累计服务超100家工业相关机构客户,正在将标杆场景验证的能力沉淀为可复制的工业智能解决方案,有智能化改造需求的工厂可以直接对接这类成熟服务商,降低自身转型的试错成本。

3. 转型方向启示:工厂数字化转型不需要只停留在单点智能化改造,可以依托决策AI实现从单点应用到贯穿全生产流程的智能决策与协同执行升级,中科闻歌推出的工业决策大脑已经能支撑这类全流程升级,为工厂转型提供了新的路径。

从这份财报可以看出决策AI服务领域的最新发展趋势,能为AI服务商提供方向参考,具体干货如下

1. 行业发展趋势:当前企业级AI服务正在从传统的一次性项目交付向平台化、标准化持续服务转型,中科闻歌的平台订阅及API服务收入增速达到94%,占比持续提升,已经成为主要增长来源,说明客户更认可可持续的AI服务模式,订阅制API服务是行业未来的核心发展方向。

2. 市场客户痛点:目前企业客户需要AI能深入业务全流程解决实际问题,普通生成式AI仅能提供内容生成服务,无法满足企业决策和生产流程的落地需求,决策AI刚好填补了这个市场空白,工业领域的需求尤为旺盛,是服务商拓展业务的核心赛道。

3. 可借鉴的解决方案:中科闻歌走的“技术沉淀+标杆场景验证+标准化复制”路径,能大幅提升交付效率,该模式值得AI服务商参考;其打造的覆盖全环节的全栈决策AI产品体系,也为服务商开发产品提供了参考框架。

这份财报反映了决策AI领域的市场需求和发展现状,能为平台商的招商、运营提供参考,具体干货如下

1. 市场需求方向:当前企业客户对标准化、可复制的决策AI服务需求快速增长,订阅及API服务需求增速接近翻倍,说明平台型AI决策服务的市场空间十分广阔,平台可以针对性布局AI产业赋能赛道,重点引入决策AI领域的优质服务商。

2. 优质项目参考:中科闻歌作为决策AI赛道的头部企业,已经形成完整的全栈决策AI产品体系,在轻工、能源等多个工业领域有成熟的落地案例,商业化模式清晰,增长速度快,已经获得资本市场认可,被纳入恒生综合指数,说明决策AI赛道的优质项目已经具备投资价值,平台可以加大对该赛道优质企业的招商和扶持力度。

3. 风险规避提示:决策AI赛道目前仍处于技术投入期,平台在引入相关企业时,需要重点关注企业的资本实力、研发投入和商业化进展,优先选择有核心技术积累、标杆客户验证、现金储备充足的企业,降低合作风险。

这份财报披露了决策大模型领域最新的产业发展情况,为研究AI产业发展提供了一手的案例参考,干货内容如下

1. 产业新动向:当前AI产业已经从C端生成式AI应用,向B端决策AI的产业赋能方向延伸,决策AI面向企业全业务流程提供支持,填补了生成式AI的产业落地空白,目前已经进入高速增长期,头部企业中科闻歌整体收入增长46%,核心订阅服务增长94%,已经在多个工业领域实现商业化落地,证明赛道已经从技术研发转向规模化推广阶段。

2. 商业模式新变化:AI企业正在从传统的一次性项目交付向平台化、标准化订阅服务转型,这种模式收入持续性更强,能有效提升经营效率,中科闻歌在保持高研发投入的同时亏损持续收窄,验证了该模式的可行性,为研究AI企业商业化提供了新样本。

3. 应用新趋势:AI产业赋能正在从单点应用向贯穿生产经营全流程的智能协同升级,中科闻歌推出的工业决策大脑就是代表性产物,为研究产业AI落地的下一阶段方向提供了新的研究对象。

返回默认

声明:快读内容全程由AI生成,请注意甄别信息。如您发现问题,请发送邮件至 run@ebrun.com 。

我是 品牌商 卖家 工厂 服务商 平台商 研究者 帮我再读一遍。

Quick Summary

This article shares key takeaways from the first interim financial report of ChinaScience Wenge, the first listed "decision-making large model" stock, after its IPO:

1. Financial and capital progress: During the reporting period, the company generated RMB 173 million in revenue, up 46% year-over-year (YoY). Gross profit grew 47.2% YoY, gross margin expanded to 55%, and net losses narrowed by more than 24% YoY, showing continuous improvement in operating efficiency. The company has also been added to the Hang Seng Composite Index, effective in September, and is expected to be included in the Stock Connect program, which will broaden access for mainland Chinese investors.

2. Business and R&D progress: Revenue from the company's platform subscriptions and API services grew 94% YoY, with its share of total revenue rising 8.4 percentage points, contributing over half of total revenue growth. In the first half of the year, the company secured RMB 355 million in new contracts, and cut the average project delivery cycle from 185 days in 2023 to 72 days. R&D spending increased 59% YoY, and the company has built a full-stack end-to-end decision AI system. It recently launched an industrial decision brain, and has served more than 100 industrial clients to date.

ChinaScience Wenge's development path and business layout offer actionable insights for brands looking to leverage AI and optimize operations:

1. Product R&D and transformation reference: Unlike generic generative AI, decision AI supports enterprises across full business workflows, from data interpretation to execution, filling the gap where generative AI falls short for industrial applications. Brands can follow this playbook to build AI capabilities tailored to their own workflow needs, and gradually convert project-based technical capabilities into standardized, replicable products to improve revenue sustainability.

2. Commercialization and go-to-market reference: ChinaScience Wenge's "broad client coverage, benchmark scenario validation, standardized efficient delivery" model has drastically shortened delivery cycles and lifted operating efficiency, a framework that B2B brands can adapt for their own AI initiatives. Decision AI has already proven its value in use cases including light manufacturing, energy and power, with equipment fault warning accuracy reaching 90%. Brands pursuing digital transformation can access these capabilities to upgrade their production and operations.

This financial report reveals the latest developments in the decision AI sector, offering opportunity and business model insights for sellers entering the enterprise AI service space:

1. Market opportunity signals: Decision AI is currently in a period of rapid growth, with enterprise demand for sustainable, standardized AI services surging. ChinaScience Wenge's 94% YoY growth in platform subscription and API revenue, which contributed over half of its total revenue increase, confirms strong market demand in this segment, making it a high-priority track for sellers targeting enterprise AI services.

2. Replicable business model: ChinaScience Wenge has developed a "broad client coverage, benchmark scenario validation, standardized efficient delivery" commercialization model that cut average delivery cycles from 185 days to 72 days, narrowed losses while maintaining high R&D investment, and continuously improved operating efficiency. This model is highly valuable for B2B sellers to learn from.

3. Growth outlook: Decision AI has already produced multiple mature benchmark cases for industrial deployment, and leading players have secured capital access to fund R&D and market expansion. The overall sector is in an upward cycle, representing clear incremental growth opportunities for sellers.

This financial report provides clear direction and actionable insights for factories pursuing digital and intelligent transformation:

1. Mature AI solutions for production: ChinaScience Wenge's decision AI has been integrated into actual factory production workflows, covering core links including order management, production scheduling, dyeing optimization and quality inspection. In the energy and power sector, its predictive maintenance solution achieves 90% accuracy in equipment fault warning, effectively supporting equipment operation and maintenance decision-making and reducing production risk. These real-world cases confirm that AI can already solve practical problems on factory production floors.

2. Accessible commercial opportunities: Leading decision AI service providers are accelerating expansion into industrial scenarios, with top players already serving more than 100 industrial clients and refining benchmark-proven capabilities into replicable industrial intelligence solutions. Factories with intelligent transformation needs can partner directly with these mature providers to cut trial-and-error costs for their transformation projects.

3. Transformation direction insights: Factory digital transformation does not need to be limited to isolated single-point intelligent upgrades. Decision AI enables a full upgrade from standalone applications to intelligent decision-making and collaborative execution across entire production workflows. ChinaScience Wenge's newly launched industrial decision brain already supports this end-to-end upgrade, offering a new path for factory transformation.

This financial report outlines the latest industry trends in decision AI services, providing strategic guidance for AI service providers:

1. Industry development trend: Enterprise AI services are shifting from traditional one-off project delivery to platform-based, standardized recurring services. ChinaScience Wenge's 94% YoY revenue growth for platform subscriptions and API services, whose share of total revenue continues to rise, confirms this model has become the primary growth driver. This shows clients prefer sustainable AI service models, and subscription-based API services will be the core growth direction for the industry going forward.

2. Unmet client needs: Enterprises today require AI that integrates into full business workflows to solve practical problems. Generic generative AI only offers content generation capabilities and cannot meet the demands of enterprise decision-making and production workflow deployment. Decision AI exactly fills this market gap, with demand particularly strong in the industrial sector, making it a core growth track for service providers expanding their business.

3. Replicable solution framework: ChinaScience Wenge's "technical accumulation + benchmark scenario validation + standardized replication" path drastically improves delivery efficiency, making it a valuable model for AI service providers to reference. Its full-stack end-to-end decision AI product system also provides a proven framework for other providers developing their own products.

This financial report reflects current market demand and development status of the decision AI sector, offering insights for platform merchants' investment attraction and operations:

1. Market demand direction: Enterprise demand for standardized, replicable decision AI services is growing rapidly, with subscription and API service demand nearly doubling, indicating huge market potential for platform-based decision AI services. Platforms can prioritize layout of the AI industry empowerment track, and focus on recruiting high-quality decision AI service providers.

2. Reference for high-quality projects: As a leading player in the decision AI track, ChinaScience Wenge has built a complete full-stack decision AI product system, with mature deployment cases in multiple industrial sectors including light industry and energy. It has a clear commercialization model, strong growth, and has already gained capital market recognition via its inclusion in the Hang Seng Composite Index. This confirms that high-quality projects in the decision AI track already have solid investment value, and platforms should increase investment attraction and support for high-quality enterprises in this sector.

3. Risk mitigation guidance: The decision AI track is still in the technology investment phase. When onboarding related enterprises, platforms should prioritize evaluating companies' capital strength, R&D investment and commercialization progress, and prioritize partners with core technical accumulation, benchmark client validation and sufficient cash reserves to reduce cooperation risk.

This financial report discloses the latest industrial development of the decision large model sector, providing first-hand case reference for research on AI industry development:

1. New industrial trends: The AI industry is currently shifting from C-end generative AI applications to B-end industrial empowerment via decision AI. Decision AI supports full enterprise business workflows and fills the deployment gap for generative AI in industrial scenarios. The sector is now in a period of rapid growth: leading player ChinaScience Wenge delivered 46% overall revenue growth and 94% growth for core subscription services, with commercial deployment across multiple industrial sectors, confirming the track has moved from pure R&D to the large-scale promotion stage.

2. New developments in business models: AI companies are transitioning from traditional one-off project delivery to platform-based, standardized subscription services. This model offers more sustainable revenue and effectively improves operating efficiency. ChinaScience Wenge has continuously narrowed losses while maintaining high R&D investment, validating the feasibility of this model and providing a new case for research on AI enterprise commercialization.

3. New application trends: Industrial AI empowerment is evolving from single-point applications to intelligent collaboration across entire production and operation workflows. ChinaScience Wenge's industrial decision brain is a representative example of this trend, providing a new research object for studying the next phase of industrial AI deployment.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

I am a Brand Seller Factory Service Provider Marketplace Seller Researcher Read it again.

8月25日,中科闻歌(1956.HK)发布截至2026年6月30日止六个月的中期业绩。这也是公司自今年6月26日登陆港交所以来发布的首份中期业绩报告。

报告期内,中科闻歌实现收入约1.73亿元,同比增长46.0%;毛利约9500万元,同比增长47.2%,毛利增速高于收入增速;毛利率提升至55.0%。

盈利能力方面,公司期内亏损同比收窄24.5%;经调整净亏损同比收窄29.5%。在保持较高研发投入的同时,公司亏损幅度进一步收窄,经营效率持续改善。

财报之外,中科闻歌也迎来资本市场新进展:8月21日,公司获纳入恒生综合指数,相关调整将于9月4日收市后实施、9月7日起生效。随着指数调整落地,中科闻歌有望成为港股通标的,进一步拓宽内地投资者参与渠道。

平台订阅及API服务收入增长94%

收入结构的变化,成为中科闻歌上市后首份中报的重要看点。

2026年上半年,公司人工智能决策平台部署收入约1.14亿元,同比增长29.5%,继续构成业务基本盘;平台订阅及API服务收入约5895万元,同比增长94.0%,占总收入的比重由上年同期的25.7%提升至34.1%,提高8.4个百分点。

按披露数据测算,平台订阅及API服务贡献了公司上半年约52%的收入增量,成为主要增量来源。

相较于一次性项目部署,平台订阅及API服务更能反映客户对模型、平台和智能体能力的持续使用需求。该类收入占比提升,也意味着中科闻歌在行业项目中沉淀的技术与产品能力,正加快向标准化产品、可复制方案和持续服务转化。

新签合同约3.55亿元,交付周期进一步缩短

商业化方面,2026年上半年,中科闻歌新签合同金额约3.55亿元,约为同期营业收入的2.1倍,为后续项目履约和收入转化提供业务储备。

报告期内,公司服务客户约290家,累计服务客户约750家。其中,超过30家标杆客户贡献收入约1.01亿元,占营业收入的58.0%。与此同时,公司平均项目交付周期由2023年的185天缩短至72天,产品化交付效率进一步提升。

新签合同、客户覆盖及交付效率等指标显示,中科闻歌正在形成“广泛客户覆盖、标杆场景验证、标准化高效交付”的商业化模式,为企业级决策AI在更多行业和客户中的复制推广奠定基础。

研发投入增长59%,完善全栈决策AI体系

中科闻歌核心创始团队源自中国科学院自动化研究所,长期聚焦决策智能方向。与主要提供内容生成服务的生成式AI不同,决策智能进一步面向企业业务流程,围绕数据理解、知识组织、推理分析、决策形成和行动执行提供技术与产品支持。

2026年上半年,公司研发投入约1.19亿元,同比增长59.0%;研发人员达到237人,占员工总数的41.5%。

报告期内,中科闻歌完成由DIOS向DOMA架构的系统性升级,并持续推进DIP决策智能平台、Decitron决策机、Claworks企业级智能体操作系统及TokSea企业级Token基础设施等产品研发,迭代雅意大模型和科学基础大模型,逐步形成贯通数据、模型、智能体、决策与执行的全栈产品体系。

报告期后,公司进一步发布覆盖“基—枢—核—脑—端”的决策AI树产品体系,并推出工业决策大脑,将数据、模型、智能体与具身智能终端相连接,推动决策AI由单点应用向贯穿生产经营流程的智能决策和协同执行升级。

决策AI加快产业落地,工业场景成效显现

目前,中科闻歌工业智能解决方案已累计服务超过100家机构客户,并在轻工制造、能源电力等领域形成代表性应用。

在某轻工业示范基地,公司将工业决策智能体应用于订单管理、生产排程、染色优化和质量检验等环节,推动AI能力进入实际生产流程。在某省级电网公司,公司开发的设备预测性维护解决方案实现约90%的故障预警准确率,可为设备健康评估、风险识别及运维决策提供支持。

这些案例显示,中科闻歌正将通用决策AI能力与行业知识、生产数据和业务流程相结合,并进一步把经过标杆场景验证的能力沉淀为可复制的工业智能产品和解决方案。

现金储备增至10.18亿元,上市后资本实力显著增强

随着全球发售募集资金到位,中科闻歌的资本实力和资产结构进一步改善。

截至2026年6月末,公司总资产约15.31亿元,较2025年末增长77.7%;净资产约11.77亿元,增长133.4%;

同期,公司持有现金及现金等价物约10.18亿元,较2025年末增长213.5%。公司全球发售所得款项净额约8.27亿港元,为后续技术研发、产品迭代及市场拓展提供了资本支持。

随着平台型收入占比提升、标杆场景逐步复制以及经营效率持续改善,中科闻歌正加快由项目交付向平台化、标准化和持续服务演进。

注:文/龚作仁,文章来源:Laborer,本文为作者独立观点,不代表亿邦动力立场。

文章来源:Laborer

广告
微信
朋友圈

FAQ回顾

中科闻歌2026年上半年经营业绩如何?

2026年上半年中科闻歌实现营收约1.73亿元,同比增长46%;毛利约9500万元,同比增长47.2%,毛利率达55%;亏损同比收窄24.5%,经调整净亏损同比收窄29.5%,经营效率持续改善。

中科闻歌的核心业务及产品布局是什么?

中科闻歌核心创始团队源自中科院自动化所,长期聚焦决策智能方向,已形成贯通数据、模型、智能体、决策与执行的全栈决策AI产品体系,覆盖决策智能平台、决策机、企业级智能体操作系统、雅意大模型、工业决策大脑等产品。

决策AI在工业场景有哪些落地应用?

目前中科闻歌工业智能解决方案已服务超100家机构客户,可应用于轻工制造领域的订单管理、生产排程、染色优化、质量检验环节,以及能源电力领域的设备预测性维护,故障预警准确率可达约90%。

中科闻歌上市后有哪些资本市场进展?

中科闻歌2026年6月26日登陆港交所,8月21日获纳入恒生综合指数,调整将于9月7日起生效,后续有望成为港股通标的;截至2026年6月末,公司现金及现金等价物达10.18亿元,资本实力显著增强。

这么好看,分享一下?

朋友圈 分享

APP内打开

赞 +1
+1
微信好友 朋友圈 新浪微博 QQ空间
关闭
收藏成功
发送
/140 0