据悉，包括华视锐达在内，2025年奉化已成功招引3家外省文化企业落户上规，形成了良好的集聚发展 态势。这批新生力量正与奉化现有的产业基础深度融合，共同驱动着区域文化产业向数字化、智能化、 高端化迈进，为奉化经济高质量发展培育了新的增长极。 奉化区委宣传部相关负责人表示，通过引入北京的资本与生态资源，不仅助力企业飞跃式发展，还有效 反哺奉化本土的数字经济产业生态，吸引更多上下游关联企业关注奉化、落户奉化。 作为奉化引进的优质文化科技企业，华视锐达（宁波）科技有限公司以"人工智能+企业营销"为核心定 位，其自主研发的AI营销平台"BAIMA"具备鲜明的技术领先性与落地能力。北京国信中数投资管理有 限公司在AI产业投资、数字生态构建等领域积累了丰富实践经验，此次战略合作将实现双方核心优势 的深度叠加，形成"资源支撑+技术落地+生态共建"的合作闭环。 华视锐达的成功签约，是奉化区创优文化产业营商环境进程中落下的的一个生动注脚。近年来，奉化区 紧紧围绕"文化+"战略，通过构建精准高效的服务体系、制定具有吸引力的产业政策、打造特色鲜明的 产业平台，成功吸引了一批优质文化科技企业聚集。 11月19日下午，华视锐达（宁波）科 ...

Core Viewpoint - The company is implementing a "comprehensive AI" strategy in 2024 to enhance business efficiency and reshape its commercial ecosystem through AI technology applications in various business areas, including consumer content, smart marketing, and consumer data [1][3]. Group 1: AI Strategy and Product Matrix - The company has developed an AI product matrix consisting of "1 large model, 2 databases, 3 engines, and 4 types of applications" to support its AI strategy [2]. - The "large model" is the "Zhidingmai Consumption Model," trained on 300G of consumer data and completed through 1.2 billion iterations, providing intelligence for AI products and applications [2]. - The "databases" include a "product database" with 1 billion product entries and a "content database," which also offers data services to third-party model companies [2]. Group 2: Cost Reduction and Efficiency Improvement - The company is leveraging AI technology to enhance efficiency and reduce costs across various business and management processes, with a focus on AIGC as a key strategic project since 2023 [3]. - In 2024, the content publishing volume on the "Zhidingmai" platform reached 34.0419 million, a year-on-year increase of 19.31%, while reducing the cost per content piece [3]. Group 3: Content Review and User Satisfaction - The company has restructured the content review process on the "Zhidingmai" platform using the AIUC engine, reducing human involvement and standard deviation in reviews [4]. - In 2024, the time for reviewing original content was shortened by 75%, and the volume of content requiring human review decreased by 57%, leading to improved user satisfaction [4]. Group 4: Ecosystem Collaboration - The company is actively participating in the co-construction of third-party AI ecosystems, aiming to optimize consumer decision-making experiences as information acquisition methods evolve [4]. - Collaborations have been established with various general model companies and smart terminal products to provide consumer content information and accelerate AI technology development [5].