The first doctor version "Lobster" is here! DoctorClaw was exposed to internal testing, and AI healthcare has another major breakthrough!

A lobster, popular in the medical field. According to media reports, Baidu Health is currently incubating a safe and controllable professional AI intelligent assistant for doctors internally, with the internal code name "DoctorClaw", which has recently started internal testing. Currently, the project is still in the closed development stage, and the specific product form is unknown, but it is close to being launched. Informed sources say that in the short term, it may start with academic retrieval and work assistance, with the long-term goal of covering multiple scenarios including clinical, scientific research, and teaching. At the time of publication, Baidu Health officials have not responded to the above information. With the popularity of OpenClaw, Agent has once again become the focus of AI in the medical field. An analyst has stated that the performance and penetration rate of AI Agents are accelerating, generating numerous commercial scenarios in the medical and financial fields, and that Agents have entered a crucial stage for engineering implementation. In China, industry giants such as JD HEALTH, Tencent Health, Winning Health Technology Group, Shanghai Runda Medical Technology, Huawei, and Ant Group are actively deploying AI Agents to empower their own businesses. There are also some related startups like Ruosheng Technology and Heguang Digital, providing intelligent solutions for pharmaceutical companies, hospitals, insurance agencies, etc. According to the forecast of the Intelligent Medicine Advisory Research Institute, the penetration rate of AI Agents in China's medical field will continue to deepen, and the market size is expected to reach 41.8 billion yuan by 2031. AI Agents, revolutionizing healthcare AI Agents, or intelligent entities, are capable of perceiving their environment, making autonomous decisions, and executing actions. Ideally, humans only need to set goals in advance and supervise, and AI Agents can autonomously complete specific tasks. Compared to chatting Siasun Robot&Automation, Agent's capabilities have reached a higher level, solving various complex and changing tasks, rather than just providing suggestions or answers, making it one of the most important directions for AI development. In 2024, Bill Gates pointed out that the next 5 years will enter the AI Agent era, which will change the way people interact with computers and revolutionize the software industry. Deloitte predicts that by 2027, 59% of enterprises using generative AI will deploy AI Agents. Specifically in the medical field, AI Agents will cover the entire process of "prevention-diagnosis-treatment-rehabilitation", with the core value lying in the integration of multimodal data, optimizing decision efficiency, and ensuring safety. The combination of high-quality data and scarce scenarios will be a key breakthrough. The shock brought by DeepSeek has not completely disappeared, and the wave of AI Agents triggered by OpenClaw has arrived. In the future, intelligent entities are expected to take over from large models and drive the practical implementation of AI in the medical field. When Agents can meet the real needs of doctors and evolve from assistants to partners, many hospitals and companies overseas have realized the huge value of Agents and explored a commercial path. The top hospital in the United States, the Mayo Clinic, stated that in 2025, groundbreaking technologies to be evaluated and applied will include autonomous intelligent agents (Agentic AI) driven automated systems. In addition, startups such as Abridge, Nabla, and Ambience have seen the track of generating electronic medical records, helping doctors save a lot of time in writing medical records through "speech recognition (ASR) + generative AI" technology. OpenEvidence, as an AI diagnostic assistance tool designed for doctors, has rapidly gained popularity among American doctors through precise clinical support and innovative business models. In short, the explosion of medical Agents paints a revolutionary track. It is not just an efficiency tool, but also a key force in reshaping medical processes, improving diagnostic accuracy, and enhancing the doctor-patient experience. With the continuous growth and optimization of large models and Agents, the future trend is the intelligent hospital brain under the coordination of multiple intelligent entities. That is, the intelligent entity matrix consisting of guidance Agents, diagnostic Agents, quality control Agents, follow-up Agents, etc., is expected to reshape decision-making models for key scenarios such as optimizing clinical pathways and dynamically allocating resources. By 2030, Agents will take over non-core medical processes such as medical record quality control and scheduling systems, and the multi-agent collaborative system will basically cover personalized diagnosis and treatment for common diseases, support complex cross-departmental case joint consultations, and provide full-cycle services from pre-diagnosis health assessment to post-rehabilitation management. The future is promising, but there are still many issues with the current large models and medical Agents. Especially when the suggestions and plans made by Agents are adopted and lead to adverse outcomes, it is difficult to determine the responsibility, and regulatory frameworks need to keep up with technological developments. In addition, Agents need strong integration capabilities to maximize their value, but existing medical IT systems are provided by different vendors, often leading to poor effects due to data fluidity and fractured workflows. Despite the challenges, the wave of medical intelligence led by Agents is unstoppable and will profoundly impact the future health of each of us. Agents are not just a concept, they are essentially the inevitable path of AI towards a more practical and intelligent direction, and an important area that AI medical companies must focus on and invest in. From a strategic perspective, AI Agents are opening the door to the value restructuring battle of the medical industry, manifesting in three very important stage goals: focusing on traffic in the short term, building a closed loop in the medium term, and establishing a pattern in the long term. Medical AI, the next battleground Short term: traffic super entrance Agents will undoubtedly change the way users interact, providing intelligent services by deeply understanding user needs, potentially replacing search engines, traditional applications, and information systems, and becoming a new traffic entry point. For example, in the context of the traditional traffic dividend reaching its peak, the customer acquisition cost of Internet medical care continues to rise, while Agents allow users to directly access and use various tools through dialogue, redefining user touchpoints through a more natural interaction and more accurate service capabilities. This means that while Agents are expected to unify and expand entry points, they will also more accurately explore and match demand, leading to the restructuring of traffic value. In the future, the battle for the new round of AI Agents will also be a battle for traffic, becoming a must-win battleground for almost all AI medical companies. Therefore, in the short term, traffic will be the core indicator to measure AI Agents, the continuous growth of the user base provides a basis for Agent iteration, and also reflects the product's perception and capture of segmented demand in the medical field, as well as a deep understanding of user behavior. Mid-term: building a business closed loop The traffic and user retention obtained at a loss in the initial stage will be converted into business value in the mid-term. The logic behind this is that the monetization of medical Agents will depend on the maturity of the market and the development of user payment habits. In general, Internet medical care may see the economic benefits of Agents sooner. For them, Agents will soon improve key KPIs in their business processes, including increasing e-commerce repeat purchase rates and consultation order values. It is more challenging to target B-side customers such as hospitals and pharmaceutical companies, as it is difficult for To B to generate concrete economic benefits quickly, and they are also susceptible to the complex management models of large institutions and policy regulations. In addition, the form of billing also needs to be discussed. Commercial models explored within the industry include subscription-based systems, usage-based billing, and results-based billing. In the past, SaaS, which was hard to make money from, has left a deep impression on a group of Chinese entrepreneurs and investors. Compared to this, the costs of development, operation, and maintenance of Agents are expected to be lower, and more open in terms of business models, with profit situations likely to be much better than SaaS. Some investors have expressed that "over the next decade, money that cannot be earned in the Chinese SaaS industry may be realized through AI Agents", bringing hope for transformation to many medical SaaS companies. Long term: opening up growth space If GPT is equivalent to the Newcomen steam engine, showing the huge potential of AI to the world for the first time; DeepSeek is like the Watt steam engine, optimizing efficiency to lower the technical barriers and allowing AI to serve the public, entering the true era of large-scale applications. AI Agents are like the appearance of steam trains and steamships, representing the practical landing solutions of AI in specific industries, leading to a larger market. In the long run, the efficiency improvement and innovation in supply brought by AI Agents are expected to stimulate a new round of investment and demand release in the medical field, profoundly impacting the industry landscape and bringing development opportunities to relevant participants. Furthermore, due to the strong collaborative capability of Agents, this will lead to collective intelligence, where the ecosystem will become a key proposition in the future. This means that industry leaders not only need to continuously break through on basic research and development, but also need to make significant investments in building the ecosystem. This article is reprinted from the WeChat public account "Intelligent Medicine Bureau"; GMTEight edited by: Yan Wencai.