Dify Brings AI Closer to Everyday Clinical Practice in Europe
From hospital onboarding to automating safety reports, a new AI middleware platform shows how tailored intelligence can reshape healthcare
Artificial intelligence in healthcare has long promised transformative efficiency, but few technologies have successfully bridged the gap between potential and practical application.
Dify, a Delaware-based open-source AI platform, has taken a deliberate approach to this problem. Its philosophy is not to replace medical systems, but to connect them more intelligently and securely.
For many healthcare professionals, administrative burden remains a major frustration. Physicians today spend almost half their time completing paperwork and only around a quarter of their time with patients. The situation has left clinicians eager for digital assistance but cautious of the limitations of consumer-grade AI tools. Dify’s team argues that the real challenge is not whether to adopt AI, but how to embed it meaningfully in day-to-day medical routines.
Dify positions itself as a middleware layer between human expertise and machine intelligence. Its interface connects clinical knowledge bases, HR systems, and compliance databases, enabling staff to retrieve information through natural-language queries. It’s not about automation for its own sake, but about building trust through transparency, citation, and accuracy.
At the AI in Health Summit, organized by The Economist and held in London on October 1, 2025, Yuqi Wu, a user experience designer at Dify, outlined how hospitals and pharmaceutical companies are utilizing this technology to streamline their operations.
She said the goal was simple: “to bring usable, safe, and transparent AI to professionals who don’t have the luxury of experimentation.”
Speaking to TechJournal.uk in an interview on the sidelines of the event, Wu said users of Dify’s platform can choose whichever large language models (LLMs) their locations and regulations permit — from OpenAI’s GPT and Anthropic’s Claude to Baidu’s ERNIE Bot and Zhipu AI.
“Our framework is designed to be flexible,” she said. “We want our users to work with any model that’s legally and technically accessible to them.”
Wu also noted that Dify’s AI agents can be adapted for various sectors beyond healthcare, including finance, education, and manufacturing.
In August 2024, the company completed its Series A funding round, which was led by investments from Chinese technology giants including Tencent Holdings and Alibaba. It employs about 70 people globally, with plans to further expand its engineering and customer success teams.
Building trust through intelligence
During her presentation, Wu described how one major hospital had struggled with fragmented internal knowledge. Policies were buried in PDFs, emails, and SharePoint folders, leaving new hires lost and HR departments overwhelmed by repetitive queries.
She said Dify helped the institution create a unified Knowledge Assistant, an AI-driven search and guidance system that understood staff queries in plain language and returned authoritative answers with full citations.
The impact was immediate. Onboarding time fell from three weeks to three days, HR inquiries declined sharply, and outdated materials were automatically flagged for review.
“AI trust begins with cleaning up your internal knowledge,” Wu said. “Clarity and consistency are the foundation for more ambitious moves.”
In another implementation, Dify’s system was embedded directly into clinical workflows. A doctor could ask, for example, “What’s the blood-thinner plan for an 82-year-old patient with reduced kidney function?” The system returned a verified, patient-specific response with dosage and rationale in seconds.
Wu explained that this approach reduced verification time from ten minutes to under one, thanks to a retrieval-augmented generation (RAG) pipeline that combined vector databases with workflow orchestration tools. A RAG-based structure allows the AI to first retrieve relevant, up-to-date information from an internal database before generating its final response, improving both accuracy and contextual relevance.
The system didn’t just answer questions—it learned from them. Repeated queries refined its internal knowledge base, allowing pharmacies and departments to share custom guidelines.
“Retrieval helps individuals,” Wu added, “but systems that learn from those interactions elevate entire organizations.”
From paperwork to vigilance
A third case study involved a pharmaceutical company that processed hundreds of adverse event reports each month in multiple languages. These reports, often stored in inconsistent formats, required specialists to read and code each one manually. Missing a deadline could result in financial penalties and regulatory risks.
Dify’s solution layers data extraction, intelligent processing, and pattern detection to automate much of this work. Descriptions such as “dizziness” or “lightheadedness” were standardized into codes, and the system detected correlations across different geographies and time periods. Case completion time fell from three hours to under 45 minutes, while continuous monitoring detected safety issues weeks earlier.
“It’s the same people,” Wu noted, “but now they’re spending time on vigilance instead of repetitive form-filling.”
Wu cautioned that efficiency alone should not be the goal.
“Start where your experts spend the most time,” she advised. “Don’t start to automate everything. Keep decisions within your hands, and you get control. And don’t wait for perfection, let’s start small.”
Her message resonated with an audience grappling with how to integrate AI without losing professional control.
Dify’s journey and ambition
Dify was founded in 2023 by John Wang and Luyu Zhang, two veterans of the Chinese DevOps community and former Tencent engineers. The company’s name, derived from “Define and Modify,” reflects its mission to help users continuously improve their AI applications.
From its headquarters in Middletown, Delaware, and R&D center in Suzhou, Dify built an open-source foundation for low-code and no-code AI workflows.
Its first year was marked by strong growth. Within 12 months, Dify achieved more than 30,000 GitHub stars and 400,000 installations worldwide, becoming one of the fastest-growing open-source AI middleware platforms.
Dify’s ecosystem now integrates with major model providers, including OpenAI, Anthropic, Azure OpenAI, Baidu, and Zhipu AI. Its recent partnership with Cyberway, a Guangzhou-based technology integrator, enables enterprises to deploy private AI agents—digital co-workers for sales, IT, HR, and finance—that operate around the clock.
Europe’s opening for AI
While healthcare remains a critical proving ground, Dify’s architecture is expanding beyond it. The same RAG-based foundation that powers hospital knowledge assistants is now being applied to corporate learning, finance, and manufacturing analytics. Yet Dify’s international growth is also shaped by the broader technological rivalry between the United States and China.
As both nations compete for AI dominance, platforms like Dify navigate an intricate balance of cooperation and caution. In global markets, U.S. firms such as Google (Gemini), OpenAI (ChatGPT), and Anthropic (Claude AI) have chosen not to offer services in mainland China or Hong Kong to avoid regulatory disputes. Meanwhile, some U.S. government agencies have restricted the use of China’s DeepSeek over data security concerns.
In this environment, Europe has emerged as an attractive expansion ground for Chinese-origin AI firms. Wu said Europe’s approach to balancing privacy protection and innovation provides “a pragmatic environment for responsible AI adoption.” For Dify, the region offers opportunity and neutrality — a space where cross-border collaboration can continue despite global tensions.
Industry analysts estimate that Europe’s healthcare AI market is currently valued at 7.92 billion euros and is projected to reach 143 billion euros by 2033. Observers note that Dify’s expansion reflects a broader pattern of Chinese AI firms seeking stable growth opportunities in Europe’s regulated but open environment.