[Rebroadcast] Webinar on How to Start Utilizing Dify with a Field-Led Approach for Large Enterprises
Majisemi Inc. will rebroadcast a webinar explaining how large enterprises can utilize Dify with a field-led approach.
📋 Article Processing Timeline
- 📰 Published: March 30, 2026 at 18:00
- 🔍 Collected: March 30, 2026 at 22:56 (4h 56m after Published)
- 🤖 AI Analyzed: April 16, 2026 at 10:07 (395h 11m after Collected)

■ Dify: The New Standard for Business AI Automation, Enabling AI Workflows with Low-Code
As the business utilization of generative AI progresses, there is a growing need to design and verify AI applications and AI workflows that reflect the on-site operational content and decision-making processes with our own hands. Dify is gaining attention as a platform that allows for the construction of AI applications while assembling workflows with low-code, and its characteristic is that it makes it easy to consider AI utilization tailored to business operations without specialized development skills. Starting with simple workflow creation allows for verification led by business departments and trials of small use cases.
■ The Wall to Production Operation - How to Master It with a Field-Led Approach?
There are many cases where efforts remain in trial and error due to a lack of concrete vision, such as "unable to master AI and not reaching production operation" or "uncertain about which tasks should be delegated to AI and in what kind of workflow." Especially when looking towards production operation, numerous challenges arise, including license selection, enterprise features, and security requirements.
■ Organizing Licenses and Introducing Use Cases to Consider with Dify
This seminar will organize and clearly explain the points that must be considered when looking towards Dify's production operation, such as licensing concepts, enterprise features, and security requirements for organizational use. It will also introduce the "Third AI Dify Construction Support Solution," which provides consistent support from license selection to building a highly secure usage environment on Azure, and to adoption and ongoing utilization after implementation.
Leveraging the customer success know-how cultivated through introducing generative AI to over 130 companies, JTP will provide support for continuous AI utilization beyond mere verification. Focusing on information useful for actual implementation considerations, the seminar will also introduce use cases for AI applications and workflows that can be built with Dify. Through simple workflow creation demos, participants will gain a concrete image of how to achieve production utilization led by the field.
*JTP is an official service partner of LangGenius, the provider of "Dify".
■ Organizer/Co-organizer
JTP Corporation
■ Cooperation
Open Source Software Utilization Research Institute Inc.
Majisemi Inc.
Dify is a platform that allows users to build AI applications and workflows using low-code, enabling the automation of business processes without requiring specialized development skills. This webinar is specifically targeted at large enterprises looking to implement and utilize AI solutions like Dify in their operations. The webinar addresses challenges such as difficulty in mastering AI for production use, uncertainty about which tasks to automate, and the complexities of license selection, enterprise features, and security requirements for organizational use. It is a solution offered by JTP that provides comprehensive support for Dify implementation, from license selection and building a secure Azure environment to ongoing utilization and adoption. JTP has experience in implementing generative AI for over 130 companies and leverages this customer success know-how to support continuous AI utilization.
Majisemi will continue to hold webinars that are "useful for participants."
Past seminar public materials and other ongoing seminars can be found at
FAQ
What is Dify?
Who is this webinar for?
What challenges does the webinar address regarding AI adoption?
What is the 'Third AI Dify Construction Support Solution'?
What is JTP's experience in AI implementation?