However, implementing AI in real-world operations is not without challenges. Organizations often face:
- The difficulty of designing effective prompts
- Deciding which large language model (LLM) to use and understanding the differences between them
- Development costs associated with integrating AI into existing systems
These technical hurdles can slow down AI adoption and prevent companies from fully realizing its potential.
One solution gaining attention is Dify. Developed and operated by LangGenius, Inc. in the United States, Dify is an open-source platform for building AI applications. Its user-friendly design makes it accessible not only to engineers but also to business professionals, allowing teams to create functional AI applications in a short period of time. This ease of use has earned Dify strong support from companies across various industries.
What is Dify?
Dify is an open platform designed to streamline the development of applications leveraging generative AI. It features an intuitive no-code/low-code interface, supporting everything from designing AI applications to deployment and operation in a single workflow.
Key Features of Dify
- Intuitive Workflow Design
- Even users without programming knowledge can quickly prototype AI applications.
- Flexible Use of Multiple LLMs
- Supports OpenAI, Anthropic, Azure OpenAI, Amazon Bedrock, and more, allowing projects to select the most suitable model for their needs.
- Versatile Deployment Options
- Applications can be published as web apps, integrated into Teams chatbots, or exposed via APIs for integration with existing systems.
- Deployment Formats
- Available as an open-source version for local installation and a cloud version for easy online access (paid).
Use case of Dify
Among Dify’s use cases, RAG (Retrieval-Augmented Generation) stands out.
Unlike traditional Internet search or standard Generative AI, it generates answers based on unique data such as internal company documents.
As a result, employees can quickly access accurate information in a natural conversational format, without having to consult complex manuals or company regulations.
RAG can be built using the following simple implementation steps.
- Sign in to Dify
- Register knowledge ( company documents)
- Set the model provider (LLM API)
- Create a work-flow
- Publish
IDE provides comprehensive support for the development and operation of Generative AI using Dify, as well as assistance with specific technical challenges, including optimal prompt design, selecting and implementing LLMs, and integrating Generative AI with existing systems.
For clients who prefer to develop AI in-house rather than outsourcing, we also offer solutions such as AI implementation training and hands-on workshops.
AI Seminar & Training | ID Europe B.V.
If you have any questions about this article or are interested in the solutions mentioned above, please contact us via the link below.
Contact | ID Europe B.V. (idnet.co.jp)