Comparative Analysis of HiAgent, BiSheng and Dify LLM Platforms
Grasp the latest developments in the large language model application development platform. Core content: 1. Comparison of core functions of the three major platforms: HiAgent, BiSheng and Dify 2. Multi-angle analysis of applicable groups, ease of use, scalability and security 3. Comparison of the convenience of data sources and information acquisition of each platform
Hello, everyone, this article compares three large-scale application development platforms, namely HiAgent, open source platform BiSheng, and open source project diify, and compares them from the dimensions of core functions, applicable groups, ease of use, scalability and security.
The data comes from: Volcano Engine official website: https://www.volcengine.com/, BiSheng Feishu document https://dataelem.feishu.cn/wiki/ZxW6wZyAJicX4WkG0NqcWsbynde, Dify official website: https://docs.dify.ai/, from the perspective of information acquisition sources, BiSheng Although the documents are detailed, it is difficult to directly obtain document information using Internet search engines in Feishu's closed environment, while the product information of the other two companies can be easily retrieved through search engines.
The following table summarizes the differences in the main functions of the three platforms, HiAgent, BiSheng and Dify :
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HiAgent |
HiAgent (Volcano Engine) |
BiSheng (Bi Sheng ) |
Dify (open source community) |
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Positioning/Properties |
Enterprise-level commercial platform; provided by volcano engine, closed source (supports private deployment) |
Open source enterprise-level LLM application development and platform; focuses on ToB scenarios, High open source and unlimited commercial use |
Open source LLM Application development platform; provides cloud services and community versions, and restricts modification of logos and restricts commercial use |
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Model support |
Built-in volcanic engine "Beanbao" series models (general Pro/Lite, role-playing Playing, voice synthesis, etc.), supports third-party large language model access and hybrid deployment (such as knowledge base + large language model) |
Supports one-click access or switching of mainstream open source or closed source large models; enterprise-owned models ("private models") can be used |
Supports hundreds of models, compatible with OpenAI, Anthropic |
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Application Construction |
Provides low code Visual orchestration : Business personnel build Agent or Workflow through graphical interfaces ;Built-in Prompt word template , Industry Application Template (100+ out of the box) |
Provides intuitive Workflow Workflow |
Provides graphical interface and Declarational Configuration and construction application: With an intuitive Prompt process orchestration interface and flexible workflow functions |
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Knowledge Base (RAG) |
Built-in Enterprise Knowledge Base Function: Support Advanced Retrieval Enhanced Generation (Advanced RAG) Build the enterprise knowledge brain and realize the context "memory" |
Supports document library Q&A (RAG), which can access internal structured/unstructured data in the enterprise; provides document parsing and retrieval policy configuration |
Built-in Knowledge Base Management : Visual interface, supporting TXT/PDF/HTML/ DOC Automatic cleaning, segmentation and vectorization of files; support synchronization Noto Document and web pages; docking various vector libraries such as Qdrant, Milvus |
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Tools/Plugins |
Rich Plugin Center Plugin Center : Provides 100+ enterprise business plug-ins, covering news retrieval, office tools, image recognition and other fields; supports custom plug-ins, and quickly integrates third-party APIs through parameter configuration |
Provides Function call (FunctionCalling): Internal/external systems can be called in Workflow; supports expansion capabilities (such as plug-ins) to connect to existing systems of the enterprise, batch processing of business data (batch audits, etc.) |
Built-in Tool call Framework: Supports standard OpenAI Plugins, and directly imports OpenAPI document generation tools; plug-ins are ecologically active, and can develop custom plug-in extension functions |
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Multimodal support |
Supports multimodal AI capabilities: text dialogue is the main focus, and combines models such as image generation, speech synthesis/recognition (such as role-playing model, literary graphics model, sound reproduction model, etc.); adapts to rich scenes |
Mainly on text applications (dialogue, analysis, generation); the functions such as image and voice can be realized through tool expansion (no official multimodal model yet) |
Supports multimodal output : The latest version supports the output of rich media content such as pictures; external AI services such as image generation can be called through plug-ins |
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Team collaboration |
For enterprise multi-users: support workspace, multi-role authority management, meet enterprise collaborative development and management needs (such as multi-person management of applications and knowledge bases) |
Enterprise users can use it together; planning to provide operational auditing, permission management and other enterprise management functions |
Multi-user workspace Support: Collaborative development and operation of team members; provide access control and role management |
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Deployment method |
Supports public cloud hosting, hybrid cloud deployment and on-premises deployment, and provides Full life cycle management The tool chain ensures online operation |
Open source code can be deployed privately; supports docking with enterprise intranet environments and local model deployment, making it convenient for running within the firewall |
Provides cloud services (Dify Cloud) and open source community version; local deployment supports Docker containers or Helm one-click deployment |
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Monitoring and Evaluation |
Built-in Agent DevOps |
Provides logging and auditing mechanisms; the statistical panel in the planning includes multiple dimensions such as call times, token usage, feedback rate, etc., to assist in evaluating application effects |
Provides basic Log Record and user reverse collection, support dialogue result annotation optimization ;Developers can obtain indicators through the API and connect Dify to their own monitoring system |
The typical large-model application development process includes model access, data configuration, application construction, test iteration to deployment monitoring and other stages.
First select or connect to the appropriate large language model, then upload or connect to the internal knowledge documents of the enterprise to build a knowledge base, then arrange the dialogue logic (or Workflow process) through the visual interface and set the prompt words, then repeatedly test and adjust, and finally deploy the online internal use and continuously monitor the effect.
HiAgent provides Agent DevOps full process management, and the effect evaluation and tuning from development to online are supported by the platform;
BiSheng emphasizes that Human in the Loop is supported in Workflow, which can manually intervene in the optimization results in the process;
Dify helps developers improve prompts and model effects through log and feedback mechanisms.
Scenario 1: Intelligent dialogue assistant (customer service/assistant class)
The dialogue robot built using the internal knowledge base of the enterprise can answer product questions and answers, policy interpretation, internal knowledge inquiries, etc. In this scenario, the large language model extracts answers from the database through retrieval enhancement (RAG) and generates replies, improving the efficiency of employees or customers in obtaining information. You can also combine Tool call Query the database or call the business system processing process during the conversation to improve the functionality of the conversation robot.
Scene 2: Long report generation (content creation class). For common fixed template reports (such as industry analysis reports, financial statements, etc.), the large-model platform can disassemble complex tasks into multiple subtasks, which are completed one by one by the workflow engine, and then fill in the results into the predefined template to generate a long-term report. In this process, multiple AI capabilities (large models, small models, rule engines, etc.) need to be combined, and key parts are allowed to be reviewed manually.
BiSheng provides Multi-segment process orchestration Multi-segment process orchestration and manual feedback mechanism, supporting report sub-section generation and verification;
HiAgent provides a rich industry template to enable report generation to start with a "one-click" ;
Dify The platform can integrate table generation, chart drawing and other tools through its plug-in mechanism to enrich the report content.
Other common scenarios include: Content audit and compliance (batch contract audit, content compliance inspection, etc.), Knowledge Management (document summary archive, intelligent search), Code Assistant (Code generation and tuning), Business Process Assistant Business Process Assistant (such as intelligent work order system), etc.
The application focus of different platforms in these scenarios is slightly different:
For example, HiAgent has a large number of ready-made templates and plug-ins for vertical industries, which can quickly build applications such as "smart customer service" and "marketing assistant";
BiSheng emphasizes Workflow Meets customized complex processes, such as human resources Q&A involving multiple rounds of interaction, recruitment of interview assistants, etc.;
Dify is known for its general capabilities, and developers can realize various innovation scenarios through its modular component splicing.
Function, applicable group, ease of use, scalability, security Five dimensions, in-depth comparison and analysis of the three platforms:
Function perfection
HiAgent: The most comprehensive functions are integrated, integrating the full set of functions required by enterprises such as model access, knowledge base, workflow, plug-ins, monitoring and evaluation. Its outstanding advantage lies in the official provision of a large number of pre-set resources (industry plug-ins and application templates) and The DevOps support for the entire process helps enterprises quickly implement production-level AI applications.
BiSheng: The core functions focus on Enterprise Application Development , it has functions such as dialogue/RAG, Workflow orchestration, and multi-agent collaboration to meet the needs of complex scenarios. Compared with HiAgent, BiSheng's characteristics are More flexible process control (such as manual intervention, circular nodes), but it is currently slightly insufficient in peripheral functions such as visual monitoring panels (some operational statistics and security audit functions are still under development).
Dify: The function covers a wide and continuously expands, providing modules such as model management, prompt word arrangement, knowledge base, plug-ins, and workflow. Dify has LLMOps features , such as log annotation, version management, etc., and its functional completeness is quite mature. The advantages are Model neutral and Modular Designed to support a variety of models and infrastructures. However, compared with HiAgent, Dify lacks official industry templates, but has also accumulated some application examples based on the community.
Easy to use
HiAgent: Emphasize Emphasize Low code and intuitiveness . Provides a graphical interface and a guided process, and business personnel can build a simple application in 5 minutes. Its "ranking" user guidance strategy classifies learning paths, gradually providing corresponding functions from beginners to experts, reducing the difficulty of first use. In addition, a large number of built-in examples and Best Practices Best Practices Have a good idea to help users avoid common pitfalls. Overall, HiAgent polishes the enterprise user experience very well. Fast to get started And The interface is friendly .
BiSheng: Focus on Professional and concise . BiSheng's Workflow interface design pursues "intuitive and capable". For technicians who are familiar with AI applications, it is faster to get started and the key functions are clear at a glance. But compared with HiAgent, it has a slightly higher threshold for business personnel and requires a certain amount of AI and programming background knowledge (the official assumes that the readers are industry insiders). However, because of its active community, documentation and discussions can help beginners get a step-by-step grasp. If the company has the support of a technical team, BiSheng's user experience will be smooth.
Dify: Dify: emphasize Simplicity and development efficiency . Provides a unified browser-based console, creating applications, configuring prompt words, and knowledge base are all completed in the visual interface. At the same time, it supports advanced configuration through YAML, etc. (for skilled developers). Its design is as much as possible Reduce duplicate work , such as directly supporting common data source access, built-in test debug panel, etc. This makes Dify simple enough for beginners and has room for operation for experienced players.
Scalability
HiAgent: Excellent expansion capability, providing Plugin Center Sustainable expansion features. The official has pre-built a large number of industry plug-ins, and enterprises can also develop custom plug-ins (through OpenAPI configuration, etc.) to expand the "hands and feet" of the agent. In addition, HiAgent supports connecting to internal enterprise systems (such as CRM, ERP), and through its SDK and API, Agent can be embedded into existing business processes. With the enrichment of byte-based ecosystems (such as the Volcano Ark large language model platform), HiAgent can also seamlessly utilize other AI services, making it an evolutionary AI middle platform Evolutionary AI middle platform .
BiSheng: As an open source project, scalability As an open source project, scalability As an open source project, scalability . Developers can directly modify or develop source code twice to add new functions. In addition, BiSheng's architecture design encourages insertion of custom modules, such as Workflow nodes that can call external services and batch process new types of data, etc. The community has also contributed a lot of plug-ins and integration functions. BiSheng supports access to various mainstream models and replacement of components such as vector libraries, databases, etc., so it is also flexible in adapting to different technical stacks. For the need Highly customized 's enterprise solution, BiSheng provides a solid foundation.
Dify: Modularity and plug-in is famous. Its plug-in mechanism supports access to third-party tool (such as AI models, storage, services, etc.). At the same time, Dify itself adopts a microservice architecture. Each module (model management, data management, application, etc.) is relatively independent and can be replaced or expanded horizontally. Dify official continuously launches new versions to enhance architectural flexibility (such as introducing "hive architecture" to improve module decoupling and scalability) and enrich the plug-in ecosystem. For developers, it is easy to develop new plug-ins for Dify or integrate their own systems. In terms of scaling capabilities, Dify is excellent in open source solutions, and can expand with the growth of enterprise demand.
Security
HiAgent: Safety is one of its biggest selling points. Support Local deployment , enterprises can deploy the platform on the intranet to ensure that data is not leaked. At the same time, it has a complete Data protection mechanism, such as the built-in DLP (data leak prevention) policy, to protect sensitive information HiAgent covers the security guarantees for the entire life cycle of the intelligent application, including content compliance audit, transmission encryption, and compliance with enterprise security compliance requirements (such as compliance guarantees). For high security-sensitive industries such as finance and government, HiAgent provides Stronger security guarantees .
BiSheng: Because it is open source and privately deployable, data security can be controlled by the enterprise. Private data does not come from its own domain. The BiSheng team is also very concerned about enterprise-level security needs and has planned functions such as audit logs and permission control. In terms of content security, bad output can be filtered in combination with the company's own review rules or model docking. BiSheng is currently committed to achieving safety standards such as Equity-safety Equity-safety Equity-safety. Although its security functions as an open source project need to be configured and improved by itself, it has high transparency. Enterprises can audit source code to ensure no backdoors, and can reinforce the deployment environment by itself, with strong security control.
Dify: Dify open source version also allows Self-hosted , enterprises can deploy it within the firewall to ensure that data does not flow to the external network. The Dify team also provides basic security functions such as Access control , API key management and other basic security functions. In addition, since it is open source, security auditing and trust are relatively guaranteed. It should be noted that if you use Dify's cloud services, the data may be stored on a third-party cloud and you need to refer to its privacy policy.
Overall, Dify provides security Basic Guarantee, and gives users sufficient control through open source and containerization, suitable for scenarios where security requirements are moderate and protection can be strengthened through deployment architectures.
Applicable groups
HiAgent: Oriented Large enterprises and institutions . The original intention of the design is to enable Business department personnel to be able to use it, so it is friendly to non-technical backgrounds and meets the needs of enterprise IT docking. It is suitable for large and medium-sized enterprises that have serious production needs and want manufacturers to provide support and industry solutions.
BiSheng: Aimed at Enterprise technical team Enterprise technical team and AI solution providers. Because it is open source and tends toward To B scenarios, it is suitable for teams with certain R&D capabilities and is developed by technical personnel in scenarios that require highly customized scenarios. There are also many scientific research or innovation teams Scientific research or innovation teams Use BiSheng to experiment with complex Agent application ideas, and the open source version restrictions are loose, so you can modify the logo and use it unlimitedly for commercial use.
Dify: First started, with a wide range of applications, from Empty developers, start-up teams, and corporate R&D Everyone can be used. Dify has cloud services for non-technical users to quickly get started, and also has open source versions for developers to deeply customize. However, open source restrictions are strictly restricted and commercial use is not allowed after modifying the logo.
In summary, HiAgent, BiSheng and Dify has its own characteristics:
HiAgent Owned The most complete one-stop function and enterprise-level support are suitable for large enterprises to quickly build multiple AI applications and strictly control security. If companies focus on official service support, need to enrich industry templates and high security, then HiAgent is a robust choice. Classic Scenario: The application of large-scale models that require high safety and compliance in the financial and government-enterprise fields is implemented; it is hoped that low code allows business departments to directly participate in the construction, such as customer service robots, marketing content generation, etc., with ready-made templates and consulting services.
BiSheng As As Open source, autonomous and controllable 's platform is very suitable for enterprises and development teams that require deep customization. It has unique advantages in the AI of complex business processes (Workflow is flexible and powerful), suitable for technical teams to explore innovative solutions or create exclusive AI applications for vertical industries. If an enterprise has R&D capabilities, pursues independent and controllable solutions and optimizes for domestic business scenarios (Chinese, etc.), BiSheng is worth considering. Typical scenarios: In enterprises with special processes such as manufacturing and energy, internal AI teams will use BiSheng to develop such as intelligent quality inspection assistants, expert knowledge Q&A systems, etc.
Dify Easy to use and versatility It is good at using individual developers, small and medium-sized teams, and even innovation departments within large factories that want to quickly try large language model applications. It is open source free, has an active community, and its functions are being iterated rapidly. Dify is suitable for the construction of product prototypes and general scenarios (such as product documentation Q&A, code assistant), and is also suitable for integration into existing systems as an underlying platform. Typical scenarios: entrepreneurial teams use Dify to create SaaS AI applications (such as intelligent writing assistant); corporate IT departments use Dify to build internal knowledge base Q&A or automatic report generation tools to verify value in the short term.
Suggestions: When selecting, first evaluate the technical strength and safety compliance requirements of your own team. If required Independent controllable + customization , BiSheng is the first choice; if required Maturity and robustness + comprehensive support , HiAgent is more suitable; if you pursue Quick landing + flexible expansion , Dify will provide a good balance. You can also use it in combination with scenarios It can also be used in combination with scenarios : For example, enterprise core data is deployed in the intranet using HiAgent/BiSheng, and peripheral innovation projects are tested with Dify. In short, each of the three has its own strengths. When choosing, it should be based on the enterprise scale, budget, safety requirements and specific application scenario needs and adopt the best.
