01
长上下文知识处理Long-context knowledge work
适合合同、手册、客服记录、代码仓库等大体量资料的问答、摘要、对比和审阅。Question answering, summaries, comparisons and review over manuals, contracts, tickets and codebases.
GLM 5.3 企业级模型服务GLM 5.3 Enterprise Model Service
以 GLM 5.3Build enterprise AI 构建企业智能应用 with GLM 5.3
Qing AI 面向企业团队提供 GLM 5.3 API 接入、Agent 应用、知识库问答与业务自动化方案，让大模型从演示走向真实生产流程。 Qing AI helps teams adopt GLM 5.3 through API integration, agent applications, knowledge workflows and business automation built for real production use.
glm-5.3 / reasoning=max
Prompt
task: 分析企业知识库并生成自动化流程Analyze enterprise knowledge base and create an automation flow context: 1M tokens tools: search, crm, docs output: json + executive brief
Streaming response
verified route: api / knowledge / agent
latency class: production workflow
Model Capabilities
把 GLM 5.3 的推理能力接入你的业务系统。Bring GLM 5.3 reasoning into your business systems.
第一阶段聚焦“可展示、可咨询、可落地”：用清晰的能力模块告诉客户我们能提供什么，而不是销售硬件资源或云主机。 The first phase focuses on a clear, consultative product site: showing what we deliver without positioning Qing AI as a hardware or GPU cloud provider.
02
Agent 与自动化流程Agents and automation
将模型连接 CRM、订单、文档与内部系统，形成可追踪的多步骤业务流程。Connect the model with CRM, orders, documents and internal systems for traceable multi-step workflows.
03
代码与工程助手Engineering assistant
面向复杂代码理解、重构建议、测试生成、技术文档和研发流程辅助。Support code understanding, refactoring, tests, technical docs and engineering workflow assistance.
04
结构化输出与系统集成Structured output and integration
让模型输出 JSON、表格、报告和 API 参数，方便接入企业现有软件。Produce JSON, tables, reports and API parameters that integrate cleanly with business software.
Why GLM 5.3
旗舰模型能力，适合从原型走向生产。Flagship model capability for moving from prototype to production.
基于 Z.AI 官方资料，GLM 5.3 支持 1M 上下文、128K 最大输出、持续 reasoning，并面向复杂软件工程与 Agent 任务优化。页面内容保留“资料来源”入口，方便客户核验。 According to Z.AI documentation, GLM 5.3 supports a 1M context window, 128K max output, always-on reasoning and optimization for complex software engineering and agent tasks.
1M上下文窗口context window
128K最大输出max output
Low / High / Max推理强度档位reasoning effort levels
OpenAI-styleAPI 调用体验API developer experience
A
接入咨询Integration advisory
评估业务场景、数据边界、调用链路和成本结构。Assess use cases, data boundaries, call routes and cost structure.
B
模型应用设计Model application design
设计 Prompt、工具调用、知识库索引和交互界面。Design prompts, tool calls, knowledge indexes and user flows.
C
API 与系统集成API and system integration
对接网站、客服、订单、CRM、文档和内部管理系统。Integrate websites, support, order systems, CRM, documents and internal tools.
D
上线与优化Launch and optimization
监控质量、稳定性、响应速度和 token 成本，持续迭代。Monitor quality, reliability, response speed and token cost, then iterate.
Developer Experience
面向开发者，接入方式保持简单。Built for developers, simple to connect.
页面演示保留 OpenAI 兼容风格的调用方式，便于技术负责人快速理解迁移成本。正式上线前，可根据你的实际代理服务地址替换 Endpoint。 The demo keeps an OpenAI-compatible style so technical buyers can understand migration effort. The endpoint can be replaced by your actual service route before launch.
api-example.js
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.QING_AI_API_KEY,
baseURL: "https://your-qing-ai-gateway.com/v1"
});
const response = await client.chat.completions.create({
model: "glm-5.3",
messages: [
{
role: "system",
content: "You are an enterprise workflow agent."
},
{
role: "user",
content: "Analyze our support tickets and propose automations."
}
],
reasoning_effort: "max"
});
console.log(response.choices[0].message.content);
deployment-consoleLIVE PREVIEW
$ qing-ai deploy workflow-support-agent
✓ glm-5.3 route configured
✓ knowledge index connected
✓ tool permissions scoped
→ waiting for first enterprise request...
Enterprise Solutions
先做能成交的场景，而不是堆技术名词。Lead with business scenarios, not a pile of buzzwords.
结合青如轩科技服务在信息技术咨询、系统集成、物联网技术服务、运行维护与技术推广方面的业务基础，第一阶段建议突出这些可咨询、可交付的方向。 Based on Qingruxuan Technology Service's IT consulting, systems integration, IoT technology, operations maintenance and technology promotion background, these are practical offers for phase one.
跨境电商智能运营Cross-border commerce intelligence
商品资料生成、客服问答、订单异常分析、邮件回复和多语言内容本地化。Product content, support answers, order issue analysis, email replies and multilingual localization.
企业知识库问答Enterprise knowledge Q&A
把制度、合同、产品文档和历史记录变成可检索、可追溯、可引用的智能助手。Turn policies, contracts, product docs and history into searchable, traceable assistants.
业务流程 AgentBusiness workflow agents
让模型读取上下文、调用工具、生成结果，并将关键节点交给人工确认。Let the model read context, call tools, create outputs and route key steps to humans.
客服与销售助手Support and sales copilot
自动整理客户问题、生成回复建议、沉淀 FAQ，并辅助销售跟进。Summarize questions, draft replies, build FAQs and support sales follow-up.
数据分析与报告Data analysis and reporting
将表格、订单、运营数据转成管理层可读的结论、风险和行动清单。Turn spreadsheets, orders and operations data into executive insights and action lists.
研发提效工具Developer productivity tools
辅助代码审阅、测试编写、文档维护、需求拆解和系统集成脚本生成。Assist code review, tests, docs, requirement breakdowns and integration scripts.
01
场景诊断Discover
梳理业务目标、数据来源、使用人群和合规边界。Map goals, data sources, users and compliance boundaries.
02
原型验证Prototype
用真实样本验证效果、成本、延迟和交互体验。Validate quality, cost, latency and UX with real examples.
03
系统接入Integrate
连接 API、知识库、权限和业务工具链。Connect APIs, knowledge bases, permissions and workflows.
04
持续优化Optimize
通过日志、评测和反馈不断提升稳定性。Improve reliability through logs, evals and user feedback.
Pilot Packages
把咨询变成可交付的试点方案。Turn consultation into deliverable pilot packages.
第三阶段补强转化路径：客户不需要立刻购买服务，但能清楚知道第一次沟通后会得到什么。 Phase three clarifies the conversion path: visitors do not need to buy immediately, but they can see what the first engagement delivers.
01 / Assessment
场景评估包Scenario Assessment
适合还不确定从哪里开始的团队，用一次轻量诊断找出最值得试点的 GLM 5.3 场景。For teams still choosing a starting point, this lightweight assessment identifies the best GLM 5.3 pilot workflow.
- 业务场景梳理Workflow discovery
- 数据与权限边界Data and permission boundary
- 试点优先级建议Pilot priority recommendation
输出：评估备忘录Output: assessment memo
02 / Prototype
原型验证包Prototype Pilot
适合已经有明确场景的团队，用真实样本验证 Prompt、知识库、Agent 流程和成本。For teams with a clear workflow, this validates prompts, knowledge context, agent steps and cost using real samples.
- Prompt 与输出格式设计Prompt and output design
- 样本数据验证Sample-data validation
- 成本与延迟估算Cost and latency estimate
推荐第一步Recommended first step
03 / Integration
系统接入包Integration Package
适合准备进入生产流程的团队，把模型网关、日志、权限、知识库和业务系统连起来。For teams ready for production workflows, this connects gateway, logs, permissions, knowledge base and business systems.
- API 网关接入建议API gateway guidance
- 工具调用与人工确认Tool calls and human approval
- 上线监控清单Launch monitoring checklist
输出：接入方案Output: integration plan
Case Blueprints
用案例蓝图说明它怎么落地。Show how it lands through case blueprints.
这些是可用于首次咨询的标准蓝图，后续可以替换成真实客户案例。 These blueprints are suitable for first consultations and can later be replaced with real customer stories.
Commerce01
跨境客服回复建议Cross-border support reply drafts
读取订单状态、产品说明和售后政策，生成多语言回复草稿，并把退款、争议等高风险场景交给人工确认。Read order status, product docs and support policies to draft multilingual replies while routing refund and dispute cases to humans.
目标：缩短单个工单处理时间Goal: reduce handling time per ticket
Knowledge02
企业制度知识库Internal policy knowledge base
将制度、合同模板和产品文档整理成可问答的知识库，回答时显示依据、不确定点和建议下一步。Turn policies, contract templates and product docs into a Q&A knowledge base with evidence, uncertainty and recommended next steps.
目标：降低内部重复咨询Goal: reduce repeated internal questions
Agent03
订单异常 AgentOrder exception agent
识别缺货、延迟、地址错误等异常，自动生成摘要、处理建议和客户沟通草稿。Identify stockouts, delays and address issues, then generate summaries, handling suggestions and customer-message drafts.
目标：让异常处理标准化Goal: standardize exception handling
Governance
上线前先把边界讲清楚。Define boundaries before production.
企业客户关心的不只是模型能力，还包括数据、权限、日志、人工确认和成本可控。 Enterprise buyers care about model capability, but also data, permissions, logs, human approval and cost control.
D
数据边界Data Boundary
明确哪些数据可进入模型，哪些需要脱敏、截断或禁止传输。Define what can enter the model, what needs redaction and what must never be transmitted.
P
权限分级Permission Levels
将动作分为只读、草稿、需确认执行，降低 Agent 误操作风险。Classify actions into read-only, draft and approval-required execution to reduce agent risk.
L
日志与评测Logs and Evals
记录调用、场景、token、延迟、错误和人工反馈，持续优化质量。Record calls, scenarios, tokens, latency, errors and human feedback to improve quality.
FAQ
客户最常问的几个问题。Questions buyers usually ask first.
这部分用于减少首次沟通成本，也让页面更适合搜索引擎理解。 This section reduces first-call friction and helps search engines understand the page.
你们卖硬件或 GPU 云吗？Do you sell hardware or GPU cloud?
不作为主要业务。本站聚焦 GLM 5.3 模型服务、API 接入、Agent 应用和企业智能化试点。No, not as the primary offer. This site focuses on GLM 5.3 model services, API integration, agent applications and enterprise AI pilots.
是否需要客户已有技术团队？Does the client need an internal tech team?
不一定。若已有技术团队，我们可以提供接入方案和原型验证；若没有技术团队，也可以从轻量试点和流程设计开始。Not necessarily. With an internal team, we can support integration planning and prototyping; without one, we can start from a lightweight pilot and workflow design.
试点通常从什么开始？What is the usual first pilot?
建议从高频、低风险、有样本数据的场景开始，例如客服回复建议、知识库问答、商品资料生成或订单异常摘要。Start with a frequent, low-risk workflow with sample data, such as support reply drafts, knowledge Q&A, product content generation or order exception summaries.
能否直接进入生产系统？Can it go directly into production systems?
建议先经过原型验证。进入生产前需要明确权限、日志、人工确认、成本监控和失败兜底机制。We recommend prototyping first. Production requires permissions, logs, human approval, cost monitoring and fallback mechanisms.
Resources
用内容建立专业信任。Build authority with a focused resource hub.
第一阶段先放可点击筛选的资源卡片，后续可以扩展成真正的文章详情页、白皮书和案例库。 Phase one ships filterable resource cards, ready to expand into essays, whitepapers and case studies.
GLM 5.3API
GLM 5.3 企业接入指南GLM 5.3 enterprise integration guide
从 API Key、Endpoint、模型参数到错误处理，梳理上线前需要准备的工程清单。A launch checklist covering API keys, endpoints, model parameters and error handling.
AGENTBUSINESS
业务 Agent 如何接入现有系统How business agents connect to existing systems
用权限、工具调用和人工确认机制，让智能体安全处理多步骤任务。Use permissions, tool calls and human checkpoints for safer multi-step execution.
BUSINESSCOST
企业大模型项目的成本结构Cost structure of enterprise LLM projects
拆解 token 成本、集成成本、数据治理和持续优化投入。Break down token usage, integration, data governance and ongoing optimization costs.
GLM 5.3AGENT
长上下文如何改变知识库体验How long context changes knowledge workflows
从碎片检索到整批文档理解，长上下文能减少切片丢失和跨文档遗漏。Move from fragmented retrieval to broader document understanding with fewer context gaps.
APICOST
Prompt、缓存与路由优化Prompt, cache and routing optimization
通过模板、缓存、分层模型和评测，让模型服务更稳定、更可控。Use templates, caching, model routing and evals for more reliable model services.
BUSINESSAPI
跨境电商 AI 应用清单AI use cases for cross-border commerce
商品、客服、订单、营销、邮件与多语言运营的模型应用方向。Model applications across product data, support, orders, marketing, email and localization.
Company
武汉青如轩科技服务有限公司Wuhan Qingruxuan Technology Service Co., Ltd.
武汉青如轩科技服务有限公司专注于人工智能大模型服务及企业智能化应用。公司部署高性能 NVIDIA B300 GPU 服务器集群，提供 GLM 5.3 等大模型的 API/Token 服务，并面向企业及机构提供大模型部署、模型推理、接口接入及相关技术服务。同时，公司业务涵盖信息技术咨询、系统集成、物联网技术服务、运行维护与技术推广等方向。 Wuhan Qingruxuan Technology Service Co., Ltd. focuses on AI large-model services and enterprise intelligent applications. The company deploys high-performance NVIDIA B300 GPU server clusters, provides API/Token services for large models such as GLM 5.3, and offers large-model deployment, model inference, API integration and related technical services for enterprises and institutions. Its business also covers IT consulting, systems integration, IoT technology services, operations maintenance and technology promotion.
公司地址Company Address
武汉市江岸区越秀星汇君泊第S3幢办公区B单元21层21/F, Office Area Unit B, Building S3, Yuexiu Xinghui Junbo, Jiang'an District, Wuhan
联系方式Contact
朱先生 15971457163Mr. Zhu 15971457163
Contact
让 GLM 5.3 进入你的业务现场。Bring GLM 5.3 into your real workflow.
填写一个小场景，我们会把你的需求整理成邮件草稿，方便直接发起咨询。Describe one workflow and we will turn it into an email draft for a first consultation.