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.
雨轩 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。 Yuxuan AI helps teams adopt GLM 5.3 through API integration, agent applications, knowledge workflows and business automation built for real production use.
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
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 Yuxuan AI as a hardware or GPU cloud provider.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.YUXUAN_API_KEY,
baseURL: "https://your-yuxuan-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);
结合雨轩科技现有的商业服务、电子商务、API 集成与国际贸易背景,第一阶段建议突出这些可咨询、可交付的方向。 Based on Yuxuan Technology's services, e-commerce, API integration and trade background, these are practical offers for phase one.
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.
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.
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.
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.
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.
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.
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.
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.
连接 API、知识库、权限和业务工具链。Connect APIs, knowledge bases, permissions and workflows.
通过日志、评测和反馈不断提升稳定性。Improve reliability through logs, evals and user feedback.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
雨轩 AI 是香港雨轩科技有限公司面向大模型服务和企业智能化场景的产品化展示。公司原有业务覆盖商业服务、电子商务、API 集成、国际贸易以及货物和技术进出口。 Yuxuan AI is the model-service brand presentation of Hong Kong Yuxuan Technology Co., Limited, whose business scope covers commercial services, e-commerce, API integration, international trade and technology import/export.
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.