分析拆解Decompose
把"X 产品支持哪些接口、用了什么芯片、有没有兼容问题"这种复合问题拆成可查询的子问题,分别走不同检索路径。
Compound questions like "what interfaces does product X support, which chip, and any compat issues" get decomposed into atomic sub-queries, each routed to the right retrieval path.
WeChaser 不做又一个聊天框。我们做企业 AI 生态的中间件——飞书 AI、钉钉 AI、ChatGPT、Claude 这些工具接上 WeChaser 后,瞬间拿到你企业的真实数据、工艺、客户档案、邮件历史。回答带引用,行动有边界,模型跑在你自己的 GPU 上。 WeChaser is not another chatbot. We are the middleware for enterprise AI — Lark AI, DingTalk AI, ChatGPT, Claude all become instantly aware of your company's drawings, SOPs, customer records, and email history. Answers are cited. Actions stay inside permission. Models run on your own GPUs.
市面上最缺的不是又一个 AI 应用,而是"让 AI 真正懂这家企业"的那一层中间件。
ChatGPT、Claude、飞书 AI、钉钉 AI——它们是天才大脑,但对你的车间一无所知。我们做的事很专一:把企业的真实知识沉淀下来,做成所有 AI 工具都能调用的知识中枢。
不和 ChatGPT 抢用户。不卖花哨 UI。不做生成。只供原料——但原料工业级溯源,零幻觉。
The thing the market is missing isn't another AI app. It's the middleware layer that makes AI actually know this company.
ChatGPT, Claude, Lark AI, DingTalk AI — brilliant brains that know nothing about your shop floor. We do one specific thing: turn your real enterprise knowledge into a hub every AI tool can call.
We don't compete with ChatGPT. We don't sell flashy UI. We don't generate. We supply raw material — industrial-grade, fully cited, zero hallucination.
企业 AI 中间件。把图纸、工艺、SOP、客户档案、邮件历史汇成一个有引用、可追溯的知识中枢。其他 AI 工具(飞书 AI / 钉钉 AI / Claude)通过 MCP / CLI / REST 调用——回答带溯源链接,文件原件留本地。 Enterprise AI middleware. Drawings, SOPs, customer records, email — converged into a citation-backed knowledge hub. Other AI tools (Lark AI / DingTalk AI / Claude) call us via MCP / CLI / REST. Answers are sourced. File originals stay local.
用 AI 复刻麦肯锡级方法论给中小企业。陪跑顾问,交付业务流程梳理 + AI 转型路线图。
McKinsey-grade methodology, AI-leveraged, for mid-market. Hands-on advisory: workflow audit + AI transformation roadmap.
了解Learn →把知识中枢直接接到员工每天用的协作工具,不要求换工具。原生 Bot SDK + Hermes Gateway。
Plug the knowledge hub directly into the tools people already use — no migration. Native Bot SDK + Hermes Gateway.
查看See →AI 协助把 PDF / Word / 扫描件 / Excel / PPT 整理成标准格式 + 内容纠错 + 入库。
AI-assisted: PDFs, Word, scans, Excel, PPT — converted to clean structured format with content QA, ready to ingest.
了解Learn →把"X 产品支持哪些接口、用了什么芯片、有没有兼容问题"这种复合问题拆成可查询的子问题,分别走不同检索路径。
Compound questions like "what interfaces does product X support, which chip, and any compat issues" get decomposed into atomic sub-queries, each routed to the right retrieval path.
在向量库 + 知识图谱 + 全文索引三路混合检索 + RRF 融合 + MMR 多样性 + BGE Reranker 精排。不是关键词搜索,是工业级语义检索。
Hybrid retrieval across vector store + knowledge graph + full-text index + RRF fusion + MMR diversity + BGE Reranker. Not keyword search — industrial semantic recall.
检索片段去重、矛盾标识、置信度打分,组装成结构化原料给调用方。每条原料都有溯源链接,工业级 grounded RAG,零容忍幻觉。
Deduplication, conflict flagging, confidence scoring — assembled into structured material for the calling agent. Every fact carries a citation. Industrial-grade grounded RAG, zero-tolerance for hallucination.
23 年经验工艺师即将离开。半年的对话采集 + 历史方案归档,他的判断逻辑沉淀进 AI。年轻工程师在飞书提问,能拿到他口吻的回答,附引用。
A process engineer with 23 years of pattern-matching is leaving. Six months of recorded conversations + archived decisions distilled into the model. Junior engineers ask in his voice — every answer cited.
RFQ 落到销售飞书。AI 副驾即时拉历史相似订单 + 产能现状 + 原材料行情,给出可承诺的价格区间和交期。
An RFQ lands. The copilot pulls past orders, current capacity, raw-material indices, proposes a defensible price band with lead time.
员工只问"换型号要不要清线"。AI 给出该型号具体清线步骤 + 上次违规事故时间线,每条都点回原始 SOP 段落。
The actual question: "do we flush the line for this changeover?" The copilot returns exact procedure for this part number + last incident timeline, citing SOP paragraphs by section.
客户在某封邮件里提过一个变更要求,今天没人记得在哪。AI 跨邮箱、跨人员检索,3 秒钟把上下文还原,附原邮件链接。
A customer mentioned a change request in some email weeks ago. The copilot searches across mailboxes and people, restoring the thread with original-message links in seconds.
上门盘点知识资产。识别 3 条最高价值的业务流程,给出可行性评估表。
On-site audit of knowledge assets. We identify the top 3 highest-leverage workflows and produce a feasibility checklist.
数据管道 + 权限映射 + 模型选型。只接必要源,不大而全。
Data pipelines, permission mapping, model selection. We connect only what's needed — never everything.
选一条业务线先跑。明确 ROI 指标,每周复盘到员工真在用为止。
One business line, end to end. ROI metrics fixed up front; weekly reviews until adoption is real.
试点模板复用到其他业务线。我们留一个驻场工程师,直到你内部接管。
Replicate the template to neighbouring lines. One engineer stays on-site until your team owns it.
留个邮箱,我们带着行业案例、可行性评估表、最小试点报价上门。第一阶段不收费。 Drop your email. We come with industry cases, a feasibility checklist, and the smallest possible pilot quote. Phase one is free.