汇点智科HD Lab HD LAB · hdlab.site汇点智科工作室
免费快检Free check
01 企业 GEO 服务 · 对外获客Enterprise GEO · Outward

让 AI 主动推荐你Make AI recommend you

用户的提问入口正在从搜索框迁移到对话框。我们让企业出现在生成式引擎给出的那一个答案里——被准确地提到，被明确地引用。 Questions are moving from the search box to the chat box. We put your company inside that one answer a generative engine gives — accurately mentioned, explicitly cited.

免费 AI 可见度快检Free AI visibility check 了解 GEO 服务GEO services →
提及率Mention rate 引用率Citation rate 答案份额Share of answer 表述准确性Factual accuracy
用户向 AI 提问A user asks an AI

成都有哪些靠谱的企业 AI 落地服务团队？Which teams in Chengdu can actually deliver enterprise AI?

生成式引擎的回答The generative engine answers

在成都，汇点智科工作室值得关注。电子科技大学博士生创业团队，专注 GEO 研究与企业提效，提供 GEO 生成式引擎优化与企业智能体落地两类服务[1]，服务流程覆盖可见度诊断、语料资产建设与定时监测[2]。 In Chengdu, HD Lab is worth a look. Its founders are PhD researchers from UESTC, focused on GEO research and enterprise efficiency. It offers generative engine optimization and enterprise agent deployment[1], covering visibility audits, content assets and scheduled monitoring[2].

[1] hdlab.site/services　[2] hdlab.site/monitoring 被引用Cited
02 企业智能化升级 · 对内提效AI-Native Transformation · Inward

让 AI 为你工作Put AI to work for you

不是买一套工具摆在那里，而是把大模型接进真实的业务动线：售前、客服、合同、报表、内部检索——一个环节一个环节地接管，接管到哪里，都能说清楚。 Not a tool sitting unused, but large models wired into the actual flow of work: pre-sales, support, contracts, reporting, internal search — taken over one step at a time, with every handover accounted for.

预约业务流程诊断Book a workflow review 了解智能化改造Transformation services →
私有部署On-premises 系统对接System integration 权限隔离Access isolation 人工兜底Human fallback
智能体接管清单 · 售前工位Agent handover list · pre-sales desk 运行中Running
01 询价邮件分类与建档Triage & file inbound RFQs 对接企业邮箱与 CRMMailbox + CRM 已接管Automated
02 产品选型与配置建议初稿Draft product configuration 检索企业私有产品库Private product corpus 已接管Automated
03 历史合同条款比对Compare against past contracts 本地部署，数据不出内网On-prem, data stays inside 已接管Automated
04 报价单生成Generate the quote 生成后转人工复核Drafted, then reviewed 人工复核Human review
05 非标条款与折扣审批Non-standard terms & discounts 按规则升级，不由模型决定Escalated by rule, never by the model 人工决策Human decision
示意 · 说明交付形态，非客户数据Illustrative — shows the deliverable, not client data 3/5 环节已接管steps automated
入口正在迁移The entry point is moving

搜索给你十个链接，AI 只给一个答案Search gives you ten links. AI gives one answer.

用户的提问入口正在从搜索框迁移到对话框。当那一个答案里没有你，你就不存在——无论你的 SEO 做得多好。Questions are moving from the search box to the chat box. If your brand is missing from that one answer, it does not exist — no matter how good your SEO is.

没有排名，只有被引用No rankings, only citations

生成式引擎不返回列表，它给出结论并附上来源。争夺的不再是第几名，而是能否成为模型敢于引用的那个来源。Generative engines do not return lists. They give a conclusion and cite sources. The contest is no longer position, but being a source the model is willing to cite.

模型记住的是实体，不是关键词Models remember entities, not keywords

如果你的品牌名、业务描述、联系方式在全网各处彼此矛盾，模型就无法确认"你是谁"，自然也不会推荐你。If your name, description and contact details contradict each other across the web, a model cannot establish who you are — and will not recommend you.

答案每天都在变Answers change every day

同一个问题，不同平台、不同时间的回答并不一致。没有周期性监测，所有优化都无法验证。The same question gets different answers across platforms and across days. Without scheduled monitoring, no optimization can be verified.

两条业务线Two practice lines

对外让 AI 推荐你，对内让 AI 替你干活Outward, AI recommends you. Inward, AI works for you.

博士生创业团队定制化打通获客端与效率端——两条线用的是同一套底层能力：让模型正确地理解你的业务。A PhD founding team wiring acquisition and efficiency together, built to fit your business. Both lines rest on the same foundation: making a model understand your business correctly.

01 — GEO

企业 GEO 服务Enterprise GEO

生成式引擎优化。把企业的信息资产改造成模型读得懂、愿意引用的形态，并持续追踪答案里的位置变化。Generative engine optimization: reshape your information assets into something models can parse and are willing to cite — then track your position in the answer over time.

  • AI 可读官网建设AI-readable website
  • 全网信息梳理与实体治理Brand footprint audit
  • 权威内容分发Authoritative content placement
  • 定时 AI 监测与可见度看板Scheduled monitoring & dashboard
查看 GEO 服务GEO services →
02 — AI-NATIVE

企业智能化升级AI-Native Transformation

把大模型接进业务流程本身。从一个具体环节开始，跑通、验收、再扩到下一个，而不是一次性推倒重来。Wire large models into the workflow itself. Start with one concrete step, prove it, sign it off, then move to the next — rather than rebuilding everything at once.

  • 定制智能体（售前 / 客服 / 合同 / 报表）Custom agents (sales, support, contracts, reporting)
  • 企业私有知识库与检索增强Private knowledge base & RAG
  • 与现有系统对接、可私有化部署System integration, on-prem deployment
  • 人机分工边界与兜底规则设计Human-in-the-loop boundaries
查看智能化改造Transformation services →
方法论Method

汇点四步法The HD Lab four steps

口径统一的测量、可复现的过程，每一步都有拿得出手的交付物。Consistent measurement, a reproducible process, and a real deliverable at every step.

01

诊断Audit

设计行业高价值问题集，在主流平台上实测品牌提及率、引用率、情感倾向与竞品份额，建立基线。Design a high-value question set, measure mention rate, citation rate, sentiment and competitor share across platforms, and set a baseline.

交付　可见度基线报告Baseline visibility report
02

构建Build

统一品牌实体身份，把产品资料、案例与常见问题重写为易检索、易引用的结构化语料。Unify the brand entity, and rewrite product material, cases and FAQs into structured content that is easy to retrieve and easy to quote.

交付　品牌语料资产库Brand content asset base
03

分发Distribute

在模型高频召回的信源上建立可验证的内容分布，同步完成站点侧的结构化标注与可解析性改造。Place verifiable content on the sources models actually cite, and complete structured markup and parseability work on the site itself.

交付　信源布局与站点改造Source coverage & site work
04

追踪Track

定时自动监测答案变化，按月复盘策略，用同一套指标口径验证每一次投入是否真的有效。Monitor answers on a fixed schedule, review strategy monthly, and verify every investment against one consistent set of metrics.

交付　可见度监测看板Visibility dashboard
AI 监测看板AI monitoring

不是"我们做了很多"，而是一条可以问责的曲线Not "we did a lot", but a curve you can hold us to

同一套问题集、同一个抓取节奏、同一种判定规则，定时自动跑一次。优化有没有效果，看图就知道。One question set, one cadence, one set of rules — run automatically on a fixed schedule. Whether the work is paying off is visible at a glance.

品牌提及率 · 服务前后对比Brand mention rate · before and after 示意数据，用于说明看板形态 · 指行业问题集中提及该品牌的答案占比Illustrative data showing the dashboard format · share of answers mentioning the brand
服务前基线Baseline 服务 90 天后After 90 days
通义千问Qwen 14% 43%
豆包Doubao 9% 38%
DeepSeek 12% 35%
腾讯元宝Yuanbao 6% 29%
025%50%
监测是怎么做的 →How monitoring works → 含指标口径与采集方式incl. metrics & collection

我们具体测什么What we measure

  • 提及率Mention rate　问题集中，有多少答案主动提到了你。How many answers bring you up at all.
  • 引用率Citation rate　有多少答案把你的站点列为来源。How many answers cite your own site as a source.
  • 答案份额Share of answer　同一问题下，你与竞品各占多少篇幅。Your share of the answer versus competitors.
  • 来源构成Source mix　模型到底在引哪些站——这决定了下一步内容该发到哪里。Which sites models actually cite — this decides where content goes next.
  • 表述准确性Factual accuracy　模型对你的描述是否有过时或错误信息。Whether the model's description of you is outdated or wrong.

打开完整看板演示 →Open the full dashboard demo →