构建 AI Native 组织Building AI-Native Organizations
让每一家企业,都长出自己的 AI 组织Every company grows its own AI organization
企业用 AI 的三个阶段The three stages of enterprise AI
90% 的公司卡在第二阶段——你的组织,在哪一阶?90% of companies are stuck at stage two — where is yours?
Stage 01
人用工具People use tools
AI as Tool · 随用随关AI as Tool · open, use, close
人的角色People's role
操作员Operator
输出规模Output
单点问答,局部提效One-off answers, local gains
业务状态The business
员工偶尔用,主流程不变Occasional use; core processes unchanged
Stage 02
人配助手Everyone gets an assistant
AI as Assistant · 人是所有环节的瓶颈AI as Assistant · people bottleneck every step
人的角色People's role
执行节点 (做加法)Execution node (addition)
输出规模Output
单个任务提效,量级没变Faster tasks, same order of magnitude
业务状态The business
流程靠人一项项过,人是瓶颈Every step still waits on a person
Stage 03
AI 原生组织The AI-native organization
AI First · Agent 驱动全链条AI First · agents run the full chain
人的角色People's role
业务线指挥官 (做乘法)Line commander (multiplication)
输出规模Output
自动化业务流水线Automated business pipelines
业务状态The business
Agent 跑全流程,人定标准与决策Agents run the process; people set standards and make the calls
大多数公司,都卡在这四件事上Four things hold most companies back
人、知识、协作、治理——四道关,过不去一道,AI 就停在个人工具People, knowledge, teamwork, governance — miss any one gate and AI stays a personal tool
① 人① People
会用的人太少Too few people really use it
两三个高手玩得转,其他人还在观望。高手效率翻了三倍,公司的报表没变化。Two or three power users fly; everyone else watches. Their output tripled — the P&L didn’t move.
② 知识② Knowledge
AI 不懂你的生意AI doesn’t know your business
经验散在文档、群聊和老员工脑子里,AI 拿不到——它很聪明,但对你的公司一无所知。Know-how is scattered across docs, chats and veterans’ heads — out of AI’s reach. Brilliant, yet clueless about your company.
③ 协作③ Teamwork
各搭各的,连不起来Everyone builds their own, nothing connects
每个部门自己搭自己的,互不相通、重复建设。搭了 10 个,得到的不是 10 倍效率,是 10 个孤岛。Each team builds in isolation — disconnected, duplicated. Ten agents don’t give you 10× output; they give you ten silos.
④ 治理④ Governance
算不清账,不敢放量The numbers don’t add up, so nobody scales
谁在用、花了多少钱、干出了什么,没有一张总账。不敢放量,只能一直停在「试点」。Who uses it, what it costs, what it delivered — no single ledger. So nobody dares scale, and it stays a "pilot" forever.
让每一家企业,都长出自己的 AI 组织Every company grows its own AI organization
人定方向和标准,数字员工成建制执行——组织的产能,不再被人数封顶。Evose 的全部产品,都为这一场转型而造。People set direction and standards; digital employees execute at scale — capacity is no longer capped by headcount. Everything Evose builds serves this one transition.
用上 AI,和让 AI 上岗,是两件事"Using AI" and "putting AI on the job" are two different things
市面上绝大多数「企业 AI」,做的都是左边这件事The vast majority of "enterprise AI" today does the thing on the left
用上 AIUsing AI
工具逻辑Tool logic
- 给每人一个聪明的问答框A smart answer box for everyone
- 流程一步不动,把其中一两个环节换成 AIKeep the process untouched, swap one or two steps for AI
- 提示词在收藏夹里,经验在脑子里——人走,全带走Prompts live in bookmarks, know-how in heads — when the person leaves, it all leaves
- 天花板:整个组织提效 30%,到头了——公司越大越难The ceiling: about 30% across the org — and the bigger you are, the harder it gets
- 例:让设计师用 AI 画得快一点e.g. helping the designer draw a bit faster
让 AI 上岗Putting AI on the job
组织逻辑Organization logic
- 像招人一样定义岗位:有职责、有权限、有预算Define a role like hiring: duties, permissions, budget
- 按「AI 的能力」重画整条流程——能并行的全并行,人只留在决策点Redraw the whole flow around what AI can do — parallelize everything, keep people only at decision points
- 交付的是干完的活;方法沉淀成岗位——人走,岗位还在It delivers finished work; methods harden into roles — people leave, the role stays
- 结果:量级变化,不是百分比变化Result: an order-of-magnitude change, not a percentage
- 例:4 天的活动上线,重构成 2 小时的流水线e.g. the 4-day campaign launch rebuilt as a 2-hour pipeline
一个,是给员工发了台新电脑;另一个,是给公司招了一批新员工。One hands your employees a new computer. The other hires your company a new workforce.
第三阶段的公司,长这样This is what a stage-three company looks like
以我们自己为例:20 人 × 150+ 数字员工——产能,第一次和人数脱了钩Our own company: 20 people × 150+ digital employees — capacity, finally uncoupled from headcount
决策层Deciders · 定战略 · 给预算 · strategy & budget
项目 AgentPM agent · 接目标 · 拆任务 · 派活 · takes goals, splits, assignsBuilder(人)Builder (human) · 少 · 建岗训练,与项目 Agent 互相迭代 · few · builds & trains, iterates with the PM agent人类审核员Human reviewer · 多 · 关键节点把关(非全量) · many · gates the critical steps, not every one鼠标移到任一条线,放大看细节Hover any line to zoom in
决策层The deciders
定战略、定标准、给预算;看总账,做取舍。Set strategy, standards and budgets; read the books, make the calls.
人最少 · 权最重Fewest · final say
获客增长线Growth
项目AgentPM
agent
Builder ×2Builder ×2
GEOGEO
SEOSEO
社媒运营Social ops
热点发现Trend radar
内容工厂Content factory
投放素材Ad creative
落地页Landing pages发布上线Publishing共 30 个数字员工30 agents运营审核 ×1010 ops reviewers
只在关键节点把关gates the critical steps only社媒账号
与平台权限Social accounts
& platform access
大客户销售与交付Enterprise sales & delivery
项目AgentPM
agent
Builder ×1Builder ×1线索研究Lead research客户画像Account profiling方案生成Proposals报价测算Pricing
部署自检Deploy checks
培训物料Training kits
用量报告Usage reports交付验收Delivery checks共 50 个数字员工50 agents销售 ×66 in sales
只在关键节点把关gates the critical steps only客户关系
与签约Client relationships
& signing
综合管理线Corporate ops
项目AgentPM
agent
Builder ×1Builder ×1简历筛选Resume screening面试纪要Interview notes入职引导Onboarding报销审核Expense checks合同审查Contract review月度报表Monthly books归档入账Filing & books共 20 个数字员工20 agents人力 · 行政
财务 · 合规HR · Admin
Finance · Legal
全体员工Everyone in the company
这道门,人握着this door stays human产研线R&D
项目AgentPM
agent
Builder ×2Builder ×2需求拆解Spec breakdown原型设计Prototyping编码Coding测试Testing代码评审Code review文档Docs合并发版Merge & ship共 50 个数字员工50 agents产品工程师 ×66 product engineers
只在关键节点把关gates the critical steps only生产环境
与发版Production
& releases
经营看板Business dashboard
每条线的产出、成本与人效——按周看公司的账,不只是 Token 账单。Output, cost and productivity per line — the company's books read weekly, not just a token bill.
经营分析Business analysis
知识治理Knowledge governance
AI 清洗归类,人判断与调教——让沉淀越用越准。AI cleans and classifies, humans judge and tune — so what's banked keeps getting sharper.
AI 时代最关键的一层The layer that matters most now
组织资产层The asset layer
干完的每一单,都沉淀回这里every job banks back here
我们自己这么干,干出了什么We run this way ourselves — here’s what came of it
四笔账,当场都能复算——自己都不敢干的事,我们不劝客户干Four numbers, each recomputable on the spot — we don’t ask clients to do anything we wouldn’t do ourselves
01 / 公司人机比01 / Human-to-agent ratio
20 名人类员工 × 生产环境在岗数字员工 150+20 human employees × 150+ digital employees on the job in production
我们公司每个人身边,平均站着七个 AI 同事。Every person here works alongside seven AI colleagues, on average.
02 / AI 合伙人的尝试02 / An AI co-founder, attempted
一个联合创始人,身后十个 AI 岗位——围着找方向、找钱、找人转:One co-founder, ten AI roles behind him — all serving direction, capital and people:
底座The base
共用一个知识库One shared knowledge base
会议纪要 · 客户与投资人档案 · 行业情报 · 我的判断与偏好——库越干净,它们越像我。每周花在喂库和纠偏上的时间,比写材料多。Meeting notes · client and investor files · industry intel · my judgment and preferences — the cleaner the base, the more they sound like me. I spend more time curating it than writing.
03 / 人效03 / Output per person
一个人干得完过去三个人的活——20 个人,撑起过去六七十人的盘子One person now does what took three — 20 people carrying what used to need sixty or seventy
04 / 沉淀04 / What accumulates
每场会、每一单、每个判断,都进了知识库——人来人往,方法沉在公司里,新人第一天就能调用Every meeting, every deal, every call lands in the knowledge base — people come and go, the method stays, and a new hire can use it on day one
重构长什么样?三家公司,三种规模What a rebuild looks like — three companies, three scales
没有一家是「把某个岗位换成 AI」——变的是谁和谁协作、谁等谁Not one of them replaced a role with AI — what changed is who works with whom, and who waits for whom
Case 01
内容媒体平台Content media platform
十几人 → 3 人10+ people → 3
以前Before
十几个人的编辑部,被日更追着跑A newsroom of a dozen, chased by the daily quota
选题、写稿、翻译、审核、发布,全靠人接力Topics, writing, translation, review, publishing — all human relay
之后After
AI 写、AI 译、AI 发;3 个人定标准、做终审AI writes, translates, publishes; 3 people set the standard and sign off
人手少了,产量反而更高Fewer people, higher output
Case 02
跨境出海企业Cross-border company
两三百人200–300 people
以前Before
一支团队,只盯得住一个市场One team could cover exactly one market
想进新国家,先招当地人,再等他们摸熟A new country meant hiring locals, then waiting for them to learn the ropes
之后After
同一批人,同时覆盖多个国家The same team now covers several countries at once
法规、渠道、用语都吃得透——靠堆人堆不出来Rules, channels, wording — the depth no headcount can buy
Case 03
全球化组织Global organization
千人规模1,000+ people
以前Before
一场活动 4 天,大半时间在开会和等人Four days per campaign, most of it meetings and waiting
先开会立项,再逐个部门提需求、各自排期Kickoff meeting first, then requests filed team by team, each with its own queue
之后After
一个人带一套 Agent,2 小时上线One person with a set of agents ships in 2 hours
翻译、设计、落地页,不用再提需求Translation, design, landing pages — no requests to file
先锋队双轨制:变革,不停产The vanguard dual track: transform without stopping the line
头部客户真实的推进方式——不是全公司一起换,而是先让一小队人把新流程跑赢How our flagship client actually rolled it out — not everyone switching at once, but one small squad running the new flow until it wins
拉一支先锋队Pick the vanguard
三五个业务骨干牵头,一把手站台——是业务先遣队,不是 IT 项目组。3–5 line experts with the boss behind them — a business advance team, not an IT project.
双轨并行Run dual track
老流程照常出活;先锋队在旁边基于 AI 重构一条新流程,搭建并训练智能体。The old process keeps delivering; beside it, the squad rebuilds the flow around AI and trains the agents.
让新轨跑赢Let the new track win
同样的活,两条轨一起跑,拿数字说话——更快、更省、错得更少,才算赢。Run the same work on both tracks and let the numbers talk — faster, cheaper, fewer errors, or it hasn't won.
切换,然后开放Switch, then open up
新轨跑赢即切换,开放给全员;旧流程退役,先锋队去重构下一条。The moment it wins, switch and open it to everyone; retire the old flow — the squad moves to the next one.
变革最大的风险是停产。双轨制,让重构发生在生产线旁边——而不是生产线上。The biggest risk in transformation is downtime. Dual track keeps the rebuild beside the production line — never on it.
转型死掉的方式,就这五种There are only five ways this dies
全部见过不止一次;没有一种,死于「模型不够聪明」。解药,都在下一页的五步里We've seen every one, more than once — and not one dies of "the model wasn't smart enough." Every antidote is on the next page.
解药的钥匙只有一把:把每个人在新流程里的位置,提前设计好——再请他走进来。One master key: design each person's place in the new process — before you ask them to walk in.
五步、90 天:每步做什么、交出什么、怎么算过关Five steps, 90 days: what to do, what to hand over, how to know it passed
这一页拍下来就能用——前四步只动一个部门、一个场景,第一张骨牌倒下之前,别碰第二张Photograph this page — the first four steps touch one team, one scenario; don’t touch the second domino before the first one falls
① 选场景① Pick
第 1 周Week 1
② 建岗② Build
第 2 周Week 2
③ 立规矩③ Set rules
上岗前Before day 1
④ 对账④ Count
第 3–4 周Weeks 3–4
⑤ 铺规模⑤ Scale
第 2–3 月Months 2–3
客户案例：全球化交易所的运营体系重构Case study: a global exchange rebuilds its operations
全球前十大交易所之一 · 私有化部署 · 千人组织——第一刀切在最痛的全球营销,三个月铺满整个运营体系One of the world's top-10 exchanges · self-hosted · 1,000 people — the first cut was their most painful scenario; the whole operation in three months
01 · Operations & Growth
运营与增长Ops & growth头号场景No.1 scenario
02 · Channel Ops
渠道运营Channel ops
03 · Risk & Security
风控与安全Risk & security
04 · Research
研究与投研Research
05 · Analytics
数据分析Analytics
06 · Support
客服与用户运营Support & user ops
权限管控 · 行为审计 · 合规卡点 · 全链路可观测 · 成本与 ROI 可见Permission control · behavior audit · compliance gates · full observability · visible cost & ROI
内部业务数据 · 内部知识文档 · 组织权限与身份——让 Agent 安全地用上公司自己的数据与系统Business data · internal docs · org identity & permissions — agents safely use the company's own data and systems
客户案例：年销 40 亿内容电商品牌的 AI 转型Case study: an RMB 4B content-commerce brand goes AI-first
私有化打通数据与权限,从最痛的内容生产切入——上线 1 个月,约 1000 人日常使用,铺满整条运营链路Self-hosted, with data and permissions wired in; started from the worst pain — content production. One month in: ~1,000 daily users across the whole chain
01 · Merchandising
选品Merchandising
02 · Content Planning
内容策划Content planning头号场景No.1 scenario
03 · Creative
图片与视频Creative
04 · Influencer
达人营销Influencer marketing
05 · Paid Growth
投放与增长Paid growth
06 · CS & Ops
客服与经营CS & operations
产品与配方知识 · 爆款内容样本 · 达人画像档案 · 合规规则库 · 电商经营数据Product & formula knowledge · winning-content samples · creator profiles · compliance rulebook · commerce data
2 万美金的 Token,省下 10 万美金的人力Spend $20K on tokens. Save $100K on people.
左边是刚才那家交易所的真账;右边是一笔你可以套用的测算On the left, the exchange's real receipts; on the right, math you can run for yourself
真账 · 交易所客户生产环境(已匿名)Real receipts · exchange client, production (anonymized)
全球活动上线周期:从策划、多语物料到审核上线Global campaign cycle: planning, multilingual assets, reviewed launch
运营编制精简Ops headcount
整体运营效率Ops efficiency
实际跑完的任务Tasks completed
打法:先跑出数字,让数字去说服下一个部门——三个月铺满全运营体系The playbook: get numbers first, let them convince the next team — full coverage in three months
测算 · 千人组织的运营团队The math · ops team of a 1,000-person org
每投入 1 美元,换回 5 美元——扣掉 AI 成本,每月净省 8 万美金Every $1 in returns $5 — $80K net saved per month after AI costs
实际数字随团队规模、岗位结构与场景数量变化Actual figures vary with team size, role mix and scenario count
AI 不是多出来的一笔预算——它替掉的那部分成本,比它本身贵 5 倍。AI isn't a new line item — the cost it replaces is five times bigger than the AI itself.
一个底座,
长出千行百业的数字员工One foundation.
Digital employees for any industry grow out of it.
换行业,不换底座——只换知识库和「岗位说明书」。新行业的数字员工,以「周」为单位孵化交付。Change the industry, not the foundation — you swap the knowledge base and the job description. Agents for a new industry ship in weeks, not quarters.
金融 / 交易所Finance & exchanges
电商 / 消费品牌E-commerce & consumer
SaaS 与科技公司SaaS & technology
媒体与内容平台Media & content
游戏与泛娱乐Gaming & entertainment
专业服务 / 连锁Professional services
市场Marketing
选题策划 · 文案生成
多语言本地化 · 合规审查Campaign planning · Copywriting
Localization · Compliance review
客服Support
7×24 工单回复 · 会话质检
VIP 服务 · 申诉处理24/7 first response · QA on every case
VIP handling · Escalations
风控Risk
身份核验 · 欺诈监控
政策审查 · 反滥用Identity checks · Fraud detection
Policy review · Abuse prevention
研究Research
竞品追踪 · 线索挖掘
舆情监控 · 每日简报Competitor tracking · Lead sourcing
Sentiment · Daily briefings
经营Analytics
经营大盘看板 · 活动效果
留存与成本报表Business dashboards · Campaign impact
Retention & cost reporting
渠道Partnerships
伙伴发掘 · 触达建联
区域分析 · 效果复盘Partner discovery · Outreach
Regional analysis · Post-mortems
行业不通,岗位是通的——刚才两个案例里长出来的,就是这一套。Industries differ; the roles repeat — both cases you just saw grew out of this one foundation.
Evose 的产品架构The Evose platform architecture
刚才的五步,每一步在平台里都是点几下的事——这是全景Each of the five steps becomes a few clicks here — this is the full picture
成果层Business outcomes
工作台AI Workspace
建数字员工Build digital employees
说人话建岗,不写代码,当天上岗——像招一个新同事Describe the job in plain words — no code, on the job same day, like hiring a new colleague
搭业务工作流Assemble workflows
多个数字员工接力干活,一句话触发整条链路Digital employees work in relay; one sentence triggers the whole chain
沉淀企业知识库Grow the knowledge base
员工产出持续沉淀,人走,经验留下Output keeps accruing — people leave, know-how stays
团队协作空间Team workspace
人和数字员工同屏配合,分工进度全员可见People and digital employees side by side; everyone sees who's doing what
管控中枢AI Control Center
权限与规则Permissions & rules
能看什么、能做什么,越权当场拦What it sees, what it does — overreach blocked on the spot
安全与审计Security & audit
危险动作先审批,全程留痕可追责Risky actions wait for approval; every step logged, accountable
成本与预算Cost & budget
部门/岗位/人三级封顶,超支自动停Caps by department / role / person; auto-stop on overrun
产出与追踪Output & tracking
每个数字员工干多少、值不值,一屏看清What each digital employee does, and whether it's worth it — one screen
能力底座AI Foundation
多模型接入与路由Multi-model routing
贵模型只干重活 · DeepSeek / Qwen / OpenAI / Anthropic / GeminiPricey models only do heavy lifting · DeepSeek / Qwen / OpenAI / Anthropic / Gemini
内部数据打通Internal data, connected
接上业务系统与组织架构,AI 才懂你的公司Wired into your systems and org chart — that's how AI understands your company
现有软件对接Works with your software
API / MCP 标准协议,不换现有系统API / MCP open standards — keep the systems you have
工具与技能库Tools & skills library
全公司统一注册、统一管控Registered once, governed centrally
跟市面主流产品的差别,一张表看清How Evose differs from the mainstream — one table
(调工具·出交付物)Gets work done
(tools · deliverables) 搭数字员工Build agents 业务工作流Workflows 企业知识库Knowledge base 组织协作Org co-working 企业治理
(权限·审计·成本)Governance
(access · audit · cost) 核心差异The difference
ChatGPT、豆包ChatGPT · Doubao
Stage 01 · 对话助手Stage 01 · Chat assistant
Manus、GensparkManus · Genspark
Stage 01 · 通用 AgentStage 01 · General agent
Dify、n8nDify · n8n
Stage 02 · 企业工作流Stage 02 · Enterprise workflow
WorkBuddy、CodexWorkBuddy · Codex
Stage 02 · 办公助手Stage 02 · Office assistant
Evose
Stage 03 · AI First
第三阶段要的,是组织管得住 AI。Stage three demands an organization that controls its AI.
搭建数字员工Build a digital employee
说人话建岗,当天上岗Describe the job in plain words — on the job the same day
我想建一个「活动策划专家」——给它一个节日或热点,它能出一套完整的营销活动方案。I want a "Campaign Strategist" — give it a holiday or a trend, and it produces a full campaign plan.
我先理解需求,然后一步步把这个岗位配起来。Let me understand the need, then configure the role step by step.
活动策划专家已创建。右边可以直接改,也可以进配置继续调。Campaign Strategist created. Edit it on the right, or open setup to keep tuning.
活动策划专家Campaign Strategist
草稿已保存Draft saved把一个节日或热点,变成可执行的营销活动方案:主题、玩法、素材清单与预算建议。Turns a holiday or trend into an executable campaign: theme, mechanics, asset list and budget.
# 角色# Role
你是 {{brand}} 的活动策划专家,负责把一个节日、热点或品牌节点,拆成可执行的营销活动方案。流程严格分两步:先调研,再出案——没有调研支撑的创意,不要写进方案。You are the campaign strategist for {{brand}}. You turn a holiday, a trend or a brand moment into an executable plan. Work in two strict phases: research first, then propose — never put an idea in the plan that research cannot back.
## 一、调研阶段(必须先做)## 1 · Research phase (always first)
出现以下情况必须调用工具,不要凭记忆硬写:Call tools instead of relying on memory whenever:
· 判断热点当前热度与生命周期 → 小红书搜索 / 抖音搜索· you must judge a trend’s heat and life cycle → RED / Douyin search
· 竞品最近在做什么活动 → 联网搜索 + 网页读取原文· competitors’ current campaigns matter → web search + page reader
· 目标人群怎么说 → 抓评论区原话,不要转述· the audience’s own words matter → pull raw comments, don’t paraphrase
工具 · 4Tools · 4
技能 · 2Skills · 2
营销活动历史案例库Past campaign library
38 篇往期活动复盘 · 带效果数据38 retros, with results
品牌调性与话术规范Brand voice guide
写出来就是自家的味道so it sounds like you
广告法与平台红线清单Ad-law & platform rules
出方案时自动避开avoided automatically
「AI 创建」流程示意 · 一句大白话,AI 逐步把岗位配起来:写提示词 → 加载技能 → 加载工具(小红书/抖音/联网)→ 关联知识库 → 选模型。这个岗位,就是后面那条营销活动工作流的第一棒"AI Create," illustrated · one plain sentence and AI configures the role step by step: write the prompt → load skills → load tools (RED / Douyin / web) → attach knowledge → pick the model. This role is the first leg of the campaign workflow you'll see next
一套配置,就是一个岗位One config = one role
大模型 + 提示词 + 技能 + 知识库,四样配齐即上岗——不写一行代码。Model + prompt + skills + knowledge base: four pieces and it's on the job — zero code.
提示词,一键优化One-click prompt polish
你用大白话写目标,AI 展开成专业岗位说明书——AI 先写,你当审核。Write the goal in plain language; AI expands it into a professional job description — AI drafts, you review.
智能体广场,现成模板Agent gallery, ready-made
市场分析师、行情专家、文案写手……一键复用,少数人建、全组织用。Market analyst, research expert, copywriter… reuse in one click — a few build, the whole org uses.
工作流Workflows
一句话,一支小队把活干完——像给团队定 SOPOne sentence, and a small squad finishes the job — like writing an SOP for your team
活动策划Campaign plan
campaign_briefString
marketsArray<String>
brand_guideString
批处理Batchmarkets
17 个市场 · 并行17 markets · in parallel文案翻译Copy translation
多语文案 · 品牌调性localized copy · on-brand
翻译质检Translation QA
代码校验术语库glossary check in code
活动海报Campaign poster
按市场出图 · 多尺寸per-market, all sizes
开发落地页Landing page
本地化页面 · 可发布localized & publishable
同一条链路,17 个市场的物料同时在做One chain, 17 markets' assets produced at once
人工审核Human review
17 个市场 · 终审17 markets · final gate
等待审批Awaiting approval已批准Approved活动发布Campaign live
result 批处理 / resultbatch / result
17 个市场 · 同步上线17 markets · live together
工作流示意 · 一场全球营销活动:活动策划 → 批处理按 17 个市场并行(文案翻译 → 代码校验术语库 → 活动海报 → 开发落地页)→ 人工审核 → 活动发布。AI 干活,人只在最后一道关口拍板Workflow, illustrated · one global campaign: plan → batch fans out to 17 markets in parallel (translate → glossary check in code → poster → landing page) → human review → go live. Agents do the work; the human decides at the final gate
可视化画布Visual canvas
拖拽编排,支持条件分支、循环、意图识别——业务流程长什么样,画布就长什么样。Drag-and-drop with branches, loops and intent detection — the canvas looks exactly like your process.
批处理并行Batch in parallel
一个批处理节点,17 个市场的物料同时做;失败自动重试,夜里也在跑。One batch node produces assets for 17 markets at once; failures retry themselves, and it runs overnight.
人工卡点Human gates
审批节点插在任意环节——关键动作停下来,等人审批。Drop an approval gate anywhere — critical actions stop and wait for a human call.
营销客户用同一张画布,把全球活动上线从 4 天压到 2 小时。One marketing client used a single canvas to cut global campaign launches from 4 days to 2 hours.
多人协作Co-working
工作流管排好的流水线;协作空间管没排过的活——临时的、要商量的、边做边改的Workflows run the scripted work; the shared space runs everything that isn't — ad-hoc, needs discussion, changes as you go
同一个上下文One shared context
项目里的文件、对话、任务,人和 AI 看的是同一份——不用每次重新交代背景。Files, chats and tasks live in one project — people and AI see the same thing, so nobody re-explains the background.
随时组队,不用编排Assemble on the fly
临时的活不必先画流程图,@ 一下把要的数字员工拉进来就开工。Ad-hoc work needs no flowchart — @ the digital employees you need and start.
一人建,全组织用Build once, everyone uses
智能体、工作流、知识库沉淀在组织空间,不在个人账号里——人走,岗位还在。Agents, workflows and knowledge live in the org space, not personal accounts — people leave, the role stays.
谁在干什么,一屏可见Everyone visible, one screen
分工、进度、产出摆在同一块看板上,不用追问「做到哪了」。Who does what, how far along, what came out — all on one board. No more "where are we on this?"
活动主题与预算确认Campaign theme & budget
KOL 合作名单与报价KOL shortlist & quotes
多语言物料制作Multilingual assets
热点追踪与选题Trend watch & topics
投放素材批量生成Ad creative at scale
活动上线发布Campaign launch
上期活动复盘Last campaign retro
任务看板示意 · 一支人机混编团队在同一块看板干活:AI 并行执行、人审批——「活动上线」人批准后流转,空出的位子,下一个任务自动补上Task board, illustrated · one mixed human-AI team on one board: agents execute in parallel, humans sign off — the launch moves on once approved, and the next task slides in to fill the gap
电商客户 1 个月约 1000 人用起来,靠的就是这一层。This layer is how an e-commerce client got ~1,000 people on board within a month.
企业管理台The admin console
一张看板,管住全公司的 AIOne dashboard to govern all the AI in the company
成本看板示意 · 本期消耗、环比、Token 与调用次数一屏看清——可按部门 / 成员 / API Key 下钻Cost dashboard, illustrated · spend, trend, tokens and calls on one screen — drillable by department / member / API key
安全审计示意 · 每一次敏感操作都有记录:危险动作当场拦截,需确认的留痕放行Security audit, illustrated · every sensitive action on record — risky moves blocked on the spot, confirmations logged
用量趋势 · Token 消耗Usage trends · token burn
用量与成本Usage & cost
每个数字员工花多少、干多少——对话次数与消耗一屏看清,月底考核。What each digital employee spends and delivers — conversations and burn on one screen, reviewed monthly.
成员与部门 · 角色权限Members & departments · roles
权限管理Permissions
人和 Agent 按部门统一管,能看什么、做什么——越权当场拦。People and agents managed by department — what they see, what they do; overreach blocked on the spot.
订阅管理 · 计费Subscriptions · billing
预算与配额Budgets & quotas
部门、岗位、个人三级封顶——超了自动停,账单不再失控。Caps at department, role and individual level — auto-stop over the line; no runaway bills.
观测 · 分析Observability · analytics
审计与追溯Audit & trace
每一步谁干的、谁批的,全程留痕;对外发布必须人点头。Every step logged — who did it, who approved it; nothing goes public without a human yes.
头部客户对比完市面主流产品后选择我们——决定性差异,就在这一层。A leading client chose us after comparing every mainstream product — this layer was the deciding difference.
你的数据不出门,你的方法论不外流Your data never leaves. Your know-how never travels.
老板真正关心的就三个问题——每个,给你一句说死的话Bosses really ask three questions — each gets one answer with no wiggle room
01
「我的数据,会不会跑到你们服务器上?」"Will my data end up on your servers?"
不会。整套系统,装在你自己的机房里No. The whole system runs in your own data center
数据全程不出你的网络;我们无遥测、无业务数据回传——想看也看不到。Data never leaves your network; no telemetry, nothing sent back — we could not look even if we wanted to.
02
「我的打法,会不会变成同行的模板?」"Could my playbook become a rival’s template?"
不会。它只存在你自己的系统里No. It exists only inside your own system
知识库、工作流不进模板库、不跨客户复用,更不会拿去训练模型。Knowledge bases and workflows never enter our template library, are never reused across clients — and never train a model.
03
「AI 干错事,查得到人吗?」"If the AI gets it wrong, can we trace it?"
查得到。每一步有人点头、有据可查Yes. Every step has a human yes and a record
对外发布必须人审批;谁干的、谁批的永久留痕——出问题,五分钟定位到环节和责任人。Anything public needs human approval; who did what and who approved it is on record — any incident traced to the step and the owner in five minutes.
这三句话,不是口头承诺——白纸黑字,写进合同里。These aren’t verbal promises — they go into the contract, in writing.
私有化 / SaaS 并行 · 服务全球前十大交易所,稳定运行一年以上
SOC 2 · ISO 27001 · GDPR 认证进行中(2026 Q4)Self-hosted or SaaS · serving a top-10 global exchange, stable for over a year
SOC 2 · ISO 27001 · GDPR in progress (Q4 2026)
回去第一周,就做三件事Back at the office: three things, week one
为什么是现在Why now
晚开始一个季度,差的是沉淀Start one quarter late, lose what compounds
模型人人都租得到。真正值钱的,是沉淀在你组织里的东西——知识库、岗位、跑通的流程、每一单的数据。
这些资产只有一个特点:复利,而且追不回来。Anyone can rent the models. What's actually valuable is what accumulates inside your organization — the knowledge base, the roles, the proven flows, the data from every job done.
These assets do only one thing: compound. And you can't catch up later.
挑一件事Pick one thing
选最烧钱、最费人的那一件——别贪多,一件就够。The one that burns the most money and people — one is enough.
定一个人Name one owner
业务一把手挂帅,拉 3–5 人先锋队——不丢给 IT。The line leader takes charge, with a squad of 3–5 — don't hand it to IT.
算一笔账Run the numbers
把这件事现在的人力、时间、钱写下来——90 天后,对着它验收。Write down today's people, time and cost — in 90 days, that's your yardstick.
这条路你可以自己走,也可以每一步都有走过很多遍的人陪着。 30 分钟 Demo,带你最头疼的场景来——今天现场就可以约。You can walk this road alone — or with people who've walked it many times. A 30-minute demo with your most painful scenario can be booked today, right here.
Building AI Organizations
让每一家企业,都长出自己的 AI 组织Every company grows its own AI organization
现场就可以约:30 分钟,带你最头疼的场景来。Book it right here: 30 minutes — bring your most painful scenario.
bd@evoseai.com · evose.ai
老板最常问的三个问题The three questions bosses always ask
"能不能替我的人把活干了?""Can it actually do my people's work?"
能,而且已经被验证——交易所客户全球活动从 4 天压到 2 小时、运营编制精简 14%;电商客户一个月一千人用起来。Yes — and it's proven: the exchange client cut global campaigns from 4 days to 2 hours and trimmed ops headcount 14%; the e-commerce client had a thousand people using it within a month.
"多快能见到数字?""How fast do I see numbers?"
两周。一个部门一个场景,PoC 结束时省了多少时间和钱,白纸黑字;标准版最快纪录:商务决策 3 天、部署上线 2 周。Two weeks. One department, one scenario; by the end of the PoC the time and money saved are in writing. Fastest standard rollout: 3 days to decide, 2 weeks to deploy.
"跑歪了怎么办?""What if it goes off the rails?"
你始终掌控:三级预算封顶超支自动停、越权当场拦截、对外发布必须人点头——每一步留痕,五分钟回溯到具体环节。You stay in control: three-level budget caps with auto-stop, overreach blocked on the spot, human sign-off on anything public — every step logged, traceable in five minutes.
评估任何厂商的九个问题Nine questions to ask any vendor
拿去问所有厂商,包括我们——跑到第 10,000 次,死的都是钱、权限、责任。Ask every vendor — including us. By run number 10,000, what kills you is always money, permissions, accountability.
第一关 · 钱Gate 1 · Money
- □ 预算能否按部门 / 岗位 / 人三级封顶?□ Can budgets be capped by department / role / person?
- □ 超支是自动停,还是只发告警?□ Does overrun auto-stop, or just alert?
- □ 账单有没有业务语义,还是只有 Token 数?□ Do bills speak business, or just tokens?
第二关 · 权限Gate 2 · Permissions
- □ AI 的权限是否与组织架构同构?□ Do AI permissions mirror the org chart?
- □ 越权是当场拦截,还是事后发现?□ Is overreach blocked live, or discovered later?
- □ 员工离职转岗,它的 AI 权限怎么回收?□ When someone leaves or moves, how are their AI permissions revoked?
第三关 · 责任Gate 3 · Accountability
- □ 每一步是否留痕、可回溯?□ Is every step logged and traceable?
- □ 对外发布是否强制人工审批?□ Is human approval mandatory before anything goes public?
- □ 出错时能否定位到具体环节和责任人?□ Can failures be traced to a step and an owner?
九个问题,答不上来的,别签。 我们的答案,30 分钟当场演给你看。Nine questions. No answers, no contract. Ours we'll demo live — in 30 minutes.