CCBots / 解决方案Solutions / B · FDE 驻场 · 难度系数标准B · FDE · difficulty standard

AI 驻场工程师 FDE
把 AI 嵌入你的核心流程
FDE on-site engineer
embedding AI into your core processes

这是三层台阶的 B 层 · 核心流程。如帕兰蒂尔一般,由一位 FDE(Forward Deployed Engineer)驻场,深入贵公司最关键、最不容差错的业务流程,定制开发贴合实际的工作流智能体。报价不再采用按周期固定总价,而是「每日入驻基础单价 × 智能体化难度系数」——为“自动化的真实难度”提供清晰定价。This is layer B · core process. As Palantir does, a Forward Deployed Engineer (FDE) works on-site, goes deep into your most critical, error-intolerant processes, and builds workflow agents that fit reality. Pricing is no longer a fixed cycle total — it is daily base rate × agentification difficulty coefficient, giving a transparent price for how difficult the work truly is to automate.

定价模型 · 透明计价Pricing model · transparent

每日基础单价 × 难度系数 = 实际零售单价Daily base × difficulty coefficient = retail day rate

将传统的“按周期固定总价”拆解为两个可解释的部分:一个公开、固定的基础单价,乘以一个有标准、可复核的难度系数We decompose the traditional fixed-cycle total into two explainable parts: a public, fixed base rate times a standardized, auditable difficulty coefficient.

实际零售单价 = ¥6,000 / 人·天 × 难度系数(1.0 – 3.0) Retail day rate = ¥6,000 / person·day × difficulty coefficient (1.0 – 3.0) 项目总价 = 实际零售单价 × 预估人天(人天同样由 Opus 4.8 依据模块拆解估算,先给区间、再随交底校准)Project total = retail day rate × estimated person-days (also estimated by Opus 4.8 from module breakdown — a range first, calibrated as scope firms up)
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基础单价 · 公开Base rate · public

¥6,000 / 人·天,对应难度系数 1.0 的最简智能体工作。透明、固定,不藏价。¥6,000 / person·day, the simplest agent work at coefficient 1.0. Transparent, fixed, nothing hidden.

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难度系数 · 有标准Coefficient · standardized

Opus 4.8 按统一的 ADC 五维标准评估,1.0–3.0,分 L1–L5 级。同一把尺,谁来量都一样。Assessed by Opus 4.8 on a unified 5-dimension ADC standard, 1.0–3.0, tiered L1–L5. One ruler for everyone.

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可复核 · 可调Auditable · adjustable

系数与人天均给出五维打分依据;随真实交底材料复核,先小范围验证再行扩展,不做一次性的宏大承诺。Both coefficient and person-days come with a 5-dimension rationale, re-checked against real materials. Validate at small scale first, no all-at-once promises.

行业标准 · ADCIndustry standard · ADC

智能体化难度系数标准(ADC)Agentification Difficulty Coefficient (ADC)

一项业务工作"交给智能体"到底有多难?我们把它拆成五个工程维度,每维 1–5 分。这不是拍脑袋——每一分都对应明确的工程判据,让难度可被讨论、可被复核。How hard is it to hand a piece of work to an agent? We break it into five engineering dimensions, each scored 1–5. Not guesswork — every point maps to an explicit engineering criterion, so difficulty can be discussed and audited.

D1

流程确定性Determinism

1=可被规则/SOP 明确描述、参数化拼装
5=强主观判断、创造性、无固定流程
1=clear rules/SOP, parametric
5=heavy judgment, creative, no fixed flow
D2

知识显隐性Knowledge explicitness

1=显性(标准 / 法条 / 文档现成)
5=高度隐性,锁在专家脑中需逐项确认
1=explicit (standards/law/docs)
5=tacit, in experts' heads, needs sign-off
D3

数据就绪度Data readiness

1=结构化文本现成
5=扫描件 / 图纸 / 多模态 / 散落,提取成本高
1=structured text ready
5=scans/drawings/multimodal/scattered
D4

校验闭环与风险Verifiability & stakes

1=可自检、错了也低风险
5=高风险难校验(法律授权 / 物理 / 资金)
1=self-checkable, low stakes
5=high-stakes, hard to verify
D5

系统耦合System coupling

1=纯文本、无外部耦合
5=深度耦合(ERP / CAD 内核 / API)+ 生成式 CAD/3D
1=plain text, no coupling
5=deep coupling (ERP/CAD/API) + generative CAD/3D
难度系数 = 1.0 + 0.1 × ( Σ − 5 )   Σ = D1+D2+D3+D4+D5 ∈ [5, 25] → 系数 ∈ [1.0, 3.0] Coefficient = 1.0 + 0.1 × ( Σ − 5 )   Σ = D1+…+D5 ∈ [5, 25] → coefficient ∈ [1.0, 3.0]
L1
基础自动化Basic automation 单点文本生成 / 查询 / 格式化single-point text gen / query / formatting
Σ 5–8 · 1.0–1.3
L2
标准增强Standard augmentation 模板拼装 + 参数库 + 一致性校验template assembly + param library + consistency checks
Σ 9–12 · 1.4–1.7
L3
复合编排Composite orchestration 多步骤 + 多源 + 多模态编排multi-step + multi-source + multimodal
Σ 13–16 · 1.8–2.1
L4
专家级Expert-grade 高风险判断 + 隐性知识 + 专家在环high-stakes judgment + tacit knowledge + human-in-loop
Σ 17–20 · 2.2–2.5
L5
前沿 / 研究级Frontier / research 生成式工程 / 科研边界generative engineering / research frontier
Σ 21–25 · 2.6–3.0

评估方:Opus 4.8。系数为按统一标准给出的工程难度刻度,非对客户行业的价值评判;同一模块在不同企业的数据就绪度(D3)不同,系数会相应微调。Assessed by Opus 4.8. The coefficient is an engineering-difficulty scale on a unified standard, not a value judgment on the industry; the same module's data readiness (D3) varies by company, so the coefficient is fine-tuned accordingly.

系数实例 · 8 个真实业务场景Worked examples · 8 real scenarios

标准落于真实业务场景The standard, applied to real scenarios

下表按统一标准给出 8 个场景的难度系数与实际零售单价(基础单价 ¥6,000/人·天)。每个场景的五维打分与"AI 到底做什么"见表下卡片。Below are 8 scenarios scored on the same standard, with retail day rates (base ¥6,000/person·day). Each scenario's 5-dimension scores and "what the AI actually does" are in the cards underneath.

业务场景Scenario 行业Industry 难度 ΣΣ 分级Tier 系数Coef. 实际零售单价 / 人·天Retail / person·day
美国外观专利附图审查报告US design-patent drawing review涉外知识产权Foreign IP15L32.0¥12,000
专利查新检索报告Patent prior-art search report知识产权IP18L42.3¥13,800
方案设计文档自动化Solution-design doc automation工业装备Industrial equip.11L21.6¥9,600
方案 / 报价文档自动化Proposal / quote doc automation工业装备Industrial equip.13L31.8¥10,800
获客与市场情报Lead-gen & market intel工业装备Industrial equip.16L32.1¥12,600
销售助理 BotSales-assistant bot工业装备Industrial equip.14L31.9¥11,400
知识标准化与销售赋能培训Knowledge standardization & enablement工业装备Industrial equip.19L42.4¥14,400
技术研发 + CAD / 3D 生成R&D + CAD / 3D generation工业装备Industrial equip.23L52.8¥16,800
知识产权 · 专业服务Intellectual property · professional services

美国外观专利附图审查报告US design-patent drawing review

2.0L3

智能体读取外观专利附图(多模态视觉),对照 USPTO 制图规范(37 CFR 1.84 / MPEP 1503)逐项审查——视图齐全性、虚实线、剖面线与阴影、各视图一致性、附图编号——产出"问题清单 + 整改建议"审查报告,供代理师复核。The agent reads the design-patent drawings (multimodal vision) and checks them against USPTO drawing rules (37 CFR 1.84 / MPEP 1503) — view completeness, solid/broken lines, shading, cross-view consistency, figure numbering — producing an "issue list + fixes" review report for the attorney.

D1·D2·D3·D4·D5 = 3·3·4·3·2 → Σ 15 · 多模态视觉 + 规范判断 + 代理师复核 · multimodal + rule judgment + attorney review

专利查新检索报告Patent prior-art search report

2.3L4

输入技术交底书,跨 USPTO / EPO / Google Patents / CNIPA 四通道做 28 轮递进检索,产出检索要素表、技术特征对比矩阵、X-Y-A 文献分类与创造性评述(对标智慧芽 PatSnap)。多源编排叠加新颖性 / 创造性的法律判断,高风险。From a disclosure, run 28 progressive search rounds across USPTO / EPO / Google Patents / CNIPA, producing a feature table, comparison matrix, X-Y-A classification and inventiveness commentary (a PatSnap-class report). Multi-source orchestration plus novelty/inventiveness legal judgment — high stakes.

D1·D2·D3·D4·D5 = 4·4·3·4·3 → Σ 18 · 多源检索 + 法律判断高风险 · multi-source + high-stakes legal judgment
工业装备 · 非标定制(以膜分离 / 流体设备为例)Industrial equipment · custom (membrane / fluid systems)

① 方案设计文档自动化① Solution-design doc automation

1.6L2

设备模块化组合、工艺已定型,从配置参数 + 组件功能库自动拼装设计 / 开发 / 操作文档初稿,助理从"照旧版逐字改"变成"审核 AI 初稿"。范本现成、参数化拼装,最容易起步。Equipment is modular and the process is fixed; assemble design / dev / operation doc drafts from config parameters + a component-function library, turning "edit the old version line by line" into "review the AI draft." Templates ready, parametric — the easiest start.

D1·D2·D3·D4·D5 = 2·2·3·2·2 → Σ 11 · 参数化拼装、范本现成 · parametric, templates ready

② 方案 / 报价文档自动化② Proposal / quote doc automation

1.8L3

一个谈判周期产生 6+ 版方案,自动同步价格 / 配置 / 文本三处,并做全文一致性校验,消灭"改了以为改了、隐患到合同执行才暴露"。跨文档一致性逻辑 + 报价勾稽。A negotiation cycle spawns 6+ versions; auto-sync price / config / text across all three and run a full-document consistency check, killing the "thought I changed it" risk that surfaces only at contract time. Cross-doc consistency + quote reconciliation.

D1·D2·D3·D4·D5 = 3·2·3·3·2 → Σ 13 · 一致性校验 + 报价勾稽 · consistency + quote reconciliation

③ 获客与市场情报③ Lead-gen & market intelligence

2.1L3

从已成功案例横向发散找同行(做通一家→系统找到同行业另 9 家)、显性企业背调 + 隐性需求挖掘(从生产环节反推需求)+ 细分市场报告。多源爬虫 / API,叠加隐性推理与销售背书。From a won case, fan out to peers (win one → systematically find 9 more in the industry), explicit company due diligence + implicit-need mining (infer needs from production), plus niche market reports. Multi-source scraping/API, plus implicit reasoning and sales validation.

D1·D2·D3·D4·D5 = 3·3·4·3·3 → Σ 16 · 多源情报 + 隐性需求推理 · multi-source + implicit-need reasoning

④ 销售助理 Bot④ Sales-assistant bot

1.9L3

拜访前情报包、拜访后录音转写挖需求、拜访中实时专业问答、新人陪练。多模态(音频)+ 实时检索;输出为建议性、低风险,所以校验维度(D4)较低。Pre-visit briefs, post-visit audio transcription to mine needs, in-visit real-time expert Q&A, and rookie role-play. Multimodal (audio) + live retrieval; output is advisory and low-stakes, so D4 is low.

D1·D2·D3·D4·D5 = 3·3·3·2·3 → Σ 14 · 多模态音频 + 实时问答 · multimodal audio + live Q&A

⑤ 知识标准化与销售赋能培训⑤ Knowledge standardization & enablement

2.4L4

27 年 / 400+ 工艺的隐性经验,沉淀为按细分行业的"标准产品 + 竞争优势 + 价格策略"知识卡片库 + 培训 Bot。知识高度隐性(D2=5)、需创始人逐项审核在环,ROI 最高、门槛也最高。Distil 27 years / 400+ processes of tacit experience into per-niche "standard product + edge + pricing" knowledge cards + a training bot. Knowledge is highly tacit (D2=5) and needs founder sign-off in the loop — highest ROI, highest bar.

D1·D2·D3·D4·D5 = 4·5·4·4·2 → Σ 19 · 隐性知识 + 创始人在环 · tacit knowledge + founder in-loop

⑥ 技术研发 + CAD / 3D 生成⑥ R&D + CAD / 3D generation

2.8L5

对接 CAD 内核(CadQuery 类)做参数化建模 / 图纸校验,乃至高分子 / 分子设计(AlphaFold 类)的情报跟踪。生成式工程 + 物理正确性难校验(D4=5)+ 深度系统耦合(D5=5),前沿 / 研究级,先做可行性评估不前期承诺交付。Drive a CAD kernel (CadQuery-class) for parametric modeling / drawing checks, up to polymer / molecular-design (AlphaFold-class) intel tracking. Generative engineering + hard-to-verify physical correctness (D4=5) + deep coupling (D5=5) — frontier; we scope feasibility first, no upfront delivery promise.

D1·D2·D3·D4·D5 = 5·4·4·5·5 → Σ 23 · 生成式工程 + 深度耦合 · generative engineering + deep coupling
边界与红线Boundaries & red lines

AI 出草稿,人定稿AI drafts, humans decide

高风险环节专家把关Experts gate high-stakes steps

凡涉及法律判断、新颖性 / 创造性认定、答复定稿、合同与报价定价——AI 只做信息梳理与检查清单,结论由代理师 / 工程师 / 管理者判定。For legal judgment, novelty/inventiveness calls, final responses, contracts and pricing — AI only organizes information and builds checklists; the conclusion is the professional's call.

数据不出企业Data stays in-house

FDE 在客户本机 / 内网驻场开发,交底书、案件材料、图纸全程私有化处理,符合工业与专业服务的安全底线。The FDE develops on the customer's own machine / intranet; disclosures, case files and drawings are handled privately throughout — meeting industrial and professional-services security bars.

由小及大,稳健推进Start small, scale steadily

先以一个低系数、高确定性的模块完成验证、建立信任,再逐步推进至高系数模块;系数与人天随真实材料复核,不一次性承诺覆盖全部六个场景。Validate and build trust with a low-coefficient, high-certainty module first, then progress to higher-coefficient ones; coefficient and person-days are re-checked against real materials — no commitment to cover all six scenarios at once.

说明:基础单价 ¥6,000/人·天为难度系数 1.0 的基准;实际零售单价 = 基础单价 × 难度系数。难度系数与预估人天均由 Opus 4.8 按本页 ADC 标准评估,正式报价以双方签署的方案与报价单为准。CCBots 席位、企业知识库(数据底座)、各部门技能库培训分别另见 报价解决方案Note: the ¥6,000/person·day base is the coefficient-1.0 benchmark; retail day rate = base × coefficient. Both coefficient and estimated person-days are assessed by Opus 4.8 on this page's ADC standard; the signed proposal and quotation prevail. CCBots seats, the enterprise KB (data foundation) and department skill-library training are covered under Pricing and Services.
咨询Contact

聚焦贵公司最关键、最不容差错的流程Focus on your most critical, error-intolerant process

我们将先按 ADC 标准提供难度系数与人天估算,再确定驻场方案与报价。We'll first provide a difficulty-coefficient and person-day estimate on the ADC standard, then finalize the on-site plan and quotation.

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