具身智能数据采集与交付 — Tate · 把真实工作变成可训练、可验收的数据

为什么是现在Why now

模型的上限，是数据的上限。A model is only as good as its data.

具身智能这一轮的瓶颈，已经从算法转到数据。人形机器人、VLA、世界模型要学会在真实世界里干活，靠的不是更多互联网视频，也不是纯合成数据——而是真实工作现场里、第一视角、带动作语义的交互数据。This wave of embodied AI is bottlenecked on data, not algorithms. To work in the real world, humanoid robots, VLA and world models don't need more internet video or synthetic frames — they need first-person interaction data, captured in real work, with the action semantics intact.

我们的判断Where we stand

能采到，不等于能用。Captured isn't the same as usable.

真实世界数据，难的从来不是"拍到画面"，是"每一条都过得了验收"。行业忙着比谁采得多、覆盖多少场景；我们只认一件事——交出去的数据，能不能直接进训练，你能不能在自己机器上复核。采得多，不等于采得对。With real-world data, the hard part was never getting footage — it's making every clip pass acceptance. The field competes on volume and scene coverage; we hold to one test: can the data you receive go straight into training, and can you re-verify it yourself. More captured is not more usable.

数据在哪一步变成废的Where data goes bad

标准难转译Standards don't translate

客户给的是 Schema 和验收口径，现场需要的是能执行的 SOP。中间这一层没人做，采回来的东西就对不上要求。Clients hand over a schema and acceptance criteria; the field needs an executable SOP. Skip that layer and the footage won't match the spec.

设备链路不稳定The capture chain drifts

时间同步、帧率、编码、导出，任何一环出问题，整段素材就废。参数表写得好看，不等于连续录制时扛得住。Clock sync, frame rate, encoding, export — one weak link voids the clip. A good spec sheet is not the same as holding up under continuous recording.

真实场景难规模化Real scenes don't scale

授权、组织、一致性，比拍摄本身难得多。能拍一条，不代表能稳定拍一百条。Consent, organization and consistency are harder than filming. Shooting one clip says nothing about shooting a hundred consistently.

我们做什么What we do

从标准进场到验收出包，六个板块，一条线走完。From your standard coming in to an acceptance-ready package going out — six modules, one continuous line.

从 Schema 到 SOPschema → SOP

标准转译Standard translation

把客户的任务定义、字段规范与验收口径，翻译成采集现场能照做的操作手册。Turn task definitions, field specs and acceptance criteria into a manual the field crew can follow.

从点位到执行sites → execution

场景组织与合规Scene operations

真实场景的落实：任务真实性、拍摄许可、隐私授权、人员培训与现场纪律。Making real scenes work: task authenticity, filming permission, privacy consent, crew training and on-site discipline.

从参数到实测spec → measured

设备方案与实测Device solutions

以客户标准为起点做选型与实测：帧率、时间同步、连续录制稳定性，合格才入池；按任务需要做适配与改造。Selection and measurement driven by your standard: frame rate, clock sync, sustained recording — measured before a device enters the pool, and adapted when the task calls for it.

从试采到批量pilot → scale

采集执行与团队Capture operations

试采锁定 SOP，再上批量。采集团队按同一套手册培训、考核、复训，规模变大标准不变形。Lock the SOP on a pilot, then scale. Crews are trained, checked and retrained against one manual so the standard holds as volume grows.

从画面到语义frames → labels

数据标注Data annotation

按客户的标注规范执行：任务分段、关键帧、动作语义、成功与失败判定。自动预标打底，人工逐条复核，标注与数据同包交付、同一套校验。Executed against your labeling spec: task segmentation, key frames, action semantics, success/failure calls. Machine pre-labeling first, then per-item human review — labels ship in the same package under the same checks.

从原始数据到验收包raw → acceptance

数据工程与质检Data engineering & QC

拆流、转码、切分、质检、打包、校验——把原始 dump 变成能直接进验收的交付包。Demux, transcode, segment, QC, package and checksum — turning a raw dump into a delivery bundle ready for acceptance.

完整能力稿Capability deck

从标准到交付，
一份讲清楚的稿子。From standard to delivery,
laid out end to end.

下面是我们对外介绍稿的核心页——服务全景、交付物结构、设备与质量体系。想完整看或转发给同事，右下角可下载 PDF。Core pages from our deck — service map, delivery structure, device and quality systems. Download the PDF to read in full or forward internally.

封面Cover

我们是谁Who we are

客户缺的不是视频What clients lack

为什么由我们交付Why us

端到端服务全景End-to-end

数据产品与交付物Data products

设备选型Device selection

标准化采集 SOPCapture SOP

质量与合规体系Quality system

从一条样片开始Start with a sample

← 横向拖动查看全部 10 页 →← drag to see all 10 pages → 下载完整 PDF · 10 页Download full PDF · 10 pages ↓

质量怎么保证How quality holds

自动检测 + 人工复核 + 可复现报告——每一步都留痕，你可以在自己机器上重跑，结论不靠我们说了算。Automated checks, human review, reproducible reports — every step on record, re-runnable on your own machine. The verdict isn't ours to declare.

86项自动化测试 · 0 skipautomated tests · 0 skipped处理管线自有工程，每次改动全量跑过再交付Our own pipeline: the full suite runs before anything ships

第三方3rd-party攻击性审计 · 修复 5 项高危adversarial audit · 5 criticals fixed先写红测试再修到绿，缺陷与修复过程留痕可查Red test first, then fixed to green — every defect and fix is on record

随包交付Shipped with it可复现的验证脚本a reproducible verification script你在自己机器上重跑，同一套校验值Re-run it yourself against the same checksums

设备与现场纪律Devices & on-site discipline

设备以样例实测为准、不押单一厂商；现场只认画面本身，跟报的场景名称、任务名称无关。Devices settled by sample measurement, never a single-vendor bet; on site we judge the footage itself, not the label attached to it.

设备对象池Devices tracked

厂商已触达Vendors contacted

已用真实数据跑通我方管线Validated with real data on our pipeline

双手可见Hands in frame手长时间离画的片段直接作废Clips where hands leave frame too long are void

真实任务Real tasks摆拍、假装干活，出现即拒收Staged or pretend work is rejected on sight

拒绝空录No idle footage无效空耗、低价值重复不计入交付Idle time and low-value repetition don't count

授权在先Consent first第三方入镜须有书面授权Anyone else in frame needs written consent

从一条样片开始Start with one clip

样片验证Sample validation

1–3 条。用你的标准验证设备、场景与交付格式，双方先对齐"什么算合格"。1–3 clips. Validate device, scene and format against your standard, and agree on what "passing" means.

小批量 PilotSmall-batch pilot

锁定 SOP、质检规则与交付格式，把问题解决在批量生产之前。Lock the SOP, QC rules and delivery format — fix problems before volume production.

规模化交付Scaled delivery

稳定生产、持续抽检、按批出核验报告。Steady production, ongoing sampling, a verification report per batch.

凭什么是我们Why us

这门活的本质是「自动化处理 + 人工质检 + 多点位组织」。下面每一条都是已经交付过的同构系统，可以点开看。This work is automated processing plus human QC plus multi-site organization. Each item below is a shipped system with the same shape — all open to inspection.

Mission Bio · 迈申

临床试验的非结构化文档 → 抽取 → 结构化 → 人工终审，医疗合规场景下的数据处理闭环。与具身数据的交付结构完全同构。Clinical-trial documents: unstructured → extraction → structured → human final review, in a regulated medical setting. Structurally identical to embodied-data delivery.

电商生图工作台Batch image workbench

机器批量处理 + 人工逐条质检 + 成本可控的完整闭环，按合同交付客户的付费项目。质检管线的直接经验来源。Bulk machine processing, per-item human review and cost control in one loop — a paid project shipped under contract, and the direct source of our QC-pipeline experience.

连锁门店绩效系统Chain-store ops system · 运营背景ops background

从 0 组织运营 93 家线下点位及配套绩效核算系统。数据采集本质就是多点位、多团队的标准化组织问题——排班、培训、质量一致性、成本核算，是同一套东西。Built and ran 93 physical sites from zero, plus the performance system behind them. Data collection is the same multi-site organization problem: scheduling, training, consistency and unit-cost accounting.

聊聊你的数据需求Tell us what you need 把你的任务 Schema、验收标准，或者最头疼的数据质量问题发我，我先判断能不能做、怎么做最省事。Send your task schema, acceptance criteria, or the data-quality problem that hurts most — we'll tell you straight whether and how we can help.

zzttb2012@gmail.com

微信WeChat · missionbio

客户真正缺的
不是视频What teams lack
isn't footage

模型的上限，是数据的上限。A model is only as good as its data.

能采到，不等于能用。Captured isn't the same as usable.

数据在哪一步变成废的Where data goes bad