FOR AI LABS

Training data from inside real companies.

Licensed, de-identified data from 100+ companies. For pre-training, SFT, RL and evals. Work data, long-form video, screen recordings and audio, linked in time order.

+companies supplying data
4training stages: pre‑training, SFT, RL and evals
2ways we source: licensed archives and paid capture
co_0217 · thread th_88f1 · 11 to 29 Mar 2024ONE PROJECT · FIVE TOOLS
MEETING 11 MARScope agreed
PERSON_14PERSON_22
transcript · 38 min
CHAT 12 MARPricing thread
PERSON_14
23 replies
DOCS 15 MARSpec v3
PERSON_22
41 edits
CODE 22 MARFix merged
PERSON_22
pr_5531 · 2 reviews
CRM 29 MARDeal won
PERSON_14CLIENT_3
deal_0412
Illustrative record. PERSON_14 is the same person in every tool.
Every stage of training

From pre-training to evals.

The same company data, shaped for the stage you are working on.

PRE-TRAINING · MID-TRAINING

Domain corpora

Years of real business writing, code and calls. Tokens the open web never had.

tokens · documents · threads
SFT · PREFERENCE

Expert demonstrations

How professionals really wrote the reply, fixed the bug or closed the ticket. With what happened next.

prompt · response · outcome
REINFORCEMENT LEARNING

RL environments

Replayable workspaces built from real company records, with tasks you can check.

state · action · reward
EVALS · BENCHMARKS

Held-out evals

Private tasks that were never online, so scores stay free of contamination.

task · rubric · answer key
Datasets

Browse what we can deliver.

Every dataset is built from licensed company data, de-identified and documented. Samples are available under NDA.

Work data

Cross-tool work threads

Email, chat, docs, tasks and CRM from one team, joined by person and project.

INCLUDESThread IDs, stable pseudonyms, timestamps, outcomes
JSONL · ParquetRequest a sample →
Work data

Customer support conversations

Tickets and live chats from first message to resolution.

INCLUDESIntent, resolution, handoffs, satisfaction
Work data

Sales cycles

CRM stages, emails and call notes from first touch to close.

INCLUDESStage history, deal outcome, linked emails
JSONL · ParquetRequest a sample →
Work data

Engineering work

Repositories, pull requests, reviews, linked tickets and incidents.

INCLUDESDiffs, review threads, issue links
Git bundles · JSONLRequest a sample →
Work dataAudio

Meetings and decisions

Meeting recordings and transcripts, with the follow-ups they triggered.

INCLUDESSpeaker turns, action items, linked tasks
Work data

Finance and operations

ERP orders, invoices and approvals, with the emails around them.

INCLUDESApproval chains, amounts bucketed, document links
Parquet · PDFRequest a sample →
Video

First-person work video

Head and chest camera footage of people doing hands-on tasks at work.

INCLUDESHand pose, objects, action segments
Video

Warehouse and factory CCTV

Multi-camera footage of real operations, shifts and incidents.

INCLUDESBoxes, tracks, event labels
Video

Long-form task video

Hours of continuous footage of real jobs, segmented into steps with start and end times.

INCLUDESStep boundaries, dense captions, temporal QA
Work dataVideo

Screen recordings of real work

People completing real tasks in real software, recorded with every action.

INCLUDESClicks, keystrokes, screens, task outcome
Audio

Call center audio

Channel-separated customer calls in many languages, with transcripts.

INCLUDESSpeaker labels, language, intent, outcome
RoboticsVideo

Robot teleoperation

Teleoperation sessions with joint states, actions and camera streams.

INCLUDESSynced streams, task success, episodes
3D and CAD

Building projects

CAD and BIM revisions, site scans and the project email around them.

INCLUDESRevision history, element types, point clouds
IFC · DWG · LASRequest a sample →
TO YOUR SPEC

Need something else?

Tell us the modality, industry and volume. We source it from licensed archives, or pay companies to capture it.

Custom briefSend a spec →

Volumes vary by dataset. We share a manifest with record counts, date ranges and audit results before you commit.

The part of work the web never saw.

Public text shows what people publish. Our data shows how teams plan, argue, decide and deliver over months.

PRIVATE

Never on the open web

Never published or crawled.

LINKED

Joined across tools

One ID per person, in every tool.

LONG

Years of history

Projects, teams and tools as they change.

MESSY

As untidy as real work

Typos, reversals and side chats left in.

MULTIMODAL AND PHYSICAL AI

Real-world data for robots and multimodal models.

Video, audio, screen and 3D, captured in real workplaces. Synced, de-identified and labeled to your spec.

Teleoperation

DELIVERED ASMCAP · MP4 · joint states, actions

First-person video

DELIVERED ASMP4 · JSON · hand pose, action segments

CCTV video

DELIVERED ASMP4 · JSON · boxes, tracks, events

Long-form task video

DELIVERED ASMP4 · JSON · step segments, timestamps

Screen recordings

DELIVERED ASMP4 · JSONL · clicks, keys, app state

Audio and speech

DELIVERED ASWAV · JSONL · speaker turns, transcripts

3D scans

DELIVERED ASLAS · IFC · point clouds, revisions

Inspection images

DELIVERED ASJPG · JSON · labels, defect classes
SYNCED STREAMSVideo, audio and screen on one clock.
LABELS ON REQUESTBoxes, pose, depth, segmentation, transcripts.
DE-IDENTIFIEDFaces and plates blurred. Names removed from audio and transcripts.
CONSENT ON RECORDEvery file traced to a signed license.
Temporal video understanding

Video that runs until the job is done.

Most video datasets are short clips. Real work takes hours. We deliver full recordings, with every step marked in time.

job_0412 · HVAC service · 2h 00m · 1 camera, head-mounted7 STEPS
  1. Set up0:00 to 0:11
  2. Take apart0:11 to 0:37
  3. Inspect0:37 to 1:02
  4. Replace filter1:02 to 1:16
  5. Reassemble1:16 to 1:41
  6. Test1:41 to 1:53
  7. Clean up1:53 to 2:00
QUESTION

When did the technician replace the filter, and what did they check first?

ANSWER

01:02:24 to 01:15:36. The pressure gauge, at 00:41:10.

Illustrative. Answers need the whole video, not one frame.
Full-length recordingsEach task runs from first step to last.
Steps in timeStart and end of every step, with captions.
Questions about timeBefore, after, how long, what changed.
PROCESS

Six stages from workspace to dataset.

Every record keeps its stage history, so you can trace any line back to its license.

  1. 01 SOURCE

    Verified companies

    → company_id
  2. 02 LICENSE

    Signed by the owner

    → license_id
  3. 03 EXTRACT

    Read-only export

    → raw, encrypted
  4. 04 DE-IDENTIFY

    Stable pseudonyms

    → person_id
  5. 05 LINK

    Cross-tool threads

    → thread_id
  6. 06 QA AND DELIVER

    Audited release

    → release, audit_log
Data spec

What one company package contains.

Before you commit, you get a manifest: sources, counts, dates and audit results.

SourceObjectsLinked by
emailMessages, threads, calendar eventsthread_id, person_id
docsDocs, sheets, decks, wiki pages, edit historydoc_id, person_id
chatChannels, threads, replies, shared filesthread_id, person_id
meetingsTranscripts, notes, attendee listsmeeting_id, person_id
crmAccounts, deals, stage history, activityaccount_id, deal_id
supportTickets, conversations, resolutionsticket_id, account_id
tasksIssues, sprints, status changesissue_id, project_id
erpOrders, inventory, invoices, approvalsorder_id, account_id
codeCommits, pull requests, reviewsrepo_id, pr_id
designCAD and BIM drawings, design files, revisionsproject_id
mediaVideo, audio and images, with transcripts and metadataasset_id, person_id
roboticsRobot logs and teleoperation streamsdevice_id, asset_id

All IDs are pseudonymous and consistent within a company.

record.jsonlschema v0.3
{
  "company": "co_0217",
  "source": "chat",
  "thread": "th_88f1",
  "ts": "2024-03-11T09:42:10Z",
  "author": "PERSON_14",
  "text": "[PERSON_22] can you push the fix
           for [CLIENT_3] before the demo?",
  "links": [
    {"source": "code", "pr": "pr_5531"},
    {"source": "tasks", "issue": "iss_1190"}
  ],
  "redactions": ["person", "client"]
}
Records per sourceExample

Sources this company used. 140 people, 6 years. Log scale.

Email
2.1M
Chat
1.4M
Documents
88K
Tasks
52K
Support
31K
Code
14K
CRM
9K
Meetings
3.2K
1K10K100K1M10M
Years covered per sourceExample

Same company. Tools were adopted at different times.

Email
Chat
Documents
Tasks
Support
Code
CRM
Meetings
2019202020212022202320242025
De-identification

We remove the people and keep the structure.

We replace identifiers with stable codes, so you lose the names and keep who talked to whom, about what, and when.

RAW · NEVER LEAVES OUR SYSTEMS
From: priya.n@northwind.io
To: john@acme.com
"Hi John, the Acme renewal
is attached. Call me on
+91 98200 41177 if the 12%
discount needs sign-off
from Rahul."
DELIVERED
From: PERSON_14
To: CLIENT_PERSON_203 (CLIENT_3)
"Hi CLIENT_PERSON_203,
the CLIENT_3 renewal
is attached. Call me on
PHONE if the 12%
discount needs sign-off
from PERSON_22."
  • Names, emails, phone numbers and handles become stable codes
  • Client and customer names become stable codes
  • Passwords, keys, tokens, card and ID numbers are deleted
  • Photos and profile images are removed
  • Every lab signs a no re-identification clause
  • Each release ships with its PII audit results
How buying works

From sample to delivery in three steps.

One contact, one contract. Scoped to what you are training.

01

Request a sample

Tell us the sources, industries and modalities you need. We share samples and a manifest under NDA.

Samples · manifest · audit log
02

Scope and license

We agree volumes, date ranges and labels, then sign one license covering every company in the order.

One license · consent on record
03

Receive data

Delivered to your cloud bucket in documented formats, with release notes and PII audit results.

JSONL · Parquet · MP4 · MCAP
FAQ

Questions labs ask us.

Want the full schema?Request the schema →
01Where does the data come from?

From companies that own it and have signed a license with us. They range from 20-person startups to enterprises, across software, services, manufacturing, finance and more. Some are running, some have closed.

02How do you know you have the right to sell it?

We check company identity and ownership, review each tool's terms and the seller's client contracts, and get a signed license before any export. Data that cannot be shared is excluded at source.

03How is personal information removed?

Automated detection, then human review. Identifiers become stable pseudonyms so cross-tool structure survives. Each release ships with sampled audit results, and you sign a no re-identification clause.

04Can you source to a spec?

Yes. Tell us the industries, company sizes, regions, tools and date ranges you need. We source against that brief.

05What formats and delivery do you support?

JSONL or Parquet with a documented schema, delivered to your cloud bucket. Raw files such as PDFs, drawings and recordings come with metadata in the same schema.

06Can we see data before we buy?

Yes. We share one de-identified company under NDA, with its manifest and audit log.

07Can you source video or robotics data to a spec?

Yes. We license existing footage and logs from our sellers, and can run paid capture with their teams for first-person video, teleoperation and site recordings.

REQUEST A SAMPLE

See one company, end to end.

Under NDA, with its manifest and audit log.