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Graviti

GRTraining data for Physical AI & LLMs

Real-world data for machines that learn.

Graviti captures, annotates and licenses production-grade datasets for humanoids, robots and large language models — with consent and provenance built into every record.

Real-world capture

  • Egocentric video
  • Multi-view video
  • Stereo + IMU
  • Camera calibration
  • Action segments
  • Body keypoints
  • Custom collection
  • LLM data programs

01Flagship dataset

Ego-Exo Workplace Tasks. Synchronized first-person and multi-view video of real work in factories, hotels and offices.

SESSION 0412 · 30 FPSEGO + 3 EXO · SYNCEDEGOEXO 1EXO 2EXO 3CAM1CAM2CAM33D · 17 KEYPOINTS · TRIANGULATED00:00:02Pick up circuit board00:00:04Carry board to the shelf00:00:07Place board in the bin00:00:12Pick up circuit board
GR-EGO-02Available

Real workers doing their real jobs — small-part assembly and packaging on factory floors, housekeeping in hotel rooms, tidying and cleaning in offices and reception areas — recorded by a head-mounted camera and three fixed cameras at the same time. Sessions are synchronized and calibrated. Annotators describe each action in free text with timestamps, and a pose model estimates body keypoints; raw footage can also be licensed without annotations.

Hours of video
4,300+
Synchronized views
4
Frame rate
30 fps
Hours per participant
≤ 10

02Real work, recorded in sync

Recorded where the work actually happens.

We don't stage data in labs. Real workers record their own jobs — on factory floors, in hotel rooms and offices — with a head-mounted camera and fixed cameras running in sync, so your models learn from the tasks they will meet in deployment.

4,300+Hours of real work
4Synchronized views
30 fpsEvery camera
≤ 10 hPer participant

03Catalog

Datasets you can license today.

Off-the-shelf datasets for Physical AI and LLMs, each with a public specification and an evaluation sample.

Large language models

For reasoning, alignment and agents.

TRAIN/PART-0000.JSONL · L 18,204DOMAIN · PHYSICS{"domain": "physics/statistical-mechanics""difficulty": 4"prompt": "A gas of N indistinguishable bosons…""reasoning": ["Step 1: Write the grand partition function…""Step 2: Take the thermodynamic limit…""Step 3: Solve for the critical temperature…"],"answer": "T_c = 2πħ²/mk_B (n/ζ(3/2))^(2/3)""verified_by": "expert:2f91"}
GR-LLM-01 · LLMEarly access

Expert STEM Problems

Original research-level science problems with expert-written solutions.

Subjects
4
Level
Research
View spec
PAIR 118,402 · TURN 3 / 4κ = 0.78RESPONSE AHELPFULHONESTHARMLESSRESPONSE BCHOSENHELPFULHONESTHARMLESSRATIONALE: B STATES ITS ASSUMPTIONS AND CORRECTLY FLAGS THE EDGE CASE.
GR-LLM-02 · LLMAvailable

Human Preference Pairs

Pairwise and graded comparisons for RLHF, DPO and reward modeling.

Comparisons
400,000+
Avg. turns
4.2
View spec
TRAJ 22,019 · 23 STEPSENV · SPREADSHEET + REST01OBSERVESpreadsheet 'Q3 vendors.xlsx' opened02THINKNeed totals grouped by vendor03ACTinsert_pivot(range='A1:F412')04RESULTPivot table created on Sheet205ACThttp.post('/api/report', …)06RESULT201 Created · report_id=88f2OUTCOME · SUCCESS
GR-LLM-03 · LLMEarly access

Agentic Coding Environments

Containerized software and tool-use tasks with automated verifiers.

Task format
Harbor
Verification
Automated
View spec
TRAIN/PART-0000.JSONL · L 18,204DOMAIN · PHYSICS{"domain": "physics/statistical-mechanics""difficulty": 4"prompt": "A gas of N indistinguishable bosons…""reasoning": ["Step 1: Write the grand partition function…""Step 2: Take the thermodynamic limit…""Step 3: Solve for the critical temperature…"],"answer": "T_c = 2πħ²/mk_B (n/ζ(3/2))^(2/3)""verified_by": "expert:2f91"}
GR-LLM-04 · LLMEarly access

Professional Work Tasks

Expert-graded finance, legal and office tasks with real deliverables.

Domains
Finance · Law · Office
Deliverables
XLSX · DOCX · PPTX
View spec

04How we build data

From the real world to your training run.

One accountable pipeline, from capture hardware to delivered shards. The same pipeline powers our catalog and custom programs.

  1. 01

    Capture

    A vetted global network of contributors, operators and domain experts records data on calibrated devices — in homes, workplaces and labs.

    Head-mounted cameras · teleop rigs · expert authors

  2. 02

    Annotate

    Trained annotators and model-assisted tooling add action segments, body and hand keypoints, language, preferences and rationales.

    Hand pose · actions · narration · rubrics

  3. 03

    Verify

    Multi-pass human review, automated checks and contamination screens. Every batch ships with measured quality metrics.

    Two-pass QA · agreement metrics · audits

  4. 04

    Deliver

    Clean rights and provenance, delivered in the formats your training stack already reads — to your bucket, on your schedule.

    LeRobot · RLDS · WebDataset · Parquet · JSONL

05Delivery

Ready for your stack on day one.

Standard formats, documented schemas and data cards. Delivered to S3, GCS, Azure or Hugging Face — no conversion scripts required.

  • MP4
  • YAML
  • JSON
  • Parquet
  • LeRobot on request
GR-EGO-02 · directory layout
ego-exo-workplace/            # indicative; final layout confirmed per delivery
├── manifest.csv
└── sessions/<scene>/<session_id>/
    ├── ego/
    ├── exo_cam1/
    ├── exo_cam2/
    ├── exo_cam3/
    ├── calibration.yaml
    ├── keypoints_2d.json
    ├── keypoints_3d.json
    ├── actions.json
    └── metadata.json

06Rights & compliance

Data you can actually ship a model on.

Clean rights are not an afterthought. Read how we license data on our company page.

  • Consent by design

    Every contributor signs a written, revocable agreement that explicitly covers AI training.

  • Provenance per record

    Each clip, episode or example traces back to its capture session, device and consent record.

  • Privacy protection

    Faces, screens and documents can be blurred before delivery; audio is only included when licensed.

  • Clear commercial license

    Perpetual rights to train and deploy models, with exclusive options for strategic partners.

07FAQ

Questions we hear most.

What is Graviti?

Graviti is a training data company that licenses datasets for Physical AI — including synchronized egocentric and multi-view video of people doing real work in factories, hotels and offices — and for large language models, and builds custom data programs for both.

What datasets does Graviti offer?

Physical AI: Ego-Exo Workplace Tasks (available), Egocentric Household Activities (available) and Bimanual Teleoperation Trajectories (early access). LLM: Expert STEM Problems (early access), Human Preference Pairs (available), Agentic Coding Environments (early access) and Professional Work Tasks (early access). Every catalog dataset has a public specification at graviti.com/datasets and an evaluation sample. Custom collection and LLM data programs are built to order.

Does Graviti provide training data for humanoid robots and robotics?

Yes. Graviti licenses synchronized first-person (egocentric) and multi-view video of real work — factory assembly and packaging, hotel housekeeping, office and reception tasks — with camera calibration, timestamped action segments and model-estimated body keypoints, alongside egocentric household video and robot teleoperation demonstrations. The data is used to pre-train vision-language-action (VLA) models and to train policies for humanoids and robot arms, and Graviti captures new data to order.

Does Graviti provide data for training large language models?

Yes. Graviti licenses original research-level STEM problems with expert-written solutions, containerized coding and tool-use environments with automated verifiers, and rubric-graded finance, legal and office tasks with reference deliverables. All three suit reinforcement learning and evaluation, and Graviti produces custom LLM data for the domains and languages you need.

Can I get a free sample before licensing a dataset?

Yes. Each dataset page has a sample request form. Samples are free and provided for internal evaluation only. Where a ready-made sample exists it is delivered as a download link after a short request with a work email address; otherwise the data team prepares a sample pack for your evaluation.

Get started

Tell us what your model needs to learn.

Share your target tasks, modalities and volume. We reply within one business day with matching datasets, samples and a quote.