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Your model needs data that doesn't exist yet. We produce it.

Custom real-world data production for AI.

Kvet builds custom datasets around the requirements of specific models and research teams — from controlled visual production and global data collection to multimodal capture and Physical AI.

Discuss a dataset

Core capabilities

Four core areas of custom data production for training, post-training and evaluation.

  1. /01

    Visual & Generative AI

    Custom image and video datasets for training, post-training and evaluation — spanning controlled visual production, human actions and interactions, video data for generative AI, creative workflows, 3D, graphics and VFX.

    • Custom Image Data
    • Video Data for Generative AI
    • Human Actions & Interactions
    • Multi-view & Controlled Capture
    • Creative Workflow & Edit Trajectories
    • 3D, Graphics & VFX Production
  2. /02

    Human Activity & Real-World Interaction

    Everyday and professional tasks, human-object interaction and multi-person scenes, in controlled or natural settings.

    • Skilled tasks
    • Human-object interaction
    • Task sequences
    • Hands & body
    • Dialogue & groups
  3. /03

    Physical AI & Robotics

    Human demonstrations and multimodal real-world data for Physical AI and robotics — including egocentric and synchronized multi-camera capture, human-object interaction, object manipulation, tool use, RGB-D, motion and sensor data.

    • Egocentric / POV
    • Human-object interaction & manipulation
    • Tool use
    • Multi-camera & RGB-D
    • Motion & sensors
    • Sync & calibration
    • Failure & recovery
  4. /04

    Data Collection & Production at Scale

    One consistent specification, scaled from pilot to full production across contributors, teams and countries.

    • Controlled production
    • Distributed collection
    • Multi-country
    • Releases & rights
    • Metadata & QA

What we do

Every project starts with a specific data requirement. We build the right production and collection approach around it.

  • Controlled Production

    We build the environment, participants, actions, objects, capture setup and protocol around the requirements of the project.

    • Sets & locations
    • Participants
    • Actions & objects
    • Capture setup
    • Protocol

  • Sourcing & Licensing

    We find and license existing content when that is faster and more cost-effective than producing it from scratch.

    • Existing content
    • Licensing
    • Rights clearance
    • Metadata

  • Distributed Collection

    Contributors and local teams collect data in their own places when geography, diversity, scale or duration matter most.

    • Contributors
    • Local teams
    • Geography
    • Diversity
    • Long-term capture

Data we produce

Real-world, visual and multimodal datasets built around specific model and research requirements.

  • Controlled Image & Video Data

    People, objects, environments and activities captured under controlled variations of viewpoint, lighting, motion, setting and scenario.

    ImageVideoMulti-viewControlled variations

  • Human Actions & Interactions

    Structured visual data covering everyday activities, professional workflows, human-object interaction, tool use and multi-step actions.

    ActionsInteractionsWorkflowsTool use

  • Video Data for Generative AI

    Purpose-built video data covering motion, human actions and interactions, continuity, camera movement and controlled visual variation.

    MotionContinuityCamera variationHuman interaction

  • Creative Workflow & Edit Trajectories

    Source assets, instructions, editing actions, project data, intermediate versions, metadata and final outputs captured as a structured creative workflow.

    EditingProject dataMetadataDecision traces

  • Egocentric & Multimodal Activity Data

    First-person and synchronized multi-camera data for real-world tasks, with RGB-D, motion and sensor modalities where required.

    POVMulti-cameraRGB-DSensors

  • 3D, Graphics & VFX Data Production

    Standalone or integrated 3D, graphics, animation and VFX data projects, including compositing, controlled transformations and synthetic assets.

    3DGraphicsAnimationVFX

Creative Workflow & Edit Trajectories

Datasets that capture the creative process from source assets and instructions through editing actions, project data, intermediate versions, metadata and final outputs.

Example trajectory

  1. 01Source Assetsoriginal files
  2. 02Instruction“Relight the scene as golden hour, remove the object on the left”
  3. 03Editing Actionsselect · remove · relight · refine
  4. 04Project Dataproject file, layers, parameters
  5. 05Intermediate Versionsv1 → v2 → v3
  6. 06Final Outputfinal asset + metadata
A person working at a laptop and monitor in a dimly lit room with bookshelves behind

Production infrastructure

Global production, one dataset specification.

  1. People

    Participants, skilled professionals and contributors, with signed releases.

  2. Locations & environments

    Homes, workplaces, studios and outdoor sites matched to the scenario.

  3. Equipment & capture systems

    POV rigs, multi-camera arrays, RGB-D and sensor setups built for the protocol.

  4. Post-production, 3D & VFX

    Editing, creative workflows, graphics, 3D and VFX production — delivered as standalone data projects or integrated into larger dataset pipelines.

  5. International teams

    Local production teams and contributor networks working to a consistent specification across countries and regions.

Our process

  1. 01

    Requirements

    Define the model task, target behaviors, constraints and success criteria.

  2. 02

    Specification

    Translate project requirements into scenarios, capture parameters, metadata structure, deliverables and QA criteria.

  3. 03

    Pilot

    Produce a small sample batch, review it with your team, and lock the spec before scaling up.

  4. 04

    Production

    Produce, collect or source the data with the required metadata, rights and releases in place.

  5. 05

    QA

    Review samples, fix inconsistencies, and validate metadata, structure and annotations where required.

  6. 06

    Delivery

    Hand over a clean, documented, rights-ready dataset in your preferred format.

  7. 07

    Scale

    Grow volume, locations and variations on the same pipeline as your model needs more data.

Tell us what data your model needs.

Why Kvet

  1. Built around your requirements

    Every project is built around the specific data, environments, actions and capture conditions required.

  2. Production-first

    We organize the participants, environments, interactions and capture setups required to produce data that does not already exist.

  3. Multiple production models

    Controlled production, distributed collection and content sourcing can be used independently or combined within one project.

  4. Visual and technical depth

    Image and video production, egocentric and multi-camera capture, RGB-D, creative workflows, 3D, VFX and multimodal data within one production ecosystem.

  5. From pilot to scale

    Validate the approach with a focused pilot, then scale across participants, locations and countries.

  6. Structured delivery

    Rights, releases, metadata, QA and technical requirements are integrated into the production pipeline.

FAQ

How do you scope and price custom data projects?

Each project is scoped individually, based on data requirements, capture complexity, participants, locations, modalities, volume and delivery specifications. We start by reviewing your requirements and defining the most efficient production approach.

What is the typical pilot size and timeline?

It depends on the type of data and the capture setup. We usually recommend a focused, reviewable batch that validates the capture protocol, metadata and quality requirements before production scales.

What delivery formats do you support?

Formats and metadata schemas follow your project requirements: standard image and video formats, structured metadata such as CSV or JSON, and cloud-based delivery. Other formats can be supported when the project needs them.

How do you handle participant consent and releases?

Consent and usage rights are built into the production workflow. For projects involving identifiable people, we collect the appropriate releases and organize documentation according to the agreed requirements and intended data use.

Who owns the data and IP after delivery?

Ownership and licensing terms are agreed for each project before production begins — for example work-for-hire, exclusive licensing or another agreed structure.

Can you work under NDA and in specific countries?

Yes. We work under NDA and organize production across countries through local production teams and contributor networks. Geographic availability depends on project requirements, local regulations and capture conditions.