The private workspace for your AI training team.

Source experts, run them inside Worqgrid Studio, and pay them on-chain, for LLM evaluation, RLHF, red teaming, and multimodal labeling. Bring your own data or start from our curated datasets, and settle contributor payouts in tokens from Solana or Ethereum.

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For AI Labs

Bring your domain experts in-house and run LLM evaluation, RLHF, and red-teaming pipelines without leaking IP to a public marketplace.

For Labeling Vendors

Manage your annotator workforce on one platform with project routing, QA review queues, and direct on-chain payouts to your team.

For Enterprise AI Teams

Stand up a private talent pool for in-house labeling and evaluation work, and pay contractors directly in tokens from Solana or Ethereum.

All in one

Source, manage, and pay AI training talent, in one workflow

From scoping a project to shipping the labeled dataset and paying contributors, your team runs every step inside one private workspace.

Talent matching

Post your scope. Review only qualified matches.

Tell us your domain, languages, and labeling tasks. Worqgrid surfaces vetted experts who fit, usually within hours, not weeks. Screen async, run live trials, and approve only the people you want on the project.

12 qualified matches Medical NER · EN/ES
  • AM
    Aria M.
    RN · 6y clinical NER
    98% match
  • JL
    Javier L.
    MD · ES native
    94% match
  • PK
    Priya K.
    PharmD · 4y annotation
    91% match

Any pipeline

Plug Worqgrid into the tools you already run.

Stream labeled data into your training stack via API, drop it into S3 or GCS, or annotate inside the tools your team already uses. No platform migration required.

Connected pipelines 14 active
{ } REST & Webhooks
S3 S3 / GCS export
SF Snowflake
DB Databricks
LS Label Studio
HF HuggingFace

Built-in workspace

Chat, docs, and project tracking, all in one room.

Centralize team comms, share guidelines, and watch progress live without bolting on Slack, Notion, and Linear. Everything sits inside the project itself.

#medical-ner · live 3 online
JL
Javier L. · 2m
Confirmed ICD-10 mapping for span 12. Ready for review.
AM
Aria M. · 5m
Approved 8 batches today. QA queue is at 3.
PK
Priya K. · 12m
Updated guidelines doc posted to /shared.

Global payouts

Pay contributors directly. On-chain, in any country.

Settle payouts on-chain in tokens from Solana or Ethereum, on whatever cadence your team picks, per-batch, weekly, or at delivery. Contributors see exactly what was sent; no FX games, no banking middlemen.

Batch payout · Apr 28 Settled
  • AM
    Aria M.
    Solana
    $1,420.00
  • JL
    Javier L.
    Ethereum
    $985.00
  • PK
    Priya K.
    Solana
    $760.00
Total batch $3,165.00

Solutions

Vetted experts for any AI workload, every domain, every modality.

From post-training and reasoning verification to red-team probes, domain annotation, and multilingual evaluation, Worqgrid matches your project to experts trained for the exact task.

prompt · #4128
"Explain backprop to a 5-year-old."
Response A preferred
Response B ,

Post-training & alignment

SFT data, pairwise preference for DPO and RLHF, and harmlessness rubrics from calibrated reviewers, feeding directly into your model training loop.

✓ Step 1, define x ∈ ℤ
✓ Step 2, apply chain rule
✗ Step 3, off-by-one in iter 4
✓ Step 4, substitute & simplify

Reasoning & verification

Chain-of-thought annotation and step-level verification of math, logic, and code traces, graded by experts who can spot the error in step 3.

> probe: bio-uplift
  severity: high
  refused: true
> probe: prompt-injection
  severity: med
  refused: false

Red teaming & safety

Adversarial prompts, jailbreak probes, and policy-violation labeling from cleared specialists with backgrounds in security, biosafety, and CSAM detection.

verified specialists credentialed
  • Aria M. Cardiologist · 8y
  • Javier L. Patent attorney · 12y
  • Priya K. PharmD · 6y

Domain expert annotation

PhDs and credentialed professionals across medicine, law, finance, and engineering, for tasks where the right answer needs a real-world specialist.

eval suite · run #218
Model A0.84
Model B0.91
Model C0.62

Evaluation & benchmarking

Human-in-the-loop pairwise eval, custom benchmark scoring, and ongoing quality monitoring, so you can ship models with numbers you trust.

EN ES JA DE AR HI +54

Multilingual & multimodal

Native-speaker fluency across 60+ languages, with audio transcription, video event labeling, and image segmentation handled by the same vetted pool.

Top talent from leading research labs and institutions.

Polaris
Helix Labs
Northwave
Apex AI
Quanta
Meridian

LLM & Agents

Hire vetted domain experts to train and evaluate LLMs and agents, driving up reasoning quality, tool use, and reliability across your model lifecycle.

LLM Evaluation RLHF & Preference Data Reasoning Verification Hallucination Audits Tool Use & Function Calling Computer Use Agents Code Generation Review Multilingual Eval Red Teaming Agent Simulations Synthetic Data Curation RL Environments
View all LLM & agent solutions

Data Labeling

Hire trained annotators to label precise, consistent data across text, image, audio, video, and 3D, feeding straight into your training pipeline.

Document Annotation Image Classification Image Segmentation Video Annotation Audio Transcription Speech Labeling NER & Text Classification Time-Series Annotation Point Cloud / 3D Medical Imaging Satellite Imagery
View all data labeling solutions

Quality & vetting

Built around a vetted network of AI training experts

Every annotator on a Worqgrid project is screened through interviews, calibrated trial tasks, and continuous QA, so you only see experts qualified for your domain, language, and task.

8,000+
Pre-vetted experts
80+
Countries
50+
Languages
24+
Domain verticals

The Network

A talent network purpose-built for AI training, not crowd work.

Worqgrid surfaces professionals and graduate-level researchers your org can invite, vet against your own spec, and onboard onto a project.

  • Domain experts and credentialed pros, not anonymous crowd workers
  • Identity, NDA, and wallet checks completed at platform onboarding
  • On-chain reputation and payment history, portable across projects
  • Project-fit calibration runs on your rubric, owned by your team

Worqgrid Studio

The annotation studio, built into the platform.

Worqgrid Studio is the workspace where contributors actually do the work, text, image, audio, and video, with QA queues, guideline updates, and IAA tracking all in one place.

  • Annotators for text, image, audio, video, and 3D in one studio
  • Built-in QA review queues with approve, return, and dispute flow
  • Live IAA, accuracy, and progress dashboards for every contributor
  • Bring your own data, or start from a Worqgrid curated dataset

How it works

From scope to shipped dataset, in four steps.

Spin up a private workspace, invite your experts, run the project in Worqgrid Studio, and pay everyone on-chain, every step happens in one place.

Step 1

Post your scope. Reach 8,000+ vetted experts.

Define what you need, domain, languages, modality, tooling, and pay rate, in a guided wizard. The platform surfaces qualified matches across our network in hours, not weeks.

  • Guided scope wizard for domains, languages, modalities, and tools
  • Monthly subscription per org, no per-task or per-contributor markup
  • Reach experts across 80+ countries and 50+ languages
Post a project
New project
Draft
Domain
Medical
Specialization
Mathematics Physics +
Languages
English Mandarin Spanish
Annotation tool
Label Studio
# experts
8
Pay rate
$45 / hr

Monthly subscription · no per-task fees · no minimums

Screening · Math reasoning
28 in pipeline
  • EH
    Eli H.
    PhD math · 5y RLHF
    passed
    Interview
    ✓
    Trial task
    9.4 / 10
    IAA baseline
    0.87
  • SN
    Sara N.
    MS applied math
    trial in progress
  • RJ
    Riya J.
    BSc math · self-taught
    below cutoff

Step 2

Every candidate screened, tested, and calibrated.

Before anyone touches your data, they pass an interview, a trial task graded against your rubric, and an inter-annotator agreement check. You set the cutoff; we cycle out the rest.

  • Background interview with our talent team
  • Calibrated trial task scored against your QA rubric
  • IAA baseline locked in before production labeling starts
How vetting works

Step 3

Run the project. Watch QA in real time.

Live progress, per-contributor accuracy, and IAA tracked on a single dashboard. QA review queues, chat, guidelines, and dispute flow are built in, no bolted-on tooling.

  • Live progress, IAA, and per-contributor accuracy
  • QA review queues with approve / return / dispute
  • Built-in chat, docs, and live guideline updates
Tour the platform
Math reasoning · live
on track
Progress
68%
IAA
0.91
QA queue
12
Today's contributors
  • Eli H.
    0.94
  • Sara N.
    0.86
  • Dan T.
    0.79
Delivery · week 6
Settled
Examples shipped
14,820
Final IAA
0.93
Export pipelines
S3 · jsonl HuggingFace Webhook
Contributor payouts (8) $28,640
Settled on Solana & Ethereum

Step 4

Ship the dataset. Pay everyone in one click.

Stream labeled data into your training stack the moment a batch is approved, and settle contributor payouts on-chain. The org's monthly subscription is separate from contributor payouts, one ledger, both sides clean.

  • Stream into your stack via API, S3, GCS, or HuggingFace
  • Token payouts settled directly to contributors on Solana or Ethereum
  • Contributor payouts settle direct from your org, no per-task surcharge
See pricing

Built for scale. Designed for transparency.

The infrastructure connecting domain experts with the teams building AI.

The human data layer

One platform for sourcing, vetting, deploying, and paying the experts who train your AI.

Connecting domain experts with the teams building AI.

24+
Domains
Monthly.
Per organization. Transparent.
Get started
8K+
AI trainers & data labelers
AM JL PK EH SN +8K

Experts from

Polaris
Helix Labs
Northwave
Apex AI
Quanta
Meridian

The infrastructure for human data.

Get started

Stand up your AI training team in days, not quarters.

Spin up a private workspace, invite the experts you want, run them in Worqgrid Studio, and pay them on-chain, all on a single monthly subscription.

Self-Service

Post your scope. Invite the experts. Ship the data.

Your team owns the workflow end-to-end on Worqgrid, sourcing, vetting against your rubric, QA, and on-chain payouts. One monthly subscription, no per-task surcharges.

  • Discover, invite, and trial-task experts in your domain
  • Worqgrid Studio for text, image, audio, and video tasks
  • Bring your own data, or start from a Worqgrid curated set
  • On-chain contributor payouts in tokens from Solana or Ethereum
Start free trial Talk to sales
Project · Math reasoning 12 matches
  • EH
    Eli H.
    PhD math · 5y RLHF
    96%
  • SN
    Sara N.
    MS applied math
    93%
  • DT
    Dan T.
    Quant · IMO bronze
    90%
AM JL PK
Earn from training the next generation of AI models.
Freelance AI trainer? Apply to join the network.
Already running an annotation team?
Data labeling company? Bring your team to Worqgrid.

Integrations

Works with the tools your team already runs.

View all integrations
{ } REST API
S3 Amazon S3
SF Snowflake
DB Databricks
LS Label Studio
HF HuggingFace
GCS Google Cloud
CV CVAT
W&B Weights & Biases
WH Webhooks
AZ Azure Blob
SDK Python SDK

FAQ

Everything you need to know.

Common questions about running a project on Worqgrid.

How much does Worqgrid cost?
Worqgrid is billed as a monthly subscription to the organization, pricing scales with the size of your team and project volume. There's no per-contributor markup or per-task surcharge. Individual annotators don't pay anything; only the org carries the subscription.
Do I have to use Worqgrid's annotation software?
Worqgrid Studio is built into the platform, your annotators work directly inside it for text, image, audio, and video tasks, with QA queues, IAA tracking, and guideline updates all in the same workspace. No external annotation tool required.
How do you verify experts actually have domain expertise?
Vetting is owned by your organization, Worqgrid gives you the tooling, your team makes the calls. Invite candidates, run trial tasks against your rubric, score them, and lock an inter-annotator agreement (IAA) baseline before production starts. You set the cutoff and approve who gets onto the project.
Is Worqgrid self-service or managed?
Self-service. Your team runs the project end-to-end on Worqgrid, sourcing, vetting, QA, and delivery, using the platform's tooling and infrastructure. There's no managed-delivery service layer; the org owns the workflow.
Where does the data come from?
Either way works. Worqgrid provides curated datasets across common domains and modalities, or you can bring your own data, upload directly or stream it in via S3, GCS, or our API. Your org owns the labels and any derived dataset from the moment they're produced.
Can I scale from a small pilot to a full team?
Yes. Most projects start with a 5–10 expert pilot to lock in guidelines and IAA, then ramp into the dozens or hundreds once the rubric is settled. The same matching engine handles both, and the per-contributor cost stays the same as you grow.
How do contributor payouts actually work?
Contributors are paid in tokens from Solana or Ethereum, settled directly to their wallet on whatever cadence your team picks (per-batch, weekly, or at delivery). Contributor payouts run between your org and your annotators, Worqgrid's monthly subscription is separate and only covers platform access.
Still have questions? Talk to sales →