Incentivize your annotators. Only pay for results.

It is a program that pays annotators for hitting defined targets, like labels that passed audit while your gold-set accuracy bar held, a calibration task passed after a guideline change, or a delivery-window shift covered. Jolly runs these as campaigns tied to the quality data your annotation platform already produces, so spend maps to usable labels rather than to raw volume.

It would, which is why volume alone never triggers a payout. Productivity campaigns pay on throughput only while an annotator's gold-set accuracy stays above the bar you set, so a fast guess on a hard example earns nothing and drags the rest of the payout with it. The hard examples are the reason the dataset exists, so the incentive has to protect them.

Yes, and the metric changes. On an evaluation queue there is often no single correct answer, so Jolly rewards rubric calibration passed and agreement with the adjudicated score rather than a gold-set match. Raters earn on the queues they are qualified for, and you only pay when the score survives adjudication.

It can, if the reward points at an answer. Jolly targets never name a class or a label value, only the process: accuracy against your gold set, calibration passed, escalations confirmed. You set the targets, so you can see what each campaign is asking for before it runs, and you can see the label distribution alongside the payout.

Guideline changes are where agreement drops, so that is where the campaign sits. Jolly rewards guideline updates acknowledged and calibration tasks passed before the new rules take effect, which turns the rollout into something annotators earn on rather than a document they find after their accuracy falls.

Yes, but not by paying for agreement itself. Paying an annotator to match the room rewards the easy answer and quietly buries the edge cases you built the dataset to capture. Jolly rewards the inputs that raise agreement honestly, like calibration tasks passed after a guideline change and edge cases escalated and confirmed. Agreement is the number you watch, not the number you pay.

Project-specific judgment takes weeks to build and leaves in a day, and annotation work is often short-term by design. Jolly runs retention campaigns tied to days on the project and to task-type certifications, so staying through a delivery carries visible upside. You only pay when retention actually improves.

By rewarding audited throughput rather than submitted volume, so the work that lands is the work that ships. Jolly pairs delivery-window scheduling campaigns with gold-set accuracy targets, which is what keeps a deadline push from producing a batch that has to be redone.

Jolly runs scheduling campaigns that reward annotators for picking up the shifts a delivery window actually needs, including weekends ahead of a client date. You only pay when the shift is covered, so the spend maps to coverage rather than to a standing overtime budget.

Annotation projects ramp in days, and your current annotators know who can do the task. Jolly rewards them when a referral is hired and stays past ramp, not just when a name is submitted, so you only pay when a seat is actually filled and held.

Yes. Data handling modules and access procedures are countable and are exactly what goes stale after onboarding. Jolly rewards modules completed and handling checks passed, so the training stays current across a workforce that turns over faster than the annual cycle assumes.

Yes. Targets are set per project and per task type, so an image labeling project, a model evaluation queue, and a client with its own quality bar can run different campaigns at the same time under one program. You see performance side by side across all of them.

Most likely, yes. Jolly's Data Agent connects to the systems you already run, including annotation and labeling platforms, your task router and review queue, and workforce management, and reads live performance from them. Campaigns run on your real project data, not on self-reported numbers.

Yes. Each campaign has defined targets. When an annotator hits theirs, points dispatch automatically. When they do not, nothing is paid, so your spend always maps to labels that actually cleared the gold set or a delivery window actually covered.

Nothing is deducted. Incentives are always upside. Annotators earn more when they perform and there is no penalty when they do not, which matters most on quality campaigns, where any downside would give someone a reason to hide an uncertain label rather than flag it for review.