Find out how your model performs for real people. Evaluators in the countries you choose rate, compare and check your model's outputs, from chatbot answers to generated images and synthetic voices.
Text, image and audio · Many evaluators per item · Any language
200+
Countries
13,487
Tasks completed
195,000+
Registered workers
~4 Hours
Avg time to results
Prepare your outputs, write the questions, and collect independent judgments from many people.
Put a numbered set of outputs into the task: text in the instructions, images or audio as reference files.
Text in the task instructionsImages or audio as reference filesNumbered item set
Set the criteria, the rating scale and examples of good and bad outputs so evaluators judge the same way.
Criteria you defineRating scale or comparisonExamples of good and bad outputs
Each evaluator completes your task once, so every item gets opinions from different people.
One submission per evaluatorMany opinions per itemCountries and languages you choose
Approve careful submissions, reject careless ones and export the answers to compare scores across model versions.
Approve or reject each submissionExport answers for analysisCompare scores across versionsIf a person can read, see or hear it, a person can judge it. Put your outputs into the task and collect human opinions at scale.
Rate answers for helpfulness, accuracy, tone and safety, or compare two versions of your model. Example: “Which answer would you rather get?”
Check generated images for quality, realism and how well they match the prompt. Example: “Does this image show what the prompt describes?”
Listen to synthetic voices and score naturalness, clarity and pronunciation. Example: “How natural does this voice sound, from 1 to 5?”
Compare audio clips with model transcripts and mark wrong or missing words. Example: “Is this transcript correct? Mark any errors.”
Native speakers check machine translations for meaning, grammar and natural wording. Example: “Does the translation keep the original meaning?”
Judge how well results match a query or how relevant recommendations feel to a real user. Example: “How useful is this result for the query?”
Pick the judgment format that matches your model and the questions you need answered.
Evaluators pick the better of two outputs and explain why.
Score each output from 1 to 5 on the criteria you define.
Average listener scores for voice and audio quality.
Yes or no questions about accuracy, safety or format.
Evaluators mark what went wrong: wrong facts, bad grammar, missed words.
Short written comments that explain the numbers.
Human evaluation shows how your model performs for actual users, not only on similarity scores.
Automatic scores measure similarity, not usefulness. People tell you which output they would actually prefer.
Native speakers catch awkward phrasing, wrong tone and cultural mistakes that metrics miss.
Every evaluator works independently, so you see real agreement and disagreement on each item.
You decide what counts as a good judgment and review every submission before it joins your results.
Add items with an obvious correct answer to spot careless submissions.
Ask for a short reason with every score so you can trust the numbers.
Order several evaluators per item and compare answers for agreement.
Reject submissions that ignore your rules. Start with a 20–50 item pilot, then scale up.
Launch evaluation tasks on the platform, or hand the project to our team for end-to-end delivery.
Self-serve
Create a task, add your outputs and rating rules, choose countries and review results yourself.
Create an evaluation taskFully managed
We design the evaluation, recruit and screen evaluators, run quality checks and deliver clean results in your format.
Talk to usYou set the pay per task. One submission is one evaluator's judgments on your item set. The 15% platform fee is included.
How long it takes a worker to complete one task.
Minimum pay is $0.10 per task. Need more evaluators later? Extend the same task instead of creating a new one.
A human evaluation platform lets you send AI model outputs to real people and collect their ratings, comparisons and comments. It shows how your model performs for actual users, not only on automatic metrics.
Any model whose output a person can read, see or hear: chatbots and language models, image generators, speech synthesis, speech recognition, translation, search and recommendations.
Put text outputs into the task instructions and upload images or audio as reference files. Evaluators review them and submit their scores and comments as their answer.
For clear-cut checks, one or two may be enough. For subjective quality like naturalness or preference, use three or more and compare their answers.
Yes. Show both outputs side by side and ask evaluators to pick the better one and explain why. This works well for A/B tests between model versions.
Evaluators are everyday users from many countries. They are best for judging clarity, usefulness, naturalness and language. Describe any skills you need in your instructions and reject submissions that do not meet them.
Yes. Choose countries where the language is spoken and state it in your instructions. Task descriptions are written in English.
You set the pay for each task, starting from $0.10, plus a 15% platform fee. A campaign starts from $0.30, so you can run a small pilot first.
Add control items with a known answer, ask for short reasons, use several evaluators per item and reject careless submissions.
Yes. Our team can design the evaluation, recruit evaluators, run quality checks and deliver the results. Contact us through the form below.
Tell us what model you are testing, how many items and which languages. We will help you design the evaluation and set up the tasks.
