WBAcademy
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WBAcademy

Practice real AI training tasks. Pass qualification exams. Get hired by Outlier AI, Scale AI, and more.

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© 2026 WBAcademy. All rights reserved.

All systems operational
Documentation

Everything you need to know

Comprehensive guides, API references, and tutorials to help you build high-quality AI training datasets with WBAcademy.

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CLI ReferenceAPI KeysWebhooksDeploymentTeamsAnalytics

Getting Started

  • Quick Start GuideUp and running in 5 minutes
  • Environment SetupConfigure your local environment
  • Database SetupPostgreSQL schema and migrations
  • AuthenticationOAuth, magic links, credentials

Questionnaires

  • Building QuestionnairesDrag-and-drop builder guide
  • Question TypesAll 27 types explained
  • Adaptive FlowsAI-powered branching logic
  • Publishing & SharingMake questionnaires live

AI Features

  • Question GenerationGPT-4o powered question creation
  • Response ScoringAutomated quality evaluation
  • Adaptive Follow-upsDynamic follow-up questions
  • Toxicity DetectionAutomatic content moderation

API Reference

  • AuthenticationAPI keys and session tokens
  • Questionnaires APICRUD operations
  • Responses APISubmit and retrieve responses
  • Analytics APIUsage stats and metrics

Gamification

  • XP & Leveling SystemHow points and levels work
  • AchievementsUnlockable badges and rewards
  • LeaderboardsWeekly, monthly, all-time
  • StreaksDaily engagement rewards

Admin & Security

  • Role-Based Access Control5 roles explained
  • Content ModerationReview flagged responses
  • Audit LogsFull activity trail
  • Dataset ExportExport training data

Quick Start

Get WBAcademy running locally in under 5 minutes.

1

Clone & install

git clone <repo>
cd wbacademy
npm install
2

Configure environment

cp .env.example .env.local
# Fill in DATABASE_URL, NEXTAUTH_SECRET, OPENAI_API_KEY
3

Set up database

npx prisma db push
npx tsx prisma/seed.ts
4

Start dev server

npm run dev
# Open http://localhost:3000

Question Types

WBAcademy supports 27 question types across 5 categories.

Basic

Text ShortText LongEssaySingle ChoiceMultiple ChoiceRating ScaleSlider

Media

Image BasedAudio QuestionVideo QuestionFile UploadVoice Recording

AI Training

RLHF TaskComparative RankingData LabelingSentiment ClassificationAI Conversation

Assessment

Code EditorTimed QuestionPersonality AssessmentSituational JudgmentInteractive Scenario

Specialized

Drag & Drop RankingMatch FollowingAnnotation TaskTranslation TaskCAPTCHA Validation

XP & Leveling

Users earn XP for completing questionnaires. The level formula creates a smooth progression curve.

level = floor(sqrt(xp / 100)) + 1
xpForNextLevel = level² × 100

// Examples:
// 0 XP    → Level 1
// 100 XP  → Level 2
// 400 XP  → Level 3
// 900 XP  → Level 4
// 10000 XP → Level 11

XP is awarded per questionnaire completion. Bonus XP is granted for streaks, high quality scores, and achievements.

Role-Based Access Control

Five roles with escalating permissions.

RoleCapabilities
USERComplete questionnaires, view own profile & stats
AI_TRAINERAccess dataset exports, view analytics
REVIEWERReview & moderate flagged responses
ADMINManage users, publish questionnaires, view all data
SUPER_ADMINFull access including role assignment and system config

Deployment

Deploy to Vercel (frontend) + Railway or Supabase (database) in minutes.

Vercel (Recommended)

  1. 1. Push to GitHub
  2. 2. Import project in Vercel
  3. 3. Add environment variables
  4. 4. Deploy
Open Vercel (Recommended)

Railway

  1. 1. Create Railway project
  2. 2. Add PostgreSQL plugin
  3. 3. Set DATABASE_URL
  4. 4. Deploy via GitHub
Open Railway