AI chatbot for WatuPRO quizzes and exams
SleekAI hooks into the WatuPRO tables, including wp_watupro_master, wp_watupro_questions, wp_watupro_answers, and wp_watupro_taken_exams. Quiz takers ask why they scored what they did, what a category result means, or how to improve before the next attempt, and the bot answers from real data using your own OpenAI, Anthropic, Google, or OpenRouter API key.
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WatuPRO scoring is rich, but the explanation is thin
WatuPRO is a serious quiz engine. It supports certification exams, personality tests, lead-generation surveys, and graded assessments with categories, advanced grading, point thresholds, and CPD-style certificates. The data model is correspondingly complex: wp_watupro_master stores quiz settings, wp_watupro_questions and wp_watupro_answers hold the question bank with point values, and wp_watupro_taken_exams records every attempt with the user's selections, score, time spent, and final grade. None of this surfaces to the test taker in plain English.
SleekAI maps those tables into bot variables. When a user finishes a 30-question certification, the bot can read their row from wp_watupro_taken_exams, join to the answer key in wp_watupro_questions, and explain category breakdowns: you scored 78 percent overall, but only 50 percent on the safety category that requires 70 percent to pass. A display condition keyed to the WatuPRO results page or the user role keeps the bot in the right context.
Generic chatbots fail because they have no view of which category each question belongs to, what the passing thresholds are, or which option the learner chose. They cannot retrieve a previous attempt to compare progress. SleekAI references concrete category names, point totals, and historical attempts, and respects whether the quiz is still in progress before discussing answers.
Workflow
How the WatuPRO chatbot is wired up
Map the WatuPRO tables
Set display conditions
Write the system instruction
Audit conversations
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A typical WatuPRO post-exam conversation
Comparison
Generic chatbot vs SleekAI for WatuPRO
Generic chatbot
- Cannot read attempt rows from wp_watupro_taken_exams to ground feedback
- Has no view of category thresholds or advanced grading rules
- Cannot quote which answer the candidate picked versus the correct one
- Treats certification exams the same as casual personality quizzes
- Will guess at retake rules, cooldowns, and certificate eligibility
SleekAI chatbot
-
Maps
wp_watupro_mastersettings so retake rules and thresholds are exact -
Reads category scores from the serialized result in
wp_watupro_taken_exams -
Joins
wp_watupro_questionsfor point values and category assignment - Display conditions can target results page, user role, or specific quiz_id
- Logs every conversation with quiz_id and attempt_id for audit-grade review
Features
What SleekAI gives you for WatuPRO
Certification-grade explanations
Reads quiz settings from wp_watupro_master including pass mark, category thresholds, time limit, and retake policy. The bot explains exactly why a certification was awarded or withheld, citing the rule that fired.
Per-category breakdowns
WatuPRO stores category scores in the serialized result on wp_watupro_taken_exams. SleekAI unpacks it so the bot can say you scored 50 percent on Safety against a 70 percent floor, not just one overall number.
Respects exam state
If the candidate has an attempt in progress, the bot answers process questions and explains concepts but refuses to reveal correct options from wp_watupro_answers. Post-submission, it can walk through specific question results.
Use cases
Where this chatbot earns its keep
Continuing education portals
CPD and CME providers running graded exams. The bot reduces support tickets from candidates who don't understand why they failed despite a passing overall score.
Internal compliance training
HR and safety teams running annual recertifications. Employees get personal feedback that points them at the exact module to review before retaking.
Lead-generation personality quizzes
Marketers using WatuPRO for diagnostic quizzes. The bot interprets the result type and recommends the next step, scoped by the result_id stored in wp_watupro_taken_exams.
The bigger picture
Why category-aware feedback changes outcomes
Overall percentage is a weak signal in a multi-category exam. A candidate can pass on aggregate but fail because a single category dragged below its floor, and they often have no idea which one. WatuPRO captures all the data needed to explain this, but the default results page is sparse.
A learner who walks away knowing only their overall percentage is far more likely to retake without preparing the right area, fail again, and churn. With SleekAI reading wp_watupro_taken_exams and joining to the category metadata in wp_watupro_questions, the bot can say: your overall was 78, but Safety hit 50 against a 70 floor, here are the two highest-weight items you missed, and your retake unlocks Thursday at 09:14. That single sentence does more for pass rates than a half-written feedback paragraph in the quiz settings.
The same data also lets compliance teams aggregate which categories trip up the most candidates, which is a strong signal about where the training content itself needs to improve. Over a year of attempts, those logs become a coaching dataset. Without category-grounded feedback, candidates retake blind and the underlying training never gets fixed.
Questions
Common questions about SleekAI for WatuPRO
Direct table access via the mapped variables system. SleekAI runs read-only SELECT statements against wp_watupro_taken_exams scoped by current user_id and quiz_id. There is no WatuPRO REST API call involved, which keeps latency under 200ms on most hosts.
 Yes. WatuPRO stores per-category scores inside the serialized result column on wp_watupro_taken_exams. SleekAI unpacks that array, joins to the category names from wp_watupro_questions, and lets the bot say things like Safety 50 percent against a 70 percent floor rather than a single overall percentage.
 Each row in wp_watupro_questions has a points column. SleekAI exposes that to the bot so it can weight feedback by impact. If a candidate missed two 2-point questions in Safety, the bot can flag those as higher priority than the single 1-point question they also got wrong.
 No, the system instruction enforces a check on attempt state. If no completed row exists in wp_watupro_taken_exams for the current user_id and quiz_id, the bot answers concept questions but refuses to discuss specific correct options from wp_watupro_answers. After submission, it explains freely.
 Retake settings live in wp_watupro_master columns like nr_taken, days_before_retake, and similar fields depending on the WatuPRO version. SleekAI reads those into the prompt so the bot can give an exact next-attempt window, not a vague guess.
 Yes. SleekAI's multibot feature lets you create one bot per quiz_id with its own system instruction, presets, and display condition. The compliance bot can be strict and concise while the personality-quiz bot can be playful, both reading the same WatuPRO tables.
 It can read certificate eligibility from the attempt row and the quiz settings. The bot can confirm whether a candidate earned the certificate, when it was issued, and the rule that triggered it. Issuing the certificate itself is still WatuPRO's job.
 WatuPRO supports guest attempts and stores them with a null user_id and an IP-based session key. SleekAI inherits that limitation. The bot can still discuss the quiz content and the just-finished attempt via session token, but cannot reference historical attempts across sessions.
 Pricing
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