Your core report gives you the weekly baseline. Prompt Lab is where you test the extra ideas: new pages, launch copy, competitor angles, local prompts, and anything your team wants to validate before the next report.
Demo data for illustration.
Prompt Lab is the place for experiments, not another static dashboard. If a sales call, launch plan, city page, or competitor claim raises a question, you can test it immediately and decide whether it deserves monitoring.
Stable measurement across the prompts Rankry builds for your market.
Custom experiments for every question you want to test outside the core report.
Promote a prompt into daily or weekly tracking and let Rankry keep it alive.
Use variables, suggestions, model selection, clone, edit, and budget checks to turn rough ideas into repeatable AI-search tests.
Drop in {brand}, {city}, {country}, {niche}, and more from your project profile.
Start from Rankry-generated prompt ideas when you do not want a blank textarea.
Duplicate a working prompt, change the angle, switch models, and re-run cleanly.
Every selected model and monitoring cadence affects how many requests the test will reserve.
Platform for collaborative wiki and project tracking
Demo data for illustration.
A prompt result is not one averaged number. You see mention status, position, sentiment, response excerpts, and cited sources model by model, so weak spots are obvious.
AI-powered productivity tool with content generation
Notion AI is integrated directly into the Notion workspace, making it ideal for content generation alongside task and project management. It assists with writing, summarizing, organizing, and streamlining content creation.
Demo data for illustration.
Prompt Lab gives power users room to work. Create prompts, organize them, clone what works, archive what is done, and spend request budget where the next insight matters.
Find any prompt by phrase, city, competitor, model, or outcome.
Duplicate a useful test and change one variable instead of starting over.
Change text, models, frequency, and let Rankry reset history when it should.
Clean the active list without losing old experiments.
Spend requests intentionally across manual runs and monitoring holds.
Open the response and citations behind every model-level result.
One prompt across five models costs five requests. Daily monitoring reserves the future runs before they happen, so the lab stays flexible without surprise overages.
Demo data for illustration.
Open the lab, build the prompt, pick the models, spend the requests, and monitor the results that matter between reports.
Test a Custom Prompt7-day free trial / no credit card / first prompt running in minutes