01
You don't know who and how on your team uses AI
How we solve it:
Maps every person, team, and department to one of 5 maturity levels across five dimensions: Usage, Skills, Impact, Culture, and Vision.
Find out where AI adoption is actually stuck in your company
Research-based assessment of the human side of AI adoption — skills, habits, and culture,
validated across 44 teams.
Integrations needed
0AI tools mapped
120+New AI developments tracked
25
Trusted by top companies
"We thought our engineering team was ahead on AI. The index showed Culture was the real bottleneck, not skills. We'd never have found that without the data. Two teams were already at Level 4, the rest were sitting at Level 2. That single view changed where we put the training budget this quarter."
Roman Rodomansky
Co-Founder & CTO, Ralabs
Our product presented at
DevWorld conference, Netherlands
Harvard
Business ReviewWAW Tech conference, Warsaw
From first survey to a rising trend
Your first run sets the baseline. Every run after it shows what your changes actually moved.
Pick a survey and invite your people by email or link — no integrations needed
Results update with every answer: overall level, five dimensions, every team
Fix the weakest spot, run the survey again, and see the trend move
Repeat every quarter
Check what is your company AI score?
Question 1 of 5
Do you know which AI tools your team uses on a daily basis?
Three problems most companies can't see
AI investment keeps growing. Clarity on what's actually happening with people doesn't. Here's what AI Adoption Score makes visible.
02
Someone figured out a powerful AI workflow.
Nobody else knows it exists.
How we solve it:
The 360° report's culture-spread gap shows where AI know-how exists but isn't written down or passed on — so you know which workflows to capture and share first.
03
"We need more AI skills" — but which skills,
and in whom?
How we solve it:
AI Skills Distribution maps each person's expertise so you can allocate training by actual gap, not assumption.
7 ways to understand your teams
Each survey answers a different question about AI adoption. Use them individually or combine them into a full picture. Two more are on the way.
Flagship360° AI Maturity Assessment
Ralabs' full methodology — usage, skills, impact, culture and vision combined into a single score, with a level for every person, team and the whole organization.
About this survey
AI Market Pulse
Is your team keeping up with what shipped in AI this quarter? Shows how far people have got with each new tool and model — heard of it, tried it, or use it at work. New questions every quarter.
About this survey
AI Anxiety Scale (AIAS)
Identifies what your employees are actually afraid of when it comes to AI — so you can address the real blockers, not the assumed ones.
About this survey
AI Skills Distribution
Maps each person's specific AI expertise — who knows which tools, who builds automations, who follows the latest models.
About this survey
AI Adoption Barriers
Uncovers the real reasons your team isn't using AI more effectively — whether that's access, confidence, habits, or something else entirely.
About this survey
Software Quality Management (SQM)
Checks which engineering practices one project follows, in 14 areas from requirements to security — and lists what's missing, most important first. One run per project, answered by its team.
About this survey
n8n Skills Assessment
How well do people really know n8n? A self-rating and a short quiz in each of 10 skill areas — levels come from right answers, not self-ratings.
About this survey
Coming soonClaude Skills Assessment
The same quiz format, for everyone who uses Claude at work — with extra questions for people who use Claude Code or build with the API.
About this survey
Coming soonQuick AI Self-Evaluation
20 questions you ask yourself. A fast self-check of where you stand compared to the current market — designed as an entry point into deeper assessment.
About this surveyKnow where your team stands
before you invest more.
One week. A clear picture of your organization's
AI performance — and exactly what to do next.
