Don't test AI knowledge. Test AI-powered problem solving.

The best professionals don't compete with AI — they collaborate with it. Invyte measures whether someone can use AI to solve real business problems: real work, real context, real collaboration.

Fluency ChallengeBanking Operations · L3
Live
BriefCut refund-queue time without weakening controls.
AI assistantsuggestion
Auto-approve all refunds under $5k to clear the backlog quickly.
Candidate⚑ caught the gap
That skips the AML check. Keep the threshold — automate the evidence collection instead, and route exceptions for review.
EvaluatingCritical thinkingAI collaborationJudgment

AI fluency is more than prompting

Traditional AI assessments ask candidates to write prompts or answer theory. That measures familiarity — not capability. Invyte places candidates inside realistic work scenarios where AI is an active collaborator throughout.

Traditional assessment

Measures familiarity

  • How many prompts you know. Theoretical questions. Multiple-choice about features and models — disconnected from real work.

Invyte Fluency Assessment

Measures capability

  • How effectively you use AI to solve a meaningful problem — in a realistic scenario, with the AI as an active collaborator.

Designed around every AI Persona

Every assessment is built for a specific AI Persona, role, seniority, and industry — reflecting the work candidates will actually perform, not generic AI exercises.

Banking Ops SpecialistProduct Manager
Compliance OfficerAI Engineer

Real work starts with real context

Every challenge begins with the same information a professional gets on the job — because solving problems starts with understanding them. Candidates may receive any of:

Business contextCustomer requirementsProduct specsTeam responsibilitiesBusiness prioritiesDesign documentsTechnical docsSource codeArchitecture diagramsProcess diagramsAPI documentationProduction logsIncident reportsData samples

Meet your AI assistant

Every assessment includes an AI assistant — but it doesn't always behave the same way. How a candidate handles each mode is the real signal.

Mode 01

A collaborative partner

Sometimes it works with the candidate to move faster.

  • Brainstorm ideas
  • Explore alternatives
  • Clarify requirements
  • Discuss trade-offs
Mode 02

Intentionally imperfect

Sometimes it's wrong on purpose — incomplete, inefficient, or confidently incorrect. Strong candidates recognize it, question it, verify it, and improve on it.

  • Suggests an incomplete solution
  • Misses a key requirement
  • Recommends an inefficient approach
  • States wrong info, confidently
Mode 03

Holds back the answer

Sometimes it knows the solution but won't hand over the whole thing — the candidate has to lead.

  • Ask thoughtful questions
  • Break the problem down
  • Guide the conversation
  • Work iteratively to the outcome

Exactly like working with modern AI systems.

Expert-crafted, adaptive challenges

Every assessment is designed by subject-matter experts around realistic business scenarios — no generic quizzes, no artificial puzzles. And every assessment evolves with the candidate: as capability rises, so does sophistication.

Role responsibilitiesIndustry frameworksBusiness prioritiesTechnical constraintsCustomer expectationsRegulatory requirements
difficulty · adapting
Greater ambiguity
Larger systems
More stakeholders
Harder trade-offs
The goal isn't to make assessments harder — it's to find exactly where exceptional performance begins.

We evaluate the entire collaboration

Success isn't just the final answer. We score how a candidate works with AI across the whole problem-solving process.

01

Understanding the problem

Can they identify what's actually being asked?Separate facts from assumptions?Clarify ambiguity before acting?
02

AI collaboration

Can they guide AI toward useful outcomes?Ask better follow-up questions and refine responses?Use AI strategically rather than passively?
03

Critical thinking

Do they verify AI-generated information?Challenge incorrect recommendations?Recognize missing context before accepting an answer?
04

Problem solving

Can they decompose complex work?Evaluate alternatives and balance competing priorities?Produce a practical solution?
05

Final outcome

Does the solution actually solve the business problem?Is it technically sound and practical?Well reasoned and ready for real-world execution?

Every interaction becomes evidence

Hiring teams don't just get a score — they get explainable evidence. Not only what a candidate answered, but how they got there.

  • Complete AI conversations
  • Candidate reasoning process & prompt evolution
  • AI corrections the candidate made
  • Decision timeline & problem-solving strategy
  • Final deliverables
  • Strengths and improvement opportunities
replay · how they got there
Prompt v1
Framed the problem and asked the AI for an approach.
Caught AI error · 03:41
Flagged the missing AML check and corrected the AI's shortcut.
Refined approach
Decomposed into evidence-collection + exception-routing.
Final deliverable
A controls-safe automation, reasoned and execution-ready.

Built for the AI workplace

The modern workplace isn't humans versus AI — it's humans working alongside AI every day. The professionals who create the most value aren't the ones who memorize prompts. They're the ones who combine human expertise with AI to solve difficult problems. That's the capability Invyte measures.

Experience matters

Domain depth still counts.

Judgment matters

Human reasoning still leads.

AI changes how

…great work actually gets done.

AI fluency is a competitive advantage

Invyte helps you identify professionals who turn AI into real business value — not just faster answers. Because the future belongs to people who know how to work with AI.