Challenge
Measuring real analysis
Linear case submissions hide decision quality. Scoring without evidence criteria drifts between graders.
ReadX presents branching constraints and scores how candidates use data and justify recommendations.
Deliver dynamic case studies with branching scenarios and AI scoring of analysis quality.
Service overview
Case evaluations should reward analysis, not memorised frameworks. ReadX AI Case Study presents branching scenarios and scores use of evidence, assumptions and recommendations.
Compare cohorts on problem-solving patterns to improve pedagogy.

Dynamic scenario trees
Data-use scoring
Peer benchmarks

Audience
B-schools and professional programmes using cases to judge analysis, not memorised frameworks.
Faculty who want branching scenarios and cohort benchmarks on evidence use.
Challenge
Linear case submissions hide decision quality. Scoring without evidence criteria drifts between graders.
ReadX presents branching constraints and scores how candidates use data and justify recommendations.
What you get
Feature areas specific to this service — secure delivery, fair evaluation, and actionable insight where they apply here.
Decisions open new evidence and constraints.
Judge use of data, assumptions, and recommendations.
Compare cohorts on problem-solving patterns.
Decisions unlock new constraints and data — closer to boardroom cases than linear short answers.

Judge whether candidates cited relevant data and tempered claims — then benchmark across batches.

Answers focused on this service — implementation, integrations and high-stakes use.
We will walk through this exact workflow using your exam volumes, policies and timelines — not a generic product tour.