Know what the class understands.
Before the exam.
ClassSignal uses Azure AI to analyse student response patterns, detect shared cohort misconceptions, and prescribe immediate teaching interventions — delivering 85% teacher review efficiency for school networks, NGOs, and education cooperatives.
Grade 10 STEM Cohort • Mathematics
Algebraic Expressions & Factorisation
Teacher Review Efficiency
85.4%
+32 min saved• 12 min avg diagnosis
Cohort Concept Mastery
68.2%
32 student responses analyzed
Shared Misconception Signal
Sign Distribution Error on Negative Expansion
Students consistently multiply terms inside brackets correctly, but invert the minus sign when expanding terms such as -(3x - 4) into -3x - 4.
Suggested 10-Minute Classroom Intervention
"Use visual area models with double-sided algebra tiles before assigning independent practice."
85.4%
Teacher Review Efficiency
12 min avg diagnosis vs 75 min manual
140+
Active Partner Schools & NGOs
Across Sub-Saharan Africa & Global Trusts
45,000+
Students Monitored Live
Continuous formative learning signals
94.8%
AI Misconception Detection
Powered by Microsoft Azure Cognitive Stack
Target B2B Sectors
Purpose-built for institutional education stakeholders
Whether you manage 50 schools in an academy trust or track foundational learning for an NGO program, ClassSignal turns raw tests into actionable intelligence.
School Networks & Trusts
Multi-school cohort aggregation, standardized misconception benchmarking, and automated formative interventions across schools.
Education NGOs & Foundations
Measure learning poverty, track numeracy and literacy interventions, and evaluate program efficacy with live response-level telemetry.
Teacher Cooperatives & Districts
Equip hundreds of teachers with instant AI diagnostic marking, reducing assessment workload while lifting student exam outcomes.
EdTech & Assessment Firms
Integrate ClassSignal's Azure-powered cognitive misconception API into existing LMS, digital testing, and curriculum platforms.
Marks show who failed. But marks hide the root misconception why.
Teachers spend hours grading papers and recording numbers like "62%". But two students with 62% might fail for completely different mathematical or scientific reasons.
Without response-level analysis, systemic misconceptions remain undetected. By the time final examinations arrive, simple foundational gaps have compounded into irreversible learning deficits.
Educators manually reviewing hundreds of assessment papers lack the automated pattern detection needed to catch shared misconceptions early.
With ClassSignal, teachers deliver targeted 10-minute micro-interventions that resolve shared misconceptions on the very next school day.
AI response telemetry. 85% review efficiency. Actionable teaching.
ClassSignal's Azure-backed AI engine scans open-ended answers and multiple-choice distractors, instantly clustering students by shared conceptual flaw.
Instead of generic grade reports, teachers receive a clear diagnostic signal: "61% of students make an error on negative expansion", coupled with a targeted 10-minute classroom reteach activity.
Automated Workflow
Assess → Analyse → Intervene
A streamlined three-step learning intelligence loop designed for real classrooms.
01
Assess & Ingest
Teachers upload handwritten or digital assessments. Azure AI Document Intelligence extracts response-level student working and reasoning steps.
02
Pattern Detection
Azure OpenAI models identify clustering error signatures across the classroom, separating trivial slips from systemic conceptual misunderstandings.
03
Prescriptive Intervention
The teacher receives an instant diagnostic summary and a ready-to-teach 10-minute micro-lesson to correct the misconception before high-stakes exams.
Experience the live intelligence cockpit
Interact with real classroom telemetry, explore concept breakdown curves, and inspect live AI misconception signals.