AI Grading System for Platforms That Need More Than Scores
Go beyond automated scoring. Capture what grading misses.
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Your platform grades. It doesn't learn.
Grading today is not a system — it is an endpoint
Education has no memory of learning.
CrazyGoldFish is not an AI grading tool.It is Evaluation Infrastructure.
Evaluation is the control point where learning becomes structured data. It is evaluation infrastructure.
Extracts reasoning, concepts, and errors during evaluation
Converts responses into structured learning signals
Stores signals across time, attempts, and contexts
Builds a continuous learning record per student
Output is not just a score. It is structured learning intelligence.
{ "concept_impact": { "primary_concept": "Differentiation", "blooms_level": "Apply", "prerequisite_gap": "Chain Rule" }, "performance_based_inference": { "error_type": "Procedural Mistake", "inferred_mastery": "Needs Review", "error_severity": "Moderate" }, "confidence_score_estimation": { "estimated_confidence": 0.72 }, "learning_action_trigger": { "action_type": "Remedial", "scope_of_improvement": "Sign convention in derivatives" }, "memory_stored": "✓ student_7f2a · session_032" }
What this makes possible
- →Feedback becomes consistent and reusable across every student
- →Learning gaps stay visible over time, not just per test
- →Personalisation runs on signals, not guesswork
- →Every evaluation decision is auditable and governed
Built for platforms that own evaluation.
Governed, not automated.
Teacher remains final authority. Every evaluation is auditable. All corrections become learning signals.
Teacher retains final grading authority on every evaluation
Every evaluation logged, traceable, and reviewable
Teacher overrides feed back into the learning memory layer
Policy-aware, rubric-driven evaluation at every step
"Evaluation time reduced by 50–60% while maintaining 93% reliability, with teachers retaining full grading authority through a governed hybrid model."Read the case study →
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CrazyGoldFish is an AI grading system built for platforms that need more than scores. It captures learning signals from every evaluation — reasoning steps, conceptual gaps, and error patterns — and structures them as persistent learning memory. Reliability: 93% scoring alignment (ICC). Human-in-the-loop, policy-aware, and built for scale.
What is an AI grading system?
An AI grading system evaluates student responses automatically, assigning marks and generating feedback. CrazyGoldFish goes further — it captures the reasoning, concepts, and gaps inside each response as structured learning signals, not just scores.
How is CrazyGoldFish different from standard AI grading tools?
Most evaluation infrastructure produces scores. CrazyGoldFish produces structured learning intelligence — capturing what the score hides, storing it as persistent memory, and making evaluation auditable and governed.
Is the evaluation fully automated?
No. CrazyGoldFish uses a human-in-the-loop model. AI evaluates first; teachers retain final authority. Every evaluation is auditable, and corrections are fed back into the system as learning signals.
What platforms can integrate with CrazyGoldFish?
CrazyGoldFish is built for EdTech platforms, LMS / ERP systems, coaching institutes, and assessment platforms scaling subjective evaluation.
What is the accuracy of AI grading vs human teachers?
CrazyGoldFish achieves 89.7% adjudicated correctness versus a teacher baseline of 82.8% — a +6.9% improvement. 87% of responses fall within a ±6-mark tolerance, and 90%+ accurate feedback is delivered instantly. These figures are validated in real evaluation environments and published in the India AI Impact Summit 2026 Compendium, MeitY.
Bring evaluation infrastructure to your platform.
Book a demo to see how CGF integrates with your stack — or explore the APIs directly.
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