Analysis & Grading
Handwritten work, voice responses, and digital submissions — graded instantly and mapped to learning outcomes.
Written work
Photo → OCR → instant result.
A student photographs their worksheet. The OCR pipeline detects bounding boxes, extracts handwritten text, and runs it through the AI grading engine. The result — mark, feedback, and learning outcome mapping — is returned in seconds.
Under 0.5% failure rate across all worksheets processed to date.
Spoken responses
Voice recognition at 96.7% accuracy.
Speaking assessments are captured through the mobile app and processed by Deepgram's transcription engine combined with AI pronunciation and fluency scoring. Works across languages and accents.
Aligned to Cambridge speaking assessment frameworks.
AI rubric scoring
Structured marking at any scale.
For open-ended responses, AI rubric scoring applies teacher-configured marking criteria consistently across every student. The same standard, applied instantly, to any volume. Every graded item is tagged to a learning outcome, feeding the learning path engine.
Investor perspective
Proven at scale — 300,000+ students, daily throughput.
This is not a prototype pipeline. It has been running in production, every school day, for a national school network. The failure rates and accuracy figures are live operational metrics, not lab benchmarks.