ReadX is an intelligent evaluation platform that transforms handwritten answer sheet assessment using a proprietary Vision-Language AI engine — delivering human-grade accuracy with unprecedented speed.
From handwriting recognition to detailed cognitive assessments, ReadX handles the entire evaluation pipeline end-to-end.
1.2T parameter Mixture-of-Experts model with 38B activated per pass. Purpose-built for understanding handwritten content across scripts.
Goes far beyond simple scoring — evaluates factual accuracy, conceptual depth, procedural correctness, and presentation quality.
Generates detailed, actionable feedback narratives with strength identification, weakness analysis, and personalized improvement strategies.
Automatically classifies demonstrated cognitive levels from Remember to Create, enabling longitudinal tracking of learning progression.
Multi-level confidence estimation on recognition, assessment, and aggregated results — route low-confidence cases for human review automatically.
Comprehensive APIs for LMS, SIS, and identity management integration. Supports SAML 2.0, OAuth 2.0, and LTI standards out of the box.
An 8-stage pipeline transforms raw answer sheet images into comprehensive, multi-dimensional assessment reports.
Acquisition from scanners, cameras, or uploads with quality assessment
Geometric correction, normalization, skew removal, and binarization
Handwriting recognition via Vision Transformer with MoE architecture
Scoring, feedback generation, Bloom's taxonomy, and report delivery
Protected intellectual property innovations that solve real problems in answer sheet evaluation workflows.
Automatically detects multi-page answers and assembles them into a unified continuous-scroll view — eliminating fragmented page navigation and reducing evaluator cognitive load.
Intelligent semantic mapping that automatically identifies which question an answer belongs to — even when students forget to write question numbers or write incorrect ones.
Cross-reference marking system that surfaces previously evaluated similar answers during grading, promoting consistent marking standards across evaluators and assessment cycles.
Complete identity separation with NRC-based extraction, encrypted storage, and anonymous identifier assignment — ensuring fully unbiased, confidential evaluation.
A Mixture-of-Experts Vision-Language Model purpose-built for handwritten document understanding and educational assessment.
The ReadX AI Engine activates only 3.2% of its 1.2T parameters per inference pass — achieving the performance of massive dense models at a fraction of the compute cost. Expert networks specialize naturally during training for different scripts, content types, and assessment functions.
Trained on curated benchmarks (IAM, IIIT-INDIC-HW-WORDS, DohaScript) combined with LLM-generated synthetic data using Chain-of-Thought augmentation and contrastive learning.
ReadX outperforms baseline transformers and commercial OCR on every key metric across all supported languages.
Native support for three languages with cross-lingual understanding for mixed-language answers.
Deploy ReadX on-premises, in the cloud, or hybrid — and start evaluating at scale within weeks.
Whether you're exploring a pilot, need a technical deep-dive, or want to discuss a partnership — our team responds within one business day.
Pick the channel that works best for you. For enterprise enquiries and demos, the form on the right gets you directly to our solutions team.
Thank you for reaching out. A member of our team will get back to you within one business day.
Most institutions are fully onboarded within two to three weeks. Our team handles LMS/SIS integration and provides sandbox access from day one.
Yes. Our cross-lingual encoder handles code-switching natively — English to Hindi or Punjabi mid-paragraph, fully supported without any special configuration.
Absolutely. ReadX supports on-premises, private cloud, and hybrid modes to satisfy data residency and institutional security requirements.
All enterprise plans include dedicated customer success management, 24/7 priority incident support, quarterly model updates, and a private Slack channel for direct engineering support.