Lingua.ly
Immersion-based language learning through real-world web content and context-aware SRS.
The AI-powered reading tutor accelerating literacy through the Science of Reading.
Amira Learning represents the vanguard of Intelligent Tutoring Systems (ITS) in the K-12 sector, specifically engineered around the 'Science of Reading.' Its technical architecture leverages a proprietary Speech Recognition engine trained specifically on millions of hours of children's speech—a demographic traditionally underserved by standard LLM and ASR models due to pitch and cadence variability. By 2026, Amira has positioned itself as the primary infrastructure for automated Oral Reading Fluency (ORF) assessments and state-mandated dyslexia screening. The platform operates on a 'Micro-Intervention' loop: as a student reads aloud, the AI analyzes phonemic awareness, decoding accuracy, and prosody in real-time. If a student stumbles, Amira provides immediate, evidence-based scaffolding (such as rhyming, synonyms, or lip-sync videos) to build neural pathways for literacy. Market-wise, Amira’s 2026 positioning is fortified by its integration with major curriculum providers like Houghton Mifflin Harcourt (HMH), making it a non-negotiable tool for district-level digital transformation. The system significantly reduces the 'assessment burden' on teachers, automating hours of manual testing into minutes of non-intrusive student activity while providing high-fidelity data for MTSS (Multi-Tiered System of Supports) frameworks.
Proprietary Automatic Speech Recognition models trained on over 10 billion spoken phonemes from children across diverse accents.
Immersion-based language learning through real-world web content and context-aware SRS.
Hybrid language mastery through pedagogical technology and expert human oversight.
Master vocabulary 10x faster with AI-driven spaced repetition and big-data linguistics.
Accelerate Spanish and English mastery through Lingu, an adaptive AI tutor that personalizes every lesson.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A rapid assessment identifying risk markers for dyslexia based on phonological processing and rapid naming metrics.
Real-time scaffolding logic that triggers specific instructional prompts based on the exact type of reading error (e.g., visual vs. phonetic).
Full cross-linguistic assessment capabilities for Dual Language and ESL programs.
Analyzes the rhythm, stress, and intonation of speech to measure reading comprehension and expression.
Embedded video clips showing correct mouth positioning for specific phonemes during an intervention.
Automated data mapping to Multi-Tiered System of Supports frameworks for immediate intervention grouping.
Manually assessing 30 students for reading fluency takes days of teacher time.
Registry Updated:2/7/2026
State laws requiring early identification of dyslexia risk.
Students need 1:1 reading time that teachers cannot provide daily.