EdTech
AI for language and learning products
Education teams use AI for assessment, feedback, and analytics, not for replacing instructors. We build scoring integrations, learner-facing flows, and admin dashboards that survive real classroom load.
Discuss edtech AIContext
What teams struggle with
Scoring must be consistent and explainable
Learners and admins need to trust results. Opaque model output or vendor-specific error codes create support churn and program drop-off.
Audio and media paths are fragile
Upload failures, format mismatches, and slow vendor responses break the learner experience unless retries, progress states, and fallbacks are designed in.
Privacy and cohort boundaries
Programs handle minors, institutional data, and cross-border learners. Data routing and retention need explicit boundaries before AI features ship.
Use cases
What we build in this vertical
Assessment
Speech and pronunciation assessment
Recording flows, vendor scoring APIs, normalized feedback, and history views for learners and coaches.
Feedback
Automated feedback on submissions
Structured comments on essays, speaking tasks, or code exercises with human review for edge cases.
Analytics
Learner and cohort analytics
Dashboards for program admins: progress, usage, and outcome trends without exposing raw vendor payloads.
Copilot
Content assistance for educators
Draft lesson plans, rubrics, and quiz items with approval workflows before anything reaches students.
Stack
Typical tooling
Scoring and speech
SpeechRater · VoX · Custom audio pipelines · Object storage
Product stack
React · Python · PostgreSQL · REST / GraphQL
Reliability
Queue workers · Retry policies · Eval fixtures · Structured logging
FAQ