Education&EdTech
Personalized learning has always been the goal in education; AI is what finally makes it operationally realistic at scale. We build adaptive tutoring copilots, grading assistants, and learning analytics pipelines that help educators and edtech teams support more students without burning out the people doing the teaching.
Grading feedback turnaround target
Adaptive content adjustment cadence
Instructor time reclaimed per week (typical estimate)
WhatmakesAIhardhere
Personalizing instruction for diverse learners is hard to do at scale
Every classroom has students at different skill levels and different learning paces, but a single teacher managing thirty or more students can't realistically customize instruction moment to moment for each one without support.
Grading and feedback create a heavy burden on instructors
Meaningful, specific feedback on student work takes real time to write, and instructors are often grading dozens or hundreds of assignments on top of teaching and lesson planning, which pushes feedback turnaround out by days or weeks.
Learning data is fragmented across platforms
Learning management systems, assessment tools, and separate practice platforms rarely share data cleanly, making it hard for educators or edtech products to build a complete picture of where a student is actually struggling.
Building genuinely adaptive content is expensive
Creating content that adjusts to a learner's demonstrated skill level, rather than presenting the same fixed curriculum to everyone, historically required significant manual content authoring effort that most education organizations can't sustain at scale.
Whatwebuild
Adaptive tutoring copilots
We build copilots that assess a student's current understanding from their responses and adjust the difficulty and format of practice material in real time, giving each learner a path that matches their actual skill level rather than a fixed sequence.
Automated grading and feedback assistants
We build tools that draft specific, rubric-aligned feedback on student writing and problem sets for an instructor to review and finalize, cutting the time between submission and feedback from days to same-day in many cases.
Learning analytics pipelines
We design data pipelines that unify data from LMS, assessment, and practice platforms into a single learner progress view, so educators and edtech products can identify where a student is struggling before it shows up in a final grade.
Edtech MVP development
We help edtech teams build a first working version of an AI-powered learning product, from adaptive content architecture through a usable pilot, so a new product concept can get in front of real classrooms and users quickly.
Responsible AI strategy for education
We advise education organizations on academic integrity safeguards, bias testing, and age-appropriate data privacy practices for AI tools, helping define policy for how AI-assisted grading and tutoring gets disclosed and used responsibly.
Howwe'dapproachthis
Commonquestions
No. We build grading assistants to draft feedback aligned to a rubric an instructor defines, but the instructor reviews and finalizes every grade and comment before it reaches a student; the tool is designed to speed up feedback, not to make the final academic judgment.