EdTech

EdTech companies are sitting on content libraries that AI can finally make interactive.

Years of course content, lecture recordings, and assessment banks, locked in PDFs and video files, unavailable for real-time student questions, not connected to adaptive learning logic, and requiring instructor time to maintain and update.

We build AI systems that make that content library interactive. Student Q&A systems that answer from your content with source citations. Assessment generators calibrated to your learning objectives. Curriculum gap analysis that maps your content against skill frameworks your learners care about.

How we work

Tell us about your learning platform.

What we build.

Five specific AI workflows for edtech platforms and learning teams.

Student Q&A from course content

A RAG system trained on your course materials, textbooks, and lecture transcripts answers student questions with source citations. Students get answers at 2 AM. Instructors stop fielding the same content questions repeatedly.

Adaptive quiz and assessment generation

Generate quiz questions, practice problems, and assessments calibrated to learning objectives and student performance history. Varies difficulty based on mastery data without instructor manual work.

Curriculum gap analysis

AI maps your course content against industry skill frameworks, job description requirements, or standards bodies, identifying what is covered, what is missing, and where prerequisites may be unclear.

Instructor lesson planning support

An AI assistant helps instructors draft lesson plans, generate discussion prompts, create rubrics, and build supplementary materials from existing course content. Reduces prep time without reducing instructional quality.

Progress report generation

Automatically generate individualized student progress reports from LMS data (completion rates, assessment scores, engagement patterns) in language that is meaningful to parents, students, or corporate learning sponsors.

Who we build for.

Online learning platforms with large course content libraries
Corporate learning and development teams with proprietary training content
K-12 and higher education institutions adding AI to existing LMS infrastructure
EdTech startups building adaptive learning products
Professional certification bodies needing assessment automation

Who this isn't for.

Platforms that want AI to replace instructors
AI works best as a support layer for instructors and students, answering questions, generating practice materials, surfacing gaps. It does not replace the judgment of a skilled educator. If the goal is to eliminate instructors entirely, this is not our model.
Projects without a content library to build RAG systems from
Student Q&A and adaptive learning systems are only as accurate as the content they are trained on. If your content library does not exist in a structured, digital form, the first project is content digitization.
Consumer tutoring apps without institutional backing
We have a minimum engagement size. Consumer apps with individual user scale and no institutional client layer are better served by existing AI tutoring products than a custom build.

Frequently asked questions.

How do you comply with FERPA when handling student data?: FERPA compliance for AI systems requires treating student education records as protected data, restricting access, maintaining disclosure logs, and ensuring data is not used for purposes beyond the educational service. We configure systems to use student data only for the specific educational function contracted, do not use student data to train or improve underlying models, and can provide a data processing agreement that maps to your FERPA obligations.
Which LMS platforms can you integrate with?: We have integrated AI systems with Canvas, Moodle, Blackboard, Schoology, and several proprietary LMS platforms via LTI integrations and REST APIs. If your LMS supports xAPI or LRS data export, we can build adaptive systems on top of that engagement data. Proprietary LMS platforms with limited API access require a middleware layer.
How do you prevent the AI from giving students wrong answers?: RAG-based student Q&A systems cite the specific source document for every answer, which lets students verify the response. We also configure systems to say 'I do not have information on that' rather than generate unsupported answers. During deployment, we run accuracy benchmarks with your instructional team (testing a sample of real student questions against your content) before go-live.
How do you handle student data privacy beyond FERPA?: For K-12 environments, we design systems to comply with COPPA for students under 13, including parental consent flows and data minimization. For corporate learning platforms, we follow your organization's data governance policies. Student data is never used to train models and is processed only within your contracted system.

Ready to make your content library interactive?

Tell us about your content library and the learner workflow you want to improve. We will reply within one business day with a rough scope and price range.

EdTech companies are sitting on content libraries that AI can finally make interactive.

What we build.

Five specific AI workflows for edtech platforms and learning teams.

Student Q&A from course content

Adaptive quiz and assessment generation

Generate quiz questions, practice problems, and assessments calibrated to learning objectives and student performance history. Varies difficulty based on mastery data without instructor manual work.

Curriculum gap analysis

AI maps your course content against industry skill frameworks, job description requirements, or standards bodies, identifying what is covered, what is missing, and where prerequisites may be unclear.

Instructor lesson planning support

Progress report generation

Who we build for.

Online learning platforms with large course content libraries

Corporate learning and development teams with proprietary training content

K-12 and higher education institutions adding AI to existing LMS infrastructure

EdTech startups building adaptive learning products

Professional certification bodies needing assessment automation

Who this isn't for.

Platforms that want AI to replace instructors

AI works best as a support layer for instructors and students, answering questions, generating practice materials, surfacing gaps. It does not replace the judgment of a skilled educator. If the goal is to eliminate instructors entirely, this is not our model.

Projects without a content library to build RAG systems from

Student Q&A and adaptive learning systems are only as accurate as the content they are trained on. If your content library does not exist in a structured, digital form, the first project is content digitization.

Consumer tutoring apps without institutional backing

We have a minimum engagement size. Consumer apps with individual user scale and no institutional client layer are better served by existing AI tutoring products than a custom build.

Frequently asked questions.

How do you comply with FERPA when handling student data?

FERPA compliance for AI systems requires treating student education records as protected data, restricting access, maintaining disclosure logs, and ensuring data is not used for purposes beyond the educational service. We configure systems to use student data only for the specific educational function contracted, do not use student data to train or improve underlying models, and can provide a data processing agreement that maps to your FERPA obligations.

Which LMS platforms can you integrate with?

We have integrated AI systems with Canvas, Moodle, Blackboard, Schoology, and several proprietary LMS platforms via LTI integrations and REST APIs. If your LMS supports xAPI or LRS data export, we can build adaptive systems on top of that engagement data. Proprietary LMS platforms with limited API access require a middleware layer.

How do you prevent the AI from giving students wrong answers?

RAG-based student Q&A systems cite the specific source document for every answer, which lets students verify the response. We also configure systems to say 'I do not have information on that' rather than generate unsupported answers. During deployment, we run accuracy benchmarks with your instructional team (testing a sample of real student questions against your content) before go-live.

How do you handle student data privacy beyond FERPA?

For K-12 environments, we design systems to comply with COPPA for students under 13, including parental consent flows and data minimization. For corporate learning platforms, we follow your organization's data governance policies. Student data is never used to train models and is processed only within your contracted system.

Ready to make your content library interactive?

Tell us about your content library and the learner workflow you want to improve. We will reply within one business day with a rough scope and price range.