EdTech & Learning

Learning Paths That Adapt in Real-Time

PULSE infers learner type, pace, and goals from behavior, not just quiz scores. Recommend the right course, adapt difficulty dynamically, and keep learners engaged through personalized paths.

+45% completion rateaverage improvement

Problems We Solve

One-size-fits-all course recommendations that ignore skill level

High dropout rates from mismatched difficulty

Static learning paths that don't adapt to learner pace

Cold start for new learners with no completion history

See It In Action

Course Recommendation

The Career Switcher

A career counselor meets someone who's been in marketing for 5 years but wants to move into data science. They don't suggest 'Marketing 101', they say: 'Start with Python for Data Analysis, then SQL.'

Signals Detected

├──Browsing:Python courses (multiple)
├──Profile:No tech background (inferred)
├──Referrer:"career change into tech" article
├──Behavior:Comparing syllabus content
Persona Detected89% confidence

Career-Switching Learner

Result

Recommends 'Python for Data Science' not 'Python 101', matches career intent.

+38% enrollmentConversion Lift

How PULSE Works for EdTech & Learning

Step 1

Observe

Capture non-invasive behavioral signals from your platform, device, referrer, time, geo, and engagement patterns.

Step 2

Infer

Build a real-time persona using Bayesian inference. Understand intent, preferences, and context in milliseconds.

Step 3

Deliver

Match the inferred persona to your content via vector space. Serve personalized responses via API in <50ms.

Integration

Learning Path API and Course Recommendation SDK. LTI integration for LMS platforms.

Drop-in SDK
RESTful API
Webhook events
OpenAPI spec

Ready to Personalize Your EdTech & Learning Experience?

Get a free audit tailored to your industry. We'll show you exactly what PULSE can do with your data.