Skip to content

AI PRODUCT STUDIO · LEARNING & ASSESSMENT

We turn learning and assessment problems into
real product workflows.

RyongWorks is an early-stage studio building AI products and prototypes around real user workflows. PathTutor has a public preview; AI Interview remains in design and development.

AI analysis can be wrong. Review PathTutor results against the original work. AI Interview is not yet released.

PRODUCTS

What you can try and what we are building

We label product status clearly and separate public interfaces from features that are still being designed.

PUBLIC PREVIEWAvailable to explore

PathTutor

Enter a math problem and solution as text or an image, then request an AI review of the work. Check any analysis against the original problem and steps.

IN DEVELOPMENTDesign and development

AI Interview

We are shaping a product for interview and skills assessment around role- and seniority-specific evidence, comparable work samples, transparent criteria, and human review.

View design principles →

HOW WE WORK

Build small. Make limits clear.

Start with a workflow

Define whose work the product should support before choosing technology.

Show evidence and limits

Separate previews, prototypes, and plans. Do not present unverified outcomes as facts.

Keep people accountable

In assessment, prioritize transparent criteria and human review.

SELECTED PROTOTYPE

BuildProof

Hackathon prototype · AI Interview integration is a future plan

BuildProof runs resume-based text technical interviews with project-specific follow-ups. If a candidate reviews the report and consents, a minimized assessment manifest and its salted hash can be recorded in a Solana Devnet Memo transaction. The original resume and full interview transcript are not written on-chain.

This describes the on-chain record only. Check the demo for separate notices about resume and response processing and external AI use.

View BuildProof prototype

OPEN SOURCE

ContextFidelity

A local-first, open-source chat workspace that selects context for each question and preserves the exact context sent to each model call.

It does not measure model attention or establish how much a context item influenced an answer.

View public repository

ABOUT RYONGWORKS

Explore the studio and its project notes.

We distinguish products, prototypes, and future plans.

About RyongWorks

Have a product or collaboration question?

Tell us what you are working on at contact@eunryong.com.

Get in touch