Athena OS

01 · CHALLENGE

AI projects need useful, well-organized labels before models can produce useful results—especially for local dialects and carefully drawn image annotations.

02 · ROLE

Founder / builder — product direction, labeling workflows, and public technical writing.

03 · DESIGN DECISIONS

• Keep people in the loop: AI drafts labels; humans decide what becomes training data.
• Support both speech (timestamped segments + speakers) and image annotation (boxes and masks) in one platform story.
• Publish openly so teams can inspect, adapt, and contribute rather than treating labeling as a black box.

04 · SCREENSHOTS / MEDIA

CURRENT STATE

Public product surface and technical field notes are live. Treat the product as a working prototype under active development—not a finished commercial claim.

WHAT I LEARNED

• Dialect speech needs reviewers who understand the language; auto-transcription is a starting point, not ground truth.
• Assisted CV works best when one careful label teaches drafts across a set that humans still review.

BUILD RECEIPTS

• productAthena product
• noteOpen-source labeling overview
• noteLabel-one / review-rest
• demoGuided demo room