Chris Conlee

I built PictaBase to solve the "dumb folder" problem in high-stakes visual workflows. In film production, finding a specific continuity shot across thousands of files is an operational bottleneck. This platform treats photos as relational data, not just files.

The Technical Footprint (May 2026)

This is not a thin wrapper. It is a professional-grade application built with a strict quality gate:

• Backend: 287 PHP 8.4+ files (38,500 lines) enforced at PHPStan Level 8.

• Frontend: 131 TS/TSX files (26,967 lines) using React 19 and Vite 7.

• Database: 17 custom tables managed via dbDelta() with synchronous schema-version locking.

• Coverage: 488 PHPUnit tests and 1,741 assertions pinning the business logic.

Hi Product Hunt. I m Chris. I spent three decades in film editing suites [IMDb here].

I built PictaBase because I got tired of managing production photos in "dumb" folders. Finding specific assets across thousands of files like a prop from a specific scene is a major bottleneck in our industry.

I am a solo developer. I used an adversarial AI development loop to build a platform with real engineering rigor:

• Pixel-blind server: Image bytes go directly from your browser to S3 via presigned POST.

• Sidecar metadata: All tags, notes, and AI labels are written to .meta.json files in your own bucket.

• Technical baseline: 287 PHP files (38,500 lines) with 100% strict_types and PHPStan Level 8.

A few months ago, we noticed something in our data that most product teams would panic about: a group of users who had been highly active for weeks suddenly went quiet. No crashes. No angry support tickets. They just stopped showing up.

The instinct was to win them back. Send a re-engagement email. Offer a new feature. Maybe a push notification saying "We miss you!"