Species.app – A visual spaced-repetition engine for taxonomy

Name: Species.app – A visual spaced-repetition engine for taxonomy
Availability: InStock
Author: jchiasson

by jchiasson·Apr 13, 2026·3 points·2 comments

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AI Analysis

●●SolidNiche GemCozy

Spaced-repetition flashcards designed specifically for visual species identification.

Strengths

•Perceptual interleaving shows similar species back-to-back to train visual discrimination skills.
•Curated high-quality image database saves users from creating cards manually in Anki.
•FSRS algorithm optimizes review timing for long-term retention of visual knowledge.

Weaknesses

•Content library is limited to 5K species compared to total global biodiversity.
•Niche audience limits viral growth potential beyond naturalists and biology students.

Post Description

Hi HN,

I’m an amateur naturalist, and I couldn't find good visual content to study for animal/plant taxonomy. Standard text-based flashcards don't work well for visual identification.

So, I built a visual spaced-repetition engine specifically designed to drill taxonomy using perceptual interleaving (showing you visually similar species back-to-back to train your eye).

The stack: SvelteKit / CDK (S3) / Fallback R2 / Postgres

Could probably use some better optimization but it works well enough.

It uses a customized implementation of the FSRS (Free Spaced Repetition Scheduler) algorithm adapted for image-heavy visual drilling.

The hardest part is building out the curated image database. There is planned content for many more species coming soon!

The platform is currently in a 100% free beta.

Would love some feedback, advice, etc if you have time!

https://species.app