• 

  Landing Page

Inspiration

BirdISeeYou was inspired by the challenges field researchers and bird watchers face when trying to select the right observation protocol. We wanted to eliminate manual lookup and errors by using AI that understands natural language, turning simple observations into structured research data.

What it does

BirdISeeYou lets users describe what they observed in plain English, for example, “record for 0–9 mins, 25 to 100m Flyover.” The system parses the input, identifies time, distance, and behavior, and automatically matches or creates the correct observation protocol. If no exact match exists, BirdISeeYou can generate a new one and export it instantly in YAML or JSON format.

How we built it

We built BirdISeeYou using:

Frontend: React + TailwindCSS for a sleek, dark-themed UI.

Backend: FastAPI for efficient routing and AI-driven matching logic.

AI Engine: Uses NLP and fuzzy logic via Python’s SequenceMatcher to compare normalized observation keys.

Database: Persistent JSON storage with instant export capability.

Mathematically, our similarity function is defined as:

similarity

SequenceMatcher(𝑎,𝑏).ra𝑡𝑖𝑜()similarity=SequenceMatcher(a,b).ratio() If similarity<0.55 similarity<0.55, a new protocol suggestion is made.

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for BirdISeeYou - AI-Powered Bird Observation Protocol Finder

Built With

• control:
• css-frameworks:-react
• export/json-tools-&-platforms:-node.js
• fastapi-styling:-tailwindcss-(dark-mode-ui)-ai-&-logic:-python-nlp
• fuzzy-matching-(sequencematcher)-database:-json-(persistent-local-storage)-apis:-custom-rest-endpoints-?-/search
• git
• github
• html
• javascript
• languages:-python
• protocols
• uvicorn
• version
• vite
• yaml