Boundary AI or FieldDay? A Comprehensive Review

Special config language BAML

Enhances LLM performance

Turns complex templates into functions

Easier test execution

Eliminates parsing boilerplate

Reduces type errors

Instantaneous testing of prompts

Supports various IDEs

Includes VSCode Playground UI

Performance monitoring feature

Creates custom vision apps

Uses camera for productivity

Mobile machine learning toolkit

Teaches apps to 'see'

Real-time accuracy visualization

Identifies multiple objects

Label and manage models

Push model iterations

Available for iOS

Comprehensive usage guide

Requires familiarity with BAML

Reliance on specific IDEs

Paid services for monitoring

Doesn't support non-generative models yet

Deployment limited to Python

TypeScript

Primary codebase in Rust

Requires manual activation for trace publishing

No direct server communication

Possible compatibility issues with other frameworks

Only available on iOS

Potential for privacy concerns

Data collection reliant on users

Limited algorithm refinement control

Requires able smartphone camera

Manual data labelling needed

Real-time accuracy might vary

Single tap might miss-label

No mention of API Integration