Diffyn VS Noms.sh

Diffyn's answer

Addresses workflow and change management on LLM prompts, provide teams with traceability and visualization of tests across multiple models, provide deeper understading into efficiency of these prompts.

Noms.sh's answer:

One catalog covers 3.7M foods and 298K brands across 230 countries, from generic foods like an apple to packaged supermarket products, with 3.4M barcodes and 566K food images. Names are normalized, units reconciled and duplicates merged before the response reaches you. Each food carries up to 177 nutrients per 100 g or 100 ml.

Diffyn's answer

Diffyn is the platform that specializes on both change management and multi-model analysis.

Noms.sh's answer:

Coverage outside the US, including Latin America, in one API. Clean data without doing the cleanup yourself. A free tier with 250 requests a day and no card, then plans from $29 a month. JSON responses with cursor pagination and RFC 9457 errors, described by an OpenAPI 3.1 document.

Diffyn's answer

React, Next.js, POSTGRESQL

Noms.sh's answer:

Python, PostgreSQL, and Google Cloud.

Diffyn's answer

Professionals incorporating LLMs or AI tools in their workflow and wants to keep track of changes and test their prompts.

Noms.sh's answer:

Developers building food, fitness, nutrition and grocery apps who need reliable nutrition data and barcode lookup without maintaining their own food database.

Diffyn's answer

I started working on Diffyn when I notice that prompting has become an essential part of work across many industries. While there are version control platofrms like github, they are not designed for just prompt management are can be overkill such applications, it is also not integrated natively with various LLMs and relevant tools for users to validate ideas and visualise results properly.

Noms.sh's answer:

Food data is scattered across sources that disagree on names, units and duplicates, and every app ends up redoing the same cleanup. Noms does that work once and serves the result through one API.