
Fig: Food Scanner & Discovery
Yuka
Spokin
Nutritics
Kaboodle
Snap any menu. Niblu flags risky ingredients and highlights safer dishes so you can order with confidence.
LayerStack’s Arm-based cloud virtual machines, powered by cloud-optimized CPU based on Arm architecture that deliver excellent cost-effective processing power, allowing you to easily complete the most demanding application development.

Website, pricing, platforms and company facts side by side.
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| Website | nib.lu | layerstack.com |
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| Company | Startup from Romania · 1 - 9 employees · 2026 | — |
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In their own words, as submitted to SaaSHub.

Niblu is a menu safety co-pilot for people with allergies, intolerances, and restrictive diets. Snap a menu (photo or PDF), set what you avoid (like dairy, gluten, eggs, nuts, shellfish), and Niblu flags risky dishes and highlights safer picks so you can order with confidence. Unlike...
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What each product offers, as listed by its team.

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An editorial look at what each product does well and who it suits.

Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
Recommended for
How often each product is chosen within a category, 0–100% relative to the other.

As answered by people managing Niblu and LayerStack Arm-based Cloud Server.
Niblu's answer
Niblu is menu-native. It reads real restaurant menus (photos/PDFs), then turns them into a clear decision: Safe, Unsafe, or Uncertain based on your personal allergy/intolerance profile, with the “why” behind each call.
Niblu's answer
Most tools are barcode-first or database-first. Niblu is built for the moment you actually need help: when you’re staring at a menu at the table. It’s fast, personal, and improves over time as you save preferences and react to dishes.
Niblu's answer
People who eat out and need to avoid specific ingredients due to allergies, intolerances, or restrictive diets (dairy-free, gluten-free, egg-free, nut-free, vegan, halal), especially travelers and busy diners.
Niblu's answer
Next.js, TypeScript, React, PostgreSQL, Tailwind CSS, Three.js, plus AI vision + language models for menu understanding.
Niblu's answer
Niblu started from the simple problem: eating out with restrictions is stressful, slow, and easy to mess up. The goal is to make restaurant dining safe and actually enjoyable again, with a tool that reads menus the way humans wish menus were written.
Niblu's answer
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