Beating Google, Meta, and Cohere at Visual Product Search and Spare Parts Identification

nyris embedding models rank first on all benchmark datasets for visual product search and parts identification. They outperform models from Google, Meta, Cohere, Jina AI, and Nomic AI on tasks from spare parts lookup to product recognition. And they do this with 768-dimensional embeddings, smaller than every competitor tested.

Field Service and Aftersales Trends: 10 Real Shifts Defining 2026

We’ve analyzed hundreds of hours of keynotes and panel discussions on Field Service and Aftersales to get the most mentioned trends for 2026. Here are the 10 trends and challenges that are actually shaping the future of Field Service and Aftersales as we head toward 2026.

Field Service and Aftersales Trends 2026

The Search Bar is a Liar

Why does parts identification cost you so much time and expert resources? It is not because your customers or service technicians are lazy. It is because you are forcing them to translate a visual reality into keywords.

How can you use visual search outside of manufacturing?

An exploration of the use of visual search in the plant industry.

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Beating Google, Meta, and Cohere at Visual Product Search and Spare Parts Identification

nyris embedding models rank first on all benchmark datasets for visual product search and parts identification. They outperform models from Google, Meta, Cohere, Jina AI, and Nomic AI on tasks from spare parts lookup to product recognition. And they do this with 768-dimensional embeddings, smaller than every competitor tested.

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