Nuclia: The Solution to the Enterprise Search Problem?
April 21, 2022
I read an interesting article called “Spanish Startup Nuclia Gets $5.4M to Advance Unstructured Data Search.” The article includes an illustration, presumably provided by Nuclia, which depicts search as a super app accessed via APIs.
Source: Silicon Angle and possibly Nuclia.com. Consult the linked story to see the red lines zip around without bottlenecks. (What? Bottlenecks in content processing, index updating, and query processing. Who ever heard of such a thing?)
Here are some of the highlights — assertions is probably a better word — about the Nuclia technology:
- The system is “AI powered.”
- Nuclia can “connect to any data source and automatically index its content regardless of what format or even language it is in.”
- The system can “discover semantic results, specific paragraphs in text and relationships between data. These capabilities can be integrated in any application with ease.”
- Nuclia can “detect images within unstructured datasets.”
- The cloud-based service can “say one video is X% similar to another one, and so on.”
What makes the Nuclia approach tick? There are two main components:
- The Nuclia vector database which is available via GitHub
- The application programming interface.
The news hook for the search story is that investors have input $5.4 million in seed funding to the company.
Algolia wants to reinvent search. Maybe Nuclia has? Google is search, but it may be intrigued with the assertions about vector embeddings and finding similarities which may be otherwise overlooked. The idea is that the ad for Liberty Mutual might be displayed in YouTube videos about seized yachts by business wizards on one or more lists of interesting individuals. Elastics may want to poke around Nuclia in a quest for adding some new functionality to its search system.
Enterprise search seems to be slightly less dormant than it has been.
Stephen E Arnold, April 21, 2022
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