Customer data search, unification and retrieval for LLMs

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Tilores Identity RAG - Customer data search, unification and retrieval for LLMs

Tilores

•1yr ago

Data scientists connect Tilores to their LLM to search internal customer data scattered across multiple source systems. The LLM retrieves unified customer data, which it uses to answer queries or as context when querying subsequent unstructured data.

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Surfsite AI

Congratulations Tilores! Data scientists can now seamlessly link LLMs to scattered internal customer data, ensuring smarter queries and better results. This is a game-changer! 💡 #AIInnovation #DataIntegration

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1yr ago

Tilores

Maker

@andreea_staicu thank you

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1yr ago

Tilores

Maker

@andreea_staicu thanks for your support.

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1yr ago

congratulations on your launch @major_grooves. How does Tilores ensure the accuracy and consistency of the unified customer data when pulling from multiple sources?

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1yr ago

Tilores

Maker

@major_grooves @zishaniqbal the data is normalized and transformed before matching. Also certain attributes can get prioritized. Let us jump onto a call if you have further questions.

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1yr ago

Tilores

Maker

@zishaniqbal good question. We have a pretty sophisticated, predominantly rules-based matching engine that uses various fuzzy matching algorithms, such as Cosine similarity, to do matching on strings, such as name. We also have ML based matching. The accuracy of the matching depends on how well the rules are set - but the important thing is that the rules that are used for matching are also mentioned in the identity graph, so they are highly explainable.

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1yr ago

AccessOwl

How nice is that! That seems like a an amazing piece of technology. Truly innovative! Will test it soon!!!

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1yr ago

Tilores

Maker

@mathias_n we can even get you set up and running in person in Berlin!

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1yr ago

Steven, as a data scientist constantly battling fragmented customer info, Tilores Identity RAG feels like the missing puzzle piece I didn't know I needed. Your solution's ability to seamlessly integrate with multiple data sources and create that unified 'source of truth' is not just technologically impressive—it's a relief for those of us striving for hyper-personalized customer experiences. The fact that Tilores can keep up with real-time updates and is tailored for European data privacy standards is a huge plus. It's fantastic to see a tool that not only streamlines data handling but also respects the intricate web of GDPR compliance. Kudos on that front! One question that pops up is how flexible Tilores is in adapting to different LLM frameworks beyond LangChain? And for those of us diving deep, are there any plans to introduce advanced analytics or visualizations to help us better understand customer patterns? Excited to give it a spin and see how it elevates our LLM's performance. That $500 credit offer is a generous nudge to kickstart the journey. Heading over to the GitHub repo now!

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1yr ago

Tilores

Maker

@frank_petron we can also work with Bedrock, which es effectively AWS's framework. As for other frameworks, we would certainly integrate with more if there is demand. Let us know how you get on with the integration! We are happy to jump onto a call to help you 1:1.

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1yr ago

It's so amazing! I'm thinking about how to integrate RAG into my website https://quitporn.ai. And today I found your tool. It's a perfect example for me to learn and use. Congrats to your team!

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1yr ago