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.
Hi Makers!
I'm Steven, one of the founders of Tilores. I've very excited to introduce our LangChain integration to you so you can use Tilores as a data source for "Identity RAG".
As companies increasingly turn to Large Language Models (LLMs) to enhance customer interactions, a common challenge arises: customer data is often fragmented across multiple internal databases and systems. This fragmentation makes it hard for LLMs to provide reliable, accurate responses based on complete, up-to-date information.
Tilores solves this by offering a real-time API that unifies scattered customer data. Originally developed for a European consumer credit bureau to power fraud prevention and anti-money laundering solutions, Tilores' "identity resolution" technology is now available to supercharge LLMs through an integration with LangChain, the leading LLM framework.
With Tilores, you can:
🖇️ Seamlessly connect all your customer data sources, including valuable metadata like orders, transactions, and more.
⚖️ Build a unified "source of truth" for your LLM, ensuring it always has access to complete and relevant customer insights.
⚡ Perform lightning-fast searches and updates, keeping your LLM working with real-time data.
🤖 Use your preferred LLM within your own infrastructure—your data stays securely within your systems.
💾 Enjoy automated scaling, enterprise-grade reliability, and GDPR compliance, all tailored to European data privacy standards.
🙌🏻 Empower your LLMs with unified customer data, and take your AI-driven customer experiences to the next level with Tilores.
Tilores is designed to be used for structured customer data alongside a vector database for unstructured data to give you the ultimate enterprise LLM experience.
For anyone from Product Hunt building a LLM based on Tilores' Identity RAG, we will offer you $500 of free credit to get started.
You can also visit our website: https://tilores.io/RAG
Go straight to the GitHub repo for our LangChain integration: https://github.com/tilotech/lang...
Or read this Medium article for more context about Identity RAG: https://bit.ly/3TSwe22
Exciting -- we are exploring any tech that brings data closer to the user, and AI is the way to go.
Congratulations on the launch. It looks really cool and powerful, and it seems like something that will simplify many use cases.
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!
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!
Happy launch day! 🚀 Can Tilores be customized to work with existing internal infrastructure and databases, or is it a standalone solution?
Getting updates new features through my email is a nice touch. It keeps me informed without overwhelming me with information.
I can finally get comprehensive insights without the headache. I love that I can unify customer records even when attributes differ.
Dynamic customers profiles are so impressive! My LLM can now access accurate data on the fly, which enhances my response accuracy significantly.
How nice is that! That seems like a an amazing piece of technology. Truly innovative! Will test it soon!!!
How does Tilores ensure the privacy and security of sensitive identity data while using RAG models?
congratulations on your launch @major_grooves. How does Tilores ensure the accuracy and consistency of the unified customer data when pulling from multiple sources?
Sounds like a game-changer for managing customer data! Haven't dived in fully yet, but the integration with LangChain seems super handy for anyone working with LLMs. Can't wait to try it out!
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
Congrats to the Tilores team on the launch of Identity RAG! This sounds like a powerful tool for streamlining access to unified customer data. Are there any specific integrations available for different source systems to enhance data retrieval?
Impressive integration with LangChain for unified customer data. This could significantly enhance AI-driven customer experiences. How do you handle data freshness and consistency when aggregating information from multiple sources in real-time?
Wow, @major_grooves, this is truly a game-changer for data scientists and enterprises leveraging LLMs! 🚀 The fragmentation of customer data has always been a significant hurdle, and Tilores seems to offer a seamless and efficient solution to this problem. The fact that it was initially developed for high-stakes environments like fraud prevention and AML really speaks to its robustness and reliability.
Integrating Tilores with LangChain to unify and streamline customer data is brilliant. The potential for enhanced customer interactions and more accurate query responses is immense. Plus, the emphasis on GDPR compliance and data security is crucial for businesses operating within European standards.
The $500 free credit offer is a generous touch and a great incentive for the Product Hunt community to dive in and explore the capabilities of Tilores. Kudos to the team for creating something that can significantly elevate AI-driven customer experiences. Can't wait to see how this transforms the landscape for LLM applications! 🌟
The integration looks super smooth, and the real-time updates feature is something I could really see being useful.
It feels like a great way to ensure LLMs always have access to complete and up-to-date customer data, especially with fragmented data sources being such a common issue.
