Tecton

How do you give LLMs the context they need? It’s common to start with basic RAG…but you shouldn’t stop there. A vector search alone won’t cut it when your model needs to make decisions using the many different data points in a business, from real-time transactions to recent user activity – not just static documents. Our latest blog post breaks down what’s missing from traditional RAG systems, and what to do next if you want to build LLM-powered apps that use the full range of context. #GenAI #RAG #AI #LLMOps

Ready to dig into our latest AI capabilities? Here's our new blog post on enriching LLMs with real-time context using Tecton! See how to enhance your AI applications with up-to-date information and personalized responses: 🗯️ Learn about enriched prompts for dynamic, context-aware LLM interactions 🔧 Explore features as tools for scalable data retrieval 🔗 See examples of seamless integration with LangChain and LlamaIndex Check out the post to stay ahead in the rapidly evolving world of AI! #AI #MachineLearning #TectonAI

Our Tecton 1.0 release is huge news for ML teams who want to build smarter #AI apps. Want the details? Join our launch event on Tuesday, Sept. 17! You’ll get an unveiling of Tecton's major platform expansion from our founders Michael Del Balso and Kevin Stumpf. You will also hear from Joshua Hansen at Atlassian and Joseph McAllister at Coinbase about how they’re building more intelligent, context-aware AI systems with Tecton. Get your spot here:

Tecton 1.0 is here! So what’s new? Tecton is bringing capabilities that give you everything you need to turn enterprise data into context for AI: ☑️ Give LLMs richer context with a new feature retrieval API ☑️ Turn unstructured data into embeddings ☑️ Use LangChain with Tecton to enhance LLM applications ☑️ Improve your prompts with dynamic prompt management And so much more! Get the details in our 1.0 release blog now  ⤵️

I'm excited to announce the launch of Tecton 1.0, a significant milestone for our team. Tecton now has unified support for predictive ML and generative AI workflows, enabling organizations to build smarter AI applications. From the beginning, our vision has been to address a critical challenge in AI development: effectively leveraging enterprise-specific data. During our time at Uber, my co-founder Kevin and I observed that the most impactful AI systems are those that utilize data unique to the enterprise. Implementing this, however, is often more complex than it appears. This challenge is evident in both predictive ML and generative AI. LLMs are trained on general knowledge but lack specific enterprise data, limiting their effectiveness in production environments. Getting models to a usable level of performance for most use cases requires providing the right inputs—features, tailored prompts, and domain-specific embeddings—that supply necessary context. Our mission at Tecton is to simplify this process by removing the data engineering complexities involved in building, managing, and operationalizing these inputs. This makes it easier to bring smarter applications into production. We started this journey five years ago with a robust feature store. Today, we've evolved into a comprehensive AI data platform that addresses end-to-end data challenges across the AI lifecycle. I'm proud of our team for reaching this milestone and grateful to our customers who are already leveraging rich enterprise context to power intelligent experiences. This launch is a significant step forward for Tecton and our customers. I invite you to check out Tecton 1.0! Learn more here: https://lnkd.in/gs6AvyQ4

Did you hear?! Today we announced Tecton 1.0, our biggest release since we went GA in 2020. Check out this video to get a quick rundown of what’s new. And for the full technical details, tune in to our upcoming webinar: https://lnkd.in/gs_5r_bE

Tecton is expanding beyond its machine learning roots into the generative AI arena with a new release of its data “feature store” platform that the startup says delivers contextual data to the large language models that power GenAI systems. “The whole point is to allow the people building AI to actually build it faster, get to production faster with AI,” Tecton co-founder and CEO Michael Del Balso told Rick Whiting.

Tecton expanded their platform to enhance enterprise #AI applications by integrating real-time contextual data into #LLMs. The team says this is a way to address challenges in deploying generative AI at scale. Tecton https://lnkd.in/ehUHF9rp

Today’s the day: We’re excited to announce Tecton 1.0! 🎉 With 1.0, we’re launching a major expansion of our platform that will change how you build smarter AI applications. Tecton already made it easier to compute, manage, and retrieve AI-ready features from raw data. Now, organizations need to productionize all kinds of AI context, including features, embeddings, prompts and more. Tecton 1.0 brings new capabilities that do just that: abstracting away the engineering needed to turn structured and unstructured data into richer context for both GenAI and predictive ML. This release is a huge milestone – both for us, and for every company productionizing AI. If you’re ready to start building smarter AI apps, this one’s for you. Get the details here! #AI #ML #GenAI #DataEngineering #ProductLaunch #MLOps