Karthik Guruswamy

What happens when you pair LangGraph’s flexibility with Snowflake’s secure, scalable compute? You get a seamless path to production-grade LLM applications. Fabian Hernandez, part of our Infostrux team, walks you through how LangGraph agents can now be executed entirely inside Snowflake using its new LLM function framework. It’s an exciting step forward for anyone building: -LLM agents -Retrieval-augmented generation pipelines -Conversational workflows directly tied to enterprise data This article is a must-read for teams operationalizing AI where it matters most—in the cloud, with governance built in. Explore it here: 👉 https://hubs.ly/Q03ykwlj0 #Snowflake #LLMFunctions #LangGraph #AIWorkflows #GenAI #EnterpriseAI #Infostrux

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New research from Databricks. It's about training enterprise search agents via RL. KARL introduces a multi-task RL approach where agents are trained across heterogeneous search behaviors, constraint-driven entity search, cross-document synthesis, and tabular reasoning. It generalizes substantially better than those optimized for any single benchmark. KARL is Pareto-optimal on both cost-quality and latency-quality trade-offs compared to Claude 4.6 and GPT 5.2. With sufficient test-time compute, it surpasses the strongest closed models while being more cost efficient.

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Data is in the air! With back-to-back Snowflake and Databricks conferences in SF, one thing that resonated is that data is paramount for AI. While everyone's talking about data use in AI innovation, securing data in the age of AI couldn't be more critical. This week, our CTO, Priyanka Tembey, dives deep into why runtime protection is essential for securing data in use within modern AI systems. Discover how Operant's AI Gatekeeper simplifies this complex challenge, making robust AI security achievable: https://lnkd.in/gYcbixSB #AIGatekeeper #SecureAI #AgenticAI #SnowflakeSummit #DataAISummit #DatabricksSummit #AIPrivacy #DataInMotion #Runtime #DataCloud #AIReady #DataTransformation #RealTimeAI #Datasecurity

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Tuning Spark, Ray, or Dask for ML isn’t one-size-fits-all. In a new Domino Blueprint, Principal Solution Architect Sameer Wadkar shows how API-driven scaling complements autoscaling to right-size clusters on demand—cutting idle spend and speeding bursts for GPU/I/O-heavy work. Practical steps, a lightweight Python client, and Helm install included. If you care about FinOps and MLOps, this is for you. Read the blueprint: https://lnkd.in/ga_qJkhC

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This is a clear example of AI infused into the data platform. Partitioning, Z order, V order... they all require knowing the shape of your data and how it will be used in advance. But you don't know. The world is being flipped on its head. Liquid Clustering adapts to use. Your data platform needs to evolve with you.

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In this world of Agents.. how do you ensure that your agent is doing what it's designed to do? Agent Evaluation is one of the core capabilities required for Explainable AI. @Snowflake #Cortex #Agents Evaluation is now GA.

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Starburst has always believed in providing customers with the freedom of choice. Nowhere is this more true than the emerging developments around interoperable compute among data platforms. Recently, I sat down with Snowflake’s Ryan C. Green to talk about the Open Semantic Interchange (OSI), an open, vendor-neutral standard for sharing semantic models across AI, BI, and analytics tools. OSI gives customers a common, open way to define and share business metrics. This helps them stay consistent across dashboards, notebooks, and machine learning models, no matter which tools they use. For Starburst, this furthers one of our core goals. Choice. Customers should be able to keep one trusted set of business definitions inside their Snowflake environment while still having the freedom to choose the tools that work best for them. OSI helps make that possible. It marks an important step in bringing Starburst’s engine to Snowflake-interoperable compute. The video from my chat with Ryan is coming soon 👀 In the meantime, you can get more details from our recent press release: https://lnkd.in/ev2XGB4u #OpenSemanticInterchange #OSI #Interoperability #AI #Data #Snowflake #Starburst

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New in Snowflake: Cortex AISQL & SnowConvert AI Excited about the powerful innovations Snowflake is delivering to help businesses harness AI like never before! 🔷 Cortex AISQL Embed generative AI directly into your SQL queries to analyze structured and unstructured data with ease. 1. Familiar SQL syntax 2. Up to 60% cost savings on data filtering/joining 3. Supports models from OpenAI, Meta, Anthropic & more 🔹 Used by top innovators like #Hex, #Sigma, and #TS Imagine. 🔷 SnowConvert AI Make your data platform migration smarter and safer with AI-powered automation. 1. Migrate from legacy platforms effortlessly 2. Lower manual rework 3. Reduce migration risk at scale Let Celestinfo Software Solutions Pvt. Ltd. help you leverage the full power of these tools for AI-ready data infrastructure. #Snowflake #AISQL #DataEngineering #GenerativeAI #SnowConvert #DataMigration #Celestinfo #AIforBusiness #DigitalTransformation

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With MS releasing Copilot Cowork. Databricks relaunching AI Assistant as Genie Code. The ball is now on Snowflake's court to rename Cortex Code to Cortex Copilot Cowork Code. #satire

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AI doesn't have an intelligence problem. The huge gaps are in memory (continuity) and sensory grounding. Thank you for this post, Babak Mehrabi.

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Great deeply technical presentation by Scott Routledge at PyData Global on how Bodo DataFrames accelerates and scales Pandas code automatically.

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Engineering at Snowflake means solving problems no one has tackled before. For Principal Software Engineer Hyungtae Kim and the Cortex team, that meant designing GPU-powered infrastructure flexible enough to handle any AI workload, at scale. Get a behind-the-scenes look at how the foundation was built, what makes it different, and how it’s powering the next era of GenAI: https://bit.ly/4kKjGVI

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