Latest news with #BarisGultekin
Economic Times
15 hours ago
- Business
- Economic Times
Enterprises using AI as returns outweigh costs: Snowflake executive
Live Events There is no shortage of demand in AI as enterprises see return on investments by increasing productivity, reducing cost and automating more things even amid tough macroeconomic conditions, said Baris Gultekin, head of AI at Snowflake This also comes at the back increasing return on investments their customers are seeing. According to a recent report from Snowflake, for every dollar spent on AI, there is a 45% return on the investment.'We are seeing a lot of productivity gains. Ability to do things that used to take a long time is now possible. Certain things that used to require a lot of expertise are now easily accessible to others. So the ROI is clearly measured by our customers. Everyone is very cost conscious, and then they are very clearly seeing the returns on their investments,' Gultekin it comes to the Indian market, Gultekin said while the firm does not have specific India-focused products, multimodal and multilingual data benefits their products as well, he said. The company is also doing proof of concepts (POCs) with customers and working with them to build their applications to improve the return on investment on is also partnering with companies in the services industry. 'For instance, we have our own systems integrator partners that we work very closely with. They're all building solutions for joint customers. Ultimately, AI is moving so fast, and everyone is trying to run as fast as possible. Partnering with others who can bring expertise to a wide range of customers, is something we'd like to do, and we do,' he services are one the biggest customers for Snowflake, where they analyse large amounts of data. The company is also seeing a lot of demand from insurance and healthcare, where significant paperwork is involved and can be analysed to bring in efficiency. 'We are seeing demand in manufacturing and retail across the board. This is actually interesting because it's not really concentrated on a single industry,' Gultekin are a few challenges for the enterprise sector. 'Many companies are building products, and they need to make sure that they're able to evaluate them and observe them before they can get them ready for large-scale production,' Gultekin big challenge is data. 'AI is data hungry. Our customers need to be able to break down these data silos, to make sure that they're able to govern that access,' Gultekin the costs are coming down, GPUs are expensive, as companies host LLM models. 'We are optimising our usage and utilisation of these GPUs. Couple of weeks ago, we released an optimised version of Llama 3.1, where we were able to reduce the costs by 70% or so. We reflected that reduction back to the customer. So being able to take advantage of the open-source ecosystem and optimise how these models are used, allows us to reduce the cost to us, and then reflect the benefits back to the customer,' Gultekin said.
Time of India
17 hours ago
- Business
- Time of India
Enterprises using AI as returns outweigh costs: Snowflake executive
Snowflake, listed in the New York stock exchange, is an AI data cloud platform with $3.5 billion in product revenue in FY25, and is doubling down on AI through partnerships with firms such as Canva and investments across products and people. Tired of too many ads? Remove Ads Tired of too many ads? Remove Ads There is no shortage of demand in AI as enterprises see return on investments by increasing productivity, reducing cost and automating more things even amid tough macroeconomic conditions, said Baris Gultekin, head of AI at Snowflake This also comes at the back increasing return on investments their customers are seeing. According to a recent report from Snowflake, for every dollar spent on AI, there is a 45% return on the investment.'We are seeing a lot of productivity gains. Ability to do things that used to take a long time is now possible. Certain things that used to require a lot of expertise are now easily accessible to others. So the ROI is clearly measured by our customers. Everyone is very cost conscious, and then they are very clearly seeing the returns on their investments,' Gultekin it comes to the Indian market, Gultekin said while the firm does not have specific India-focused products, multimodal and multilingual data benefits their products as well, he said. The company is also doing proof of concepts (POCs) with customers and working with them to build their applications to improve the return on investment on is also partnering with companies in the services industry. 'For instance, we have our own systems integrator partners that we work very closely with. They're all building solutions for joint customers. Ultimately, AI is moving so fast, and everyone is trying to run as fast as possible. Partnering with others who can bring expertise to a wide range of customers, is something we'd like to do, and we do,' he services are one the biggest customers for Snowflake, where they analyse large amounts of data. The company is also seeing a lot of demand from insurance and healthcare, where significant paperwork is involved and can be analysed to bring in efficiency. 'We are seeing demand in manufacturing and retail across the board. This is actually interesting because it's not really concentrated on a single industry,' Gultekin are a few challenges for the enterprise sector. 'Many companies are building products, and they need to make sure that they're able to evaluate them and observe them before they can get them ready for large-scale production,' Gultekin big challenge is data. 'AI is data hungry. Our customers need to be able to break down these data silos, to make sure that they're able to govern that access,' Gultekin the costs are coming down, GPUs are expensive, as companies host LLM models. 'We are optimising our usage and utilisation of these GPUs. Couple of weeks ago, we released an optimised version of Llama 3.1, where we were able to reduce the costs by 70% or so. We reflected that reduction back to the customer. So being able to take advantage of the open-source ecosystem and optimise how these models are used, allows us to reduce the cost to us, and then reflect the benefits back to the customer,' Gultekin said.
Techday NZ
03-06-2025
- Business
- Techday NZ
Snowflake launches AI agents to ease enterprise data access
Snowflake has introduced new agentic AI features and expanded its enterprise-grade AI capabilities, aiming to enhance data analysis and machine learning (ML) workflows for businesses in Canada and worldwide. Snowflake Intelligence, set to enter public preview soon, provides business users and data professionals with a unified conversational interface driven by intelligent data agents. This development enables users to pose natural language questions and quickly access actionable insights from both structured and unstructured data. The company has also announced Data Science Agent, currently in private preview, which acts as an agentic companion designed to assist data scientists by automating routine ML model development tasks. These additions are intended to streamline AI and ML workflows, widen access to data within enterprises, and remove the technical barriers that traditionally slow business decision-making through natural language interactions within Snowflake. "AI agents are a major leap from traditional automation or chatbots, but in order to deploy them at scale, businesses need an AI-ready information ecosystem. This means enterprises must be able to unite data silos, maintain enterprise-grade security and compliance, and have easy ways to adopt and build agents. Snowflake Intelligence breaks down these barriers by democratizing the ability to extract meaningful intelligence from an organization's entire enterprise data estate — structured and unstructured data alike. This isn't just about accessing data, it's about empowering every employee to make faster, smarter decisions with all of their business context at their fingertips," Baris Gultekin, Head of AI at Snowflake, said, commenting on the evolution of AI agents. Organisations frequently face difficulties in decision-making due to fragmented data governance, separate data formats, and a lack of technical analysts. Snowflake Intelligence addresses these issues by enabling business teams and non-technical users to interact conversationally with their enterprise data, all without needing to write code. Snowflake Intelligence operates within the user's existing Snowflake environment, inheriting all established security controls, data masking, and governance policies. It consolidates data from multiple sources, including Snowflake, Box, Google Drive, Workday, and Zendesk, via Snowflake Openflow, allowing users to retrieve insights from spreadsheets, documents, images, and databases simultaneously. Data agents can create visualisations and help users act on insights through natural language prompts. The platform also provides access to external knowledge via Cortex Knowledge Extensions available on Snowflake Marketplace, with content provided by sources such as CB Insights, Packt, Stack Overflow, The Associated Press, and USA TODAY, to add further depth and context to responses. The system is powered by large language models from Anthropic and OpenAI and is built on Cortex Agents, currently in public preview. All are presented through a no-code interface that seeks to ensure transparency and explainability in the use of AI. "By integrating Claude's reasoning capabilities directly into Snowflake's platform, we're further eliminating the traditional barriers between data and insights. Business users can now have natural conversations with their enterprise data, while data scientists can automate complex ML workflows — all through simple natural language interactions. This demonstrates how Claude's advanced reasoning can democratize AI while maintaining the enterprise-grade security and governance that organizations require," Michael Gerstenhaber, VP of Product Management at Anthropic, said, highlighting the integration's potential. Snowflake Intelligence is aimed at moving organisations away from reliance on analytics teams for insights, enabling broader employee access to data. "At WHOOP, our mission is to unlock human performance and healthspan, and data is central to everything we do. Snowflake Intelligence marks a big step forward in our ability to be a data-first organisation, ensuring that all employees can access insights without relying on analytics teams as the intermediary. By eliminating the technical barriers to gleaning the insights we need for decision-making, our analytics teams can now shift from manual data retrieval tasks to more strategic, predictive, and value-generating work," Matt Luizzi, Sr. Director of Business Analytics at WHOOP, said. To support data scientists, Snowflake's Data Science Agent automates time-consuming tasks linked to ML workflows. The agent, also using Anthropic's Claude, segments ML workflow challenges into separate steps such as data analysis, preparation, feature engineering, and training. It leverages advanced reasoning, contextual understanding, and action execution to generate validated ML pipelines that can be run from a Snowflake Notebook. Users can iterate with suggested improvements or follow-ups, helping to reduce time spent on experimentation or debugging. Currently, more than 5,200 customers, including companies such as BlackRock, Luminate, and Penske Logistics, are using Snowflake Cortex AI as part of their business operations. Snowflake is introducing several new AI features, such as enhanced document processing, batch semantic search, and the new Cortex AISQL, now available in public preview, aiming to facilitate analysis of multi-modal data at scale and assist teams that may lack extensive AI engineering skills.
Yahoo
03-06-2025
- Business
- Yahoo
Snowflake Intelligence and Data Science Agent Deliver The Next Frontier of Data Agents for Enterprise AI and ML
Business users can now harness AI data agents to analyze, understand, and act on structured and unstructured data with Snowflake Intelligence, without technical overhead Data scientists can leverage Data Science Agent to automate their ML workflows, boost productivity, and accelerate time-to-production for ML use cases Over 5,200 customers from companies like BlackRock, Luminate, and Penske Logistics are using Snowflake to deploy AI solutions across their businesses SAN FRANCISCO, June 03, 2025--(BUSINESS WIRE)--Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced at its annual user conference, Snowflake Summit 2025, new agentic AI innovations that bridge the gap between enterprise data and business action, making AI and ML workflows easy, connected, and trusted for technical and non-technical users alike. Snowflake Intelligence (public preview soon) offers business users and data professionals a unified conversational experience — powered by intelligent data agents — to ask natural language questions and instantly uncover actionable insights from both structured tables and unstructured documents. Snowflake is also unveiling Data Science Agent (private preview soon), an agentic companion that boosts data scientists' productivity by automating routine ML model development tasks. These innovations enable users to simplify their AI and ML workflows, democratize access to data across their businesses, and eliminate the technical overhead that slows down business decision-making — all through natural language interactions within Snowflake. "AI agents are a major leap from traditional automation or chatbots, but in order to deploy them at scale, businesses need an AI-ready information ecosystem. This means enterprises must be able to unite data silos, maintain enterprise-grade security and compliance, and have easy ways to adopt and build agents," said Baris Gultekin, Head of AI, Snowflake. "Snowflake Intelligence breaks down these barriers by democratizing the ability to extract meaningful intelligence from an organization's entire enterprise data estate — structured and unstructured data alike. This isn't just about accessing data, it's about empowering every employee to make faster, smarter decisions with all of their business context at their fingertips." "At WHOOP, our mission is to unlock human performance and healthspan, and data is central to everything we do. Snowflake Intelligence marks a big step forward in our ability to be a data-first organization, ensuring that all employees can access insights without relying on analytics teams as the intermediary," said Matt Luizzi, Sr. Director of Business Analytics, WHOOP. "By eliminating the technical barriers to gleaning the insights we need for decision-making, our analytics teams can now shift from manual data retrieval tasks to more strategic, predictive, and value-generating work." Snowflake Intelligence Reimagines Business Intelligence, Without the Overhead Today, organizations are plagued by inefficient decision-making due to disjointed data governance, silos between data formats, and a shortage of technical data analysts who can code and synthesize information across the business. Snowflake Intelligence eliminates these operational challenges, allowing non-technical users and business teams to have conversations with their enterprise data in natural language — all without writing a single line of code. Running directly inside organizations' existing Snowflake environment, Snowflake Intelligence inherits all security controls, data masking, and governance policies automatically. It unifies data across sources including Snowflake, Box, Google Drive, Salesforce Data Cloud via Zero Copy, Workday, Zendesk, and more, using the new Snowflake Openflow to bring together insights from spreadsheets, documents, images, and databases simultaneously. By leveraging natural language prompts, the data agents powering Snowflake Intelligence can generate visualizations and assist users in taking action on insights. From analyzing business metrics to looking up helpful internal knowledge, Snowflake Intelligence enables every employee to easily access and harness the full potential of their company's data. Snowflake Intelligence can also access third-party knowledge through Cortex Knowledge Extensions (generally available soon) on Snowflake Marketplace, and incorporate expert content from Packt, Stack Overflow, the USA TODAY Network, and more to further contextualize and enrich responses. Snowflake Intelligence is powered by state-of-the-art large language models from Anthropic and OpenAI, running inside the Snowflake perimeter, and is powered by Cortex Agents (generally available soon) under the hood — all delivered through an intuitive, no-code interface that helps provide transparency and explainability. "By integrating Claude's reasoning capabilities directly into Snowflake's platform, we're further eliminating the traditional barriers between data and insights. Business users can now have natural conversations with their enterprise data, while data scientists can automate complex ML workflows — all through simple natural language interactions," said Michael Gerstenhaber, VP, Product Management, Anthropic. "This demonstrates how Claude's advanced reasoning can democratize AI while maintaining the enterprise-grade security and governance that organizations require." Data Science Agent Automates Tedious ML Tasks, Saving Hours of Manual Work Data scientists spend lengthy cycles on developing and troubleshooting their ML workflows, leading to operational bottlenecks and fewer ML models making their way to production. Now, Snowflake is bringing agentic AI to ML workflows with Data Science Agent to boost productivity for ML teams by slashing hours of manual work. Data Science Agent uses Anthropic's Claude to break down problems associated with ML workflows into distinct steps, such as data analysis, data preparation, feature engineering, and training. Combining advanced techniques such as multi-step reasoning, contextual understanding, and action execution, Data Science Agent provides verified solutions in the form of fully functional ML pipelines that can be easily executed from a Snowflake Notebook. With suggested improvements, or with user provided follow-ups, Data Science Agent helps users easily iterate to the next-best version. By automating this tedious work, data science teams save hours of time that they would typically spend on experimentation or debugging — and can instead focus on higher-impact initiatives. Snowflake Accelerates Enterprise AI Adoption for More Than 5,200 Customers Today, over 5,200¹ customers from companies like BlackRock, Luminate, and Penske Logistics are using Snowflake Cortex AI to transform their businesses. To further empower users to harness the power of AI, Snowflake is also announcing new innovations in AI building blocks for advanced conversational apps, unstructured data analytics, and ML. Teams can explore and analyze multi-modal data at scale with enhanced document processing, batch semantic search, and the new Cortex AISQL (now in public preview) to bridge the gap between data analysts and AI engineering skills. Learn More: Double click into how Snowflake Intelligence is democratizing access to data in this blog post. Read more about how Snowflake is making it faster and easier to build and deploy agentic AI apps on enterprise data in this blog post. Learn more about how global organizations can get started with AI data agents today and define an ROI framework to measure business impact in this A Practical Guide to AI Agents ebook. Check out all the innovations and announcements coming out of Snowflake Summit 2025 on Snowflake's Newsroom. Stay on top of the latest news and announcements from Snowflake on LinkedIn and X, and follow along at #SnowflakeSummit. 1. As of May 21, 2025. Forward Looking Statements This press release contains express and implied forward-looking statements, including statements regarding (i) Snowflake's business strategy, (ii) Snowflake's products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, and (iv) the integration, interoperability, and availability of Snowflake's products with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading "Risk Factors" and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. As a result, you should not rely on any forward-looking statements as predictions of future events. © 2025 Snowflake Inc. All rights reserved. Snowflake, the Snowflake logo, and all other Snowflake product, feature and service names mentioned herein are registered trademarks or trademarks of Snowflake Inc. in the United States and other countries. All other brand names or logos mentioned or used herein are for identification purposes only and may be the trademarks of their respective holder(s). Snowflake may not be associated with, or be sponsored or endorsed by, any such holder(s). About Snowflake Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 11,000 companies around the globe, including hundreds of the world's largest, use Snowflake's AI Data Cloud to build, use, and share data, apps and AI. With Snowflake, data and AI are transformative for everyone. Learn more at (NYSE: SNOW). View source version on Contacts Media Contacts: Lindsey ShepardProduct PR Specialist, Snowflakepress@ Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Business Wire
03-06-2025
- Business
- Business Wire
Snowflake Intelligence and Data Science Agent Deliver The Next Frontier of Data Agents for Enterprise AI and ML
SAN FRANCISCO--(BUSINESS WIRE)-- Snowflake (NYSE: SNOW), the AI Data Cloud company, today announced at its annual user conference, Snowflake Summit 2025, new agentic AI innovations that bridge the gap between enterprise data and business action, making AI and ML workflows easy, connected, and trusted for technical and non-technical users alike. Snowflake Intelligence (public preview soon) offers business users and data professionals a unified conversational experience — powered by intelligent data agents — to ask natural language questions and instantly uncover actionable insights from both structured tables and unstructured documents. Snowflake is also unveiling Data Science Agent (private preview soon), an agentic companion that boosts data scientists' productivity by automating routine ML model development tasks. These innovations enable users to simplify their AI and ML workflows, democratize access to data across their businesses, and eliminate the technical overhead that slows down business decision-making — all through natural language interactions within Snowflake. 'AI agents are a major leap from traditional automation or chatbots, but in order to deploy them at scale, businesses need an AI-ready information ecosystem. This means enterprises must be able to unite data silos, maintain enterprise-grade security and compliance, and have easy ways to adopt and build agents," said Baris Gultekin, Head of AI, Snowflake. "Snowflake Intelligence breaks down these barriers by democratizing the ability to extract meaningful intelligence from an organization's entire enterprise data estate — structured and unstructured data alike. This isn't just about accessing data, it's about empowering every employee to make faster, smarter decisions with all of their business context at their fingertips." 'At WHOOP, our mission is to unlock human performance and healthspan, and data is central to everything we do. Snowflake Intelligence marks a big step forward in our ability to be a data-first organization, ensuring that all employees can access insights without relying on analytics teams as the intermediary,' said Matt Luizzi, Sr. Director of Business Analytics, WHOOP. 'By eliminating the technical barriers to gleaning the insights we need for decision-making, our analytics teams can now shift from manual data retrieval tasks to more strategic, predictive, and value-generating work.' Snowflake Intelligence Reimagines Business Intelligence, Without the Overhead Today, organizations are plagued by inefficient decision-making due to disjointed data governance, silos between data formats, and a shortage of technical data analysts who can code and synthesize information across the business. Snowflake Intelligence eliminates these operational challenges, allowing non-technical users and business teams to have conversations with their enterprise data in natural language — all without writing a single line of code. Running directly inside organizations' existing Snowflake environment, Snowflake Intelligence inherits all security controls, data masking, and governance policies automatically. It unifies data across sources including Snowflake, Box, Google Drive, Salesforce Data Cloud via Zero Copy, Workday, Zendesk, and more, using the new Snowflake Openflow to bring together insights from spreadsheets, documents, images, and databases simultaneously. By leveraging natural language prompts, the data agents powering Snowflake Intelligence can generate visualizations and assist users in taking action on insights. From analyzing business metrics to looking up helpful internal knowledge, Snowflake Intelligence enables every employee to easily access and harness the full potential of their company's data. Snowflake Intelligence can also access third-party knowledge through Cortex Knowledge Extensions (generally available soon) on Snowflake Marketplace, and incorporate expert content from Packt, Stack Overflow, the USA TODAY Network, and more to further contextualize and enrich responses. Snowflake Intelligence is powered by state-of-the-art large language models from Anthropic and OpenAI, running inside the Snowflake perimeter, and is powered by Cortex Agents (generally available soon) under the hood — all delivered through an intuitive, no-code interface that helps provide transparency and explainability. 'By integrating Claude's reasoning capabilities directly into Snowflake's platform, we're further eliminating the traditional barriers between data and insights. Business users can now have natural conversations with their enterprise data, while data scientists can automate complex ML workflows — all through simple natural language interactions,' said Michael Gerstenhaber, VP, Product Management, Anthropic. 'This demonstrates how Claude's advanced reasoning can democratize AI while maintaining the enterprise-grade security and governance that organizations require.' Data Science Agent Automates Tedious ML Tasks, Saving Hours of Manual Work Data scientists spend lengthy cycles on developing and troubleshooting their ML workflows, leading to operational bottlenecks and fewer ML models making their way to production. Now, Snowflake is bringing agentic AI to ML workflows with Data Science Agent to boost productivity for ML teams by slashing hours of manual work. Data Science Agent uses Anthropic's Claude to break down problems associated with ML workflows into distinct steps, such as data analysis, data preparation, feature engineering, and training. Combining advanced techniques such as multi-step reasoning, contextual understanding, and action execution, Data Science Agent provides verified solutions in the form of fully functional ML pipelines that can be easily executed from a Snowflake Notebook. With suggested improvements, or with user provided follow-ups, Data Science Agent helps users easily iterate to the next-best version. By automating this tedious work, data science teams save hours of time that they would typically spend on experimentation or debugging — and can instead focus on higher-impact initiatives. Snowflake Accelerates Enterprise AI Adoption for More Than 5,200 Customers Today, over 5,200¹ customers from companies like BlackRock, Luminate, and Penske Logistics are using Snowflake Cortex AI to transform their businesses. To further empower users to harness the power of AI, Snowflake is also announcing new innovations in AI building blocks for advanced conversational apps, unstructured data analytics, and ML. Teams can explore and analyze multi-modal data at scale with enhanced document processing, batch semantic search, and the new Cortex AISQL (now in public preview) to bridge the gap between data analysts and AI engineering skills. Learn More: 1. As of May 21, 2025. Forward Looking Statements This press release contains express and implied forward-looking statements, including statements regarding (i) Snowflake's business strategy, (ii) Snowflake's products, services, and technology offerings, including those that are under development or not generally available, (iii) market growth, trends, and competitive considerations, and (iv) the integration, interoperability, and availability of Snowflake's products with and on third-party platforms. These forward-looking statements are subject to a number of risks, uncertainties and assumptions, including those described under the heading 'Risk Factors' and elsewhere in the Quarterly Reports on Form 10-Q and the Annual Reports on Form 10-K that Snowflake files with the Securities and Exchange Commission. In light of these risks, uncertainties, and assumptions, actual results could differ materially and adversely from those anticipated or implied in the forward-looking statements. As a result, you should not rely on any forward-looking statements as predictions of future events. © 2025 Snowflake Inc. All rights reserved. Snowflake, the Snowflake logo, and all other Snowflake product, feature and service names mentioned herein are registered trademarks or trademarks of Snowflake Inc. in the United States and other countries. All other brand names or logos mentioned or used herein are for identification purposes only and may be the trademarks of their respective holder(s). Snowflake may not be associated with, or be sponsored or endorsed by, any such holder(s). About Snowflake Snowflake is the platform for the AI era, making it easy for enterprises to innovate faster and get more value from data. More than 11,000 companies around the globe, including hundreds of the world's largest, use Snowflake's AI Data Cloud to build, use, and share data, apps and AI. With Snowflake, data and AI are transformative for everyone. Learn more at (NYSE: SNOW).
