Snowflake launches Openflow to speed AI data integration
Snowflake has introduced Snowflake Openflow, a data movement service designed to facilitate data interoperability and accelerate data transfer for artificial intelligence initiatives.
Snowflake Openflow allows users to connect to a wide range of data sources and architectures, streamlining the process of integrating enterprise data ecosystems with AI models, applications, and data agents directly within the Snowflake platform. The service eliminates fragmented data stacks and seeks to reduce the manual effort data teams invest in ingestion tasks. Snowflake says Openflow supports an open, extensible, and managed approach to data integration, enabling unified data management for rapid deployment of AI-powered solutions.
"Snowflake Openflow dramatically simplifies data accessibility and AI readiness. We're seeing more customers adopt an AI-first data strategy, which is dependent on having access to all of your data in a single platform. With Snowflake Openflow, we're redefining what open, extensible, and managed data integration looks like, so our customers can quickly build AI-powered apps and agents without leaving their data behind," Chris Child, Vice President of Product, Data Engineering at Snowflake, said.
Snowflake Openflow is powered by Apache NiFi, an open-source technology for automating the flow of data between systems. This enables engineers to develop custom connectors rapidly and operate them on Snowflake's managed platform. Ready-to-use connectors and processors allow integration from an array of data sources such as Box, Google Ads, Microsoft Dataverse, Microsoft SharePoint, Oracle, Proofpoint, Salesforce Data Cloud, ServiceNow, Workday, and Zendesk, with support for destinations that extend beyond the Snowflake platform.
Customers including Irwin, Securonix, and WorkWave are planning to use these features to move and scale data in their operations, leveraging hundreds of connectors to simplify global data transfer. The platform also includes features such as dbt Projects, improved support for Apache Iceberg tables, and Snowpipe Streaming, all of which are aimed at making data engineering more collaborative and scalable.
With a market opportunity estimated at USD $15 billion, Snowflake Openflow enables businesses to integrate both structured and unstructured, batch and streaming data from virtually any source, whether on-premise or in the cloud. This supports enterprises seeking to establish a single connected view of their data as they build out AI projects, without the complexity of vendor lock-in.
Snowflake's additional data engineering advancements include new capabilities to support dbt Projects natively within Snowflake via a new development environment, Snowflake Workspaces. This facilitates automation, integration with git, and assistance from an AI Copilot. The company has also extended its support for semi-structured data using the VARIANT data type and added optimisations for handling file sizes and partitions, particularly benefiting those managing Apache Iceberg tables.
Improvements to data streaming are also being rolled out, with Snowpipe Streaming now offering a higher throughput of up to 10 gigabytes per second and reduced latency, allowing near real-time data querying following ingestion.
Several partners commented on Snowflake Openflow and their collaborations:
"Our partnership with Snowflake is dedicated to empowering businesses to create exceptional customer experiences through the strategic use of their data. With Snowflake Openflow, our joint customers will be able to seamlessly integrate a wider array of rich customer insights and audience data from Adobe Experience Platform with their broader enterprise data in Snowflake. This will accelerate their ability to unlock more holistic insights and activate them with enhanced agility, powering highly personalised engagements with remarkable efficiency," Justin Merickel, Vice President for Analytics and Technology Partners at Adobe, stated.
"Enterprises today face increasing pressure to unify fragmented data and make it AI-ready, and that starts with seamless, scalable integration. The strategic partnership between Box and Snowflake combines the leading platforms for both their unstructured and structured data to use the power of AI to unlock the value of their data like never before. Together, we're removing the complexity of data integrations so customers can maximise value and accelerate outcomes across the entire content lifecycle," Ben Kus, Chief Technology Officer at Box, said.
"Microsoft is collaborating with Snowflake to make data from Microsoft Dataverse, Dynamics 365 apps, and Power Platform apps easily connected across enterprise data ecosystems through Snowflake Openflow. The ready-to-use connectors make data movement fast, effortless, and secure so customers can reach their full data potential to advance meaningful AI development," Nirav Shah, Corporate Vice President, Dataverse, Microsoft, commented.
"Enterprises today are looking to unlock the full potential of their data, wherever it resides, to drive transformative AI initiatives. Our expanded partnership with Snowflake and the introduction of this new, high-speed connector directly addresses this need. By enhancing the interoperability and performance of data connectivity with the Snowflake AI Data Cloud, we are empowering our joint customers to accelerate their data pipelines to gain faster, more actionable insights that can truly move their businesses forward in the AI era," Jeff Pollock, Vice President of Product Management at Oracle, said.
"AI has drastically increased the volume and velocity of data, making it even more imperative for enterprises to maintain full control and governance over their most valuable asset. Snowflake Openflow ensures that fully interoperable data movement is not only possible, but can be secure at the same time. Proofpoint DSPM enables customers to classify sensitive data inline within Openflow and apply Snowflake tags to it, unlocking a more complete, centralised data landscape so they can innovate confidently and securely," Amer Deeba, Group Vice President, Proofpoint DSPM group, explained.
"The new integration with Snowflake Openflow represents an important enhancement in our existing Zero Copy data integration, actively dismantling these barriers. It empowers joint customers with more functionality to seamlessly and securely access and activate all their data in real time, transforming enterprise data to fuel AI-powered applications and intelligent agents across their operations," Nick Johnston, SVP of Strategic Partnerships and Business Development at Salesforce, remarked.
"As AI adoption increases, there's an increasing need to eliminate data siloes through bi-directional integrations with enterprise data lakes like Snowflake. Through our partnership with Snowflake Openflow and ServiceNow's Workflow Data Network, we're eliminating data siloes so that our customers can reap the benefits of intelligent automation to better power their organisations," Amit Saxena, Vice President and General Manager, Workflow Data Fabric, ServiceNow, said.
"Zendesk powers more than 10,000 AI customers worldwide, delivering real-time, personalised support at scale. Our partnership with Snowflake and the launch of Snowflake Openflow creates an unprecedented, fully-integrated data ecosystem that drives smarter insights and accelerates AI innovation across customer journeys. Together, we're defining the future of AI-powered service and helping businesses transform their customer experience through data-driven intelligence," Tim Marsden, VP of Technology Alliances at Zendesk, commented.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Techday NZ
11 hours ago
- Techday NZ
AI agent adoption rises among IT security leaders in ANZ
IT security leaders in Australia and New Zealand see considerable promise in adopting AI agents to address key security concerns, according to results from the Salesforce State of IT report. The survey of over 2,000 enterprise IT security leaders globally, including 100 from Australia and New Zealand (ANZ), found that every respondent identified at least one security issue they believe could be improved with the use of AI agents. According to the report, 36 per cent of IT security teams in ANZ have already integrated AI agents into their daily operations. This figure is expected to nearly double to 68 per cent within the next two years, signalling a significant upward trend in AI agent deployment across the region. While optimism around the benefits of AI agents is evident, the report also highlights several challenges facing the region's IT security leaders. Notably, 58 per cent of ANZ respondents expressed concerns that their data foundations are not robust enough to fully realise the benefits of agentic AI. An equal proportion are not fully confident that appropriate safeguards and guardrails are in place for the safe deployment of these agents. Despite these concerns, there is momentum towards greater adoption. Security leaders anticipate a range of benefits from AI agents, from enhancing threat detection capabilities to providing more robust auditing of AI model performance. Alice Steinglass, Executive Vice President and General Manager, Salesforce Platform, Integration, and Automation, said: "Trusted AI agents are built on trusted data. IT security teams that prioritise data governance will be able to augment their security capabilities with agents while protecting data and staying compliant." The survey also indicates that up to 75 per cent of IT security leaders in Australia and New Zealand acknowledge that their current security practices require transformation. While 74 per cent see AI agents as offering opportunities to improve compliance, such as with privacy laws, nearly 83 per cent also identified ongoing compliance challenges as a key concern. Cloud security threats, insider risks, and data poisoning—where malicious actors compromise AI training datasets—were listed among the most pressing risks for IT security leaders. In light of these evolving threats, 71 per cent of ANZ organisations expect to increase their security budgets in the coming year. This is only slightly below the global average of 75 per cent, reflecting a broad trend towards higher investment in IT security resources. Complex and changing regulatory environments continue to pose challenges for IT teams aiming to deploy AI agents. Only 48 per cent of ANZ IT security leaders said they are fully confident that they can deploy AI agents in ways that are compliant with relevant regulations and industry standards. Furthermore, 85 per cent of organisations have not yet fully automated their compliance processes, leaving room for error and inefficiency. There are signs of readiness and confidence among ANZ security leaders when it comes to their security and compliance practices. Sixty-one per cent believe their organisations are prepared for the development and implementation of AI agents. This figure is higher than both the Asia-Pacific average of 57 per cent and the global average of 47 per cent, indicating the region's relatively strong position in preparing for the AI era. Maintaining effective data governance is seen as crucial to enabling the successful adoption of AI agents. Nevertheless, more than half of IT security leaders in ANZ are not confident that their organisations have adequate data quality or the right infrastructure required for AI deployment. Globally, CIOs report that budgets for data infrastructure and management are four times greater than those for AI itself, suggesting a focus on laying solid foundations before wider adoption of AI tools. Building trust remains central to the deployment of AI within enterprises. Recent research indicates a decline in general consumer trust, with three-quarters of Australian consumers stating they trust companies less than a year ago. Additionally, 69 per cent believe advances in AI make trust increasingly important. Among ANZ security leaders, 59 per cent have not fully established ethical guidelines for AI use, 68 per cent lack complete confidence in the accuracy and explainability of AI outputs, and 58 per cent do not provide full transparency in the use of customer data for AI purposes. Arizona State University is among the first higher education institutions to implement Salesforce's Agentforce digital labour platform, using trusted autonomous AI agents in operational workflows. The university has placed particular attention on data relevancy as it broadens its AI initiatives, and has adopted Salesforce-acquired backup, recovery, and archiving solutions to address its data management, compliance, and innovation needs. The findings of the Salesforce State of IT report are based on a double-anonymous survey conducted between December 2024 and February 2025 across a broad range of countries including Australia, New Zealand, the United Kingdom, the United States, and others. One hundred respondents represented Australia and New Zealand.
Scoop
12 hours ago
- Scoop
Southern Cross, ASN And OMS Group Sign SX Tasman Express 'SX-TX' Subsea Cable Supply Contract
Southern Cross, Alcatel Submarine Networks and OMS Group have signed the SX Tasman Express 'SX-TX' subsea supply contract, connecting Sydney (Australia) to Auckland (New Zealand). Leveraging ASN's state-of-the-art subsea technology, the Tasman Express subsea cable system will deliver 400 terabits of additional capacity across 16 fibre pairs (FPs) for Southern Cross customers. The subsea cable system will showcase the latest in subsea technology including Open Cable System architecture that will be compatible with future generations of submarine line terminals and optimised latency to support next generation digital applications. The system design includes ASN branching unit technology to facilitate an alternate Australian landing, subject to demand and final design confirmation. In partnership with ASN, OMS Group will lead the marine installation using its latest fleet of vessels. The project is scheduled for completion in 2028. Laurie Miller, President and CEO of Southern Cross Cables Limited, stated, "Tasman Express marks a significant step in enhancing digital infrastructure between Australia and New Zealand. With ASN and OMS's support, this system delivers ultra-high capacity, low-latency fibre connectivity, meeting the evolving demands of AI-driven cloud regions in Sydney and Auckland." Ronnie Lim, Group CEO of OMS Group, added "This partnership underscores our commitment to shaping the future of digital infrastructure in the Asia-Pacific. By deploying the SX-TX system, we are not only reinforcing vital links between Australia and New Zealand but also strengthening the backbone of regional connectivity. OMS Group is proud to play a central role in enabling resilient, high-capacity networks that empower communities and fuel digital economies." Projesh Banerjea, Managing Director, Infrastructure, KKR said, ' OMS Group's collaboration with Southern Cross Cables and ASN marks a meaningful step forward in strengthening the region's digital infrastructure. The SX-TX project brings to bear OMS Group's ability to deliver resilient, high-capacity subsea solutions and ASN's advanced technology to benefit Southern Cross' customers, and underscores OMS Group's commitment to enabling next-generation connectivity across the Asia-Pacific.' Paul Gabla, VP Sales & Marketing, ASN said, 'ASN is delighted to be working again with Southern Cross team and our strategic partner OMS Group. Combining ASN's latest subsea technology with OMS's regional marine expertise, this project will be a transformational infrastructure asset significantly enhancing capacity and resilience across the Tasman Sea for Australia and New Zealand.'
Techday NZ
a day ago
- Techday NZ
Snowflake boosts AI with real-time licensed content access
Snowflake has introduced Cortex Knowledge Extensions, allowing enterprises to supplement their AI agents with real-time, licensed content from third-party publishers, with Stack Overflow among the first partners to join the Snowflake Marketplace. The introduction of Cortex Knowledge Extensions enables enterprise customers to enrich their AI applications and agents with updated, reliable content from publishers such as Stack Overflow, USA TODAY, and Packt. This approach ensures proper attribution and licensing of content, distinguishing it from other systems that use scraped material without consent from original publishers. According to Snowflake, this new capability is designed to address challenges faced by both enterprises and publishers. Enterprises often struggle to gain access to timely external information for their AI systems, limiting accuracy and depth of insight. Meanwhile, publishers are seeking a secure and fair way to allow their content to be used by enterprise AI, with assurance of both compensation and control. "Building powerful AI apps and agents at scale hinges on enterprises having access to a wealth of internal and external data that adds rich context to AI outputs. Snowflake is raising the bar on enterprise-wide collaboration to make it even easier for customers to fuel their AI initiatives with AI-ready data and harness the power of agentic apps — regardless of whether the data and apps reside within their own four walls or come from trusted third-party sources. Our latest innovations enable teams to turn possibilities into reality with data and AI, all without worrying about security and governance risk," Prasanna Krishanan, Head of Apps & Collaboration and Horizon at Snowflake, commented on the launch. With Cortex Knowledge Extensions, publishers are able to list their content, such as news articles, textbooks, and research papers, on the Snowflake Marketplace. Enterprises can then purchase this content and integrate it into their AI-powered apps and agents, including Cortex Agents, Cortex Search, and the soon-to-be-available Snowflake Intelligence. This functionality enables AI systems to provide responses informed by timely and relevant information while allowing publishers to monetise their intellectual property under agreed licensing terms. The mechanism for delivering content through Cortex Knowledge Extensions relies on retrieval-augmented generation and is underpinned by Snowflake's Zero-ETL Sharing functionality. This setup empowers publishers to revoke access to content if necessary, while always displaying clear attribution and links to the original source, thereby enhancing reliability and provenance. Alongside Cortex Knowledge Extensions, Snowflake has introduced Semantic Model Sharing, which is currently in private preview. Semantic Model Sharing allows enterprises to integrate and interact with AI-ready structured data within their Snowflake Cortex AI applications — whether the data originates from internal sources or third-party providers. The use of semantic models helps ensure consistency in how data and business concepts are defined and applied across different systems, contributing to more trustworthy and accurate AI outputs. By mapping internal data to standardised semantic models, enterprises can accelerate insights, support more uniform decision-making, and access industry-standard metrics while maintaining governance and version control. Snowflake reports that these advances are intended to eliminate the manual effort required to create semantic models internally, while supporting high-quality, context-rich, and accurate AI responses. Users can directly interact with their data using Semantic Model Sharing in Cortex AI, including Cortex Analyst, Cortex Agents, and Snowflake Intelligence. In addition to content and model sharing, Snowflake is adding support for Agentic Native Apps in its marketplace. This feature provides customers with access to third-party agentic applications, which can securely combine provider and consumer data within the enterprise's governance framework. Data remains within the customer's environment while agents perform tasks such as portfolio management and optimisation, using proprietary algorithms and datasets. Currently, Snowflake Marketplace connects enterprises with over 750 providers, offering more than 3,000 live data, application, and AI products. The introduction of Agentic Native Apps is intended to give providers new ways to distribute and monetise their offerings while allowing enterprises to drive additional value from their data without compromising privacy or security.
