Latest news with #Snowflake
Business Wire
a day ago
- Business
- Business Wire
Three Community Banks Partner with Tulsa's iDENTIFY to End Data Silos
TULSA, Okla.--(BUSINESS WIRE)--iDENTIFY, a Tulsa-based data engineering firm and a Snowflake Select Certified Partner, helps community banks unify their data. This quarter, they announced three new banking clients. 'Fragmented data silos slowed down our decision-making, iDENTIFY is helping us build a roadmap to the cloud so we can make smarter, faster decisions with confidence for our customers.' - Pratt Lewis, CIO of InBank Share InBank, Academy Bank and Core Bank selected iDENTIFY for the team's ability to help banks scale confidently, without compromising their community-focused service. 'Fragmented data silos slowed down our decision-making,' said Pratt Lewis, CIO of InBank, 'iDENTIFY is helping us build a roadmap to the cloud so we can make smarter, faster decisions with confidence for our customers.' Lee Easton, President of iDENTIFY, emphasizes that reliable data is foundational to the bank- fintech partnerships: 'Our role is to help banks increase their confidence and nimbleness by consolidating isolated data sets into an accessible system. Banks must be able to trust their data.' How iDENTIFY Helps Partner Banks Better Serve Customers iDENTIFY helps banks centralize data, whether by migrating data to platforms like Snowflake, developing custom reporting, or designing secure data flows between systems like Lithic and Unit21. With cleaner pipelines and fewer manual touchpoints, banks can monitor activity, streamline compliance, and surface strategic insights. 'By collecting all the places we have data and organizing it into useful dashboards, it's now going to be possible to fine-tune our strategy while it's ongoing instead of reacting to end results," said Lindsay Borgeson, President of Partner Banking at Core Bank. Why Tulsa? Tulsa's tech ecosystem has gained national attention after the region's Tech Hub initiative was honored in Fast Company's 2025 World Changing Ideas Awards. Easton says the city's momentum has helped iDENTIFY stay close to the community‑bank market that stretches nationwide. Meet the Banks InBank InBank offers personal, private, business, and commercial banking. It specializes in flexible financing and personalized service for entrepreneurs and growing businesses. Recently, InBank moved its headquarters to Denver's thriving River North district to better serve the region. Academy Bank Academy Bank is a full-service commercial bank with $2.9B in assets and more than 75 banking centers in AZ, CO, KS, AR, and MO. They provide a wide range of financial solutions for business and individuals, including commercial and business banking, treasury management and mortgage. Core Bank Core Bank is a family-owned institution serving Omaha, Kansas City, and Mesa, Arizona. It provides mortgages, construction loans, business banking, and wealth management through a relationship-focused approach.
CNBC
2 days ago
- Business
- CNBC
Here are Friday's biggest analyst calls: Nvidia, Apple, Dell, Tesla, Netflix, Microsoft, Snowflake, Chipotle, Micron & more
Here are Friday's biggest calls on Wall Street: Stephens initiates Snowflake as overweight Stephens said Snowflake is best-in-class. "Long-term growth visibility which has traditionally been the replacement of legacy databases is now being augmented as faster product development has launched key new products w/large TAMs that have yet to contribute to the growth rate, in our view." Evercore ISI upgrades Citizens Financials to outperform from in line Evercore said shares of the banking company are compelling following earnings. "We are upgrading CFG to Outperform from In Line as we expect strengthening B/S [balance sheet] trends, favorable NIM [net interest margin] dynamics, fee income upside, and positive operating leverage to drive steady improvement in CFG's earnings trajectory and L/T returns." Mizuho reiterates Micron as buy Mizuho said it sees a slew of positive catalysts and that investors should buy the weakness. "We would be buyers on MU on the pullback..." Bank of America reiterates Alphabet as buy Bank of America raised its price target on Alphabet ahead of earnings on July 23 to $210 per share from $20. "Expecting strong results, above Street for 2Q." Citi downgrades Barclays to neutral from buy Citi said it sees more balanced risk/reward. "Barclays shares are +125% since end-2023 and now trade on 0.9x P/TB for a target > 12% RoTE next year. While this target appears feasible (we model ~12%), we believe the risk-reward is now more evenly balanced.." Rosenblatt initiates SentinelOne as buy Rosenblatt said the cyber security company is "significantly undervalued." "We are initiating coverage on SentinelOne (NYSE: S) with a Buy rating and a $24 Price Target." Morgan Stanley reiterates Netflix as overweight Morgan Stanley raised its price target on the stock to $1,500 per share from $1,450. "Importantly, newly deployed ad tech appears poised to deliver a roughly doubling of ad revs in '25. Netflix's early but growing use of GenAI tools to power content and product innovation further reinforces our bullish view." Read more. Deutsche Bank reiterates Microsoft as buy Deutsche raised its price target on the stock to $550 per share from $500. " Microsoft shares have significantly outperformed since the company reported much better-than-expected F3Q Azure results in April and seem well supported heading into what we anticipate will be strong F4Q results on July 30th." Jefferies upgrades Abbott Labs to buy from hold Jefferies said investors should buy the dip following earnings. "While ABT's 2Q/guide update was underwhelming, we view the stock rxn as too punitive and are taking advantage of the pullback, upgrading ABT to Buy." KeyBanc upgrades Materion Corporation to overweight from sector weight KeyBanc said it sees an attractive risk/reward for the engineered materials company. "Following our recent analysis, we are upgrading shares of Materion Corporation (MTRN) to Overweight from Sector Weight with a $112 price target, representing > 20% upside." Deutsche Bank adds a catalyst call buy on DuPont Deutsche said it's bullish ahead of earnings in early August. "We are adding DuPont as a Catalyst Call Buy as we believe the upcoming Q2 release would be a catalyst for the shares as it will mark DuPont's last quarterly earnings release prior to the spin-off of its Electronics business (Qnity) on November 1." JPMorgan reiterates Nvidia as overweight The firm said Nvidia remains a top pick heading into earnings next month. "AI/accelerated compute demand remains positioned to weather a potential trade/tariff challenging macro environment...13-15% EPS upside to outyear estimates on resumption of China shipments for AMD/ Nvidia. " JPMorgan reiterates Roku as overweight JPMorgan raised its price target to $100 per share from $85. "We believe Roku is well positioned to deliver a beat/raise qtr, with ad spend largely stable in 2Q and China tariff de-escalation." BMO upgrades Chipotle to outperform from market perform BMO said comps have begun to accelerate. "We believe CMG is well positioned for accelerating comp growth and improving margin trajectory beginning in 2H25, and view favorably its strong US-heavy store growth that has room to accelerate towards 10% over time." Evercore ISI reiterates Apple as outperform Evercore said it's sticking with the stock ahead of earnings on July 31. "Finally, AAPL we expect to see strength in June-qtr driven by better iPhone demand though focus will be on services and gross-margins." Bank of America reiterates Dell as buy The firm raised its price target on the stock to $165 per share from $155. "We expect IT Hardware companies like DELL to benefit from the growth of enterprise /sovereign AI over the next decade." Deutsche Bank reiterates Tesla as buy Deutsche said it's sticking with the stock heading into earnings on July 23. "Long term, our view continues to be that Tesla is well positioned as a technology platform to leverage end-to-end AI into a leading position in autonomous driving and humanoid robotics."
Forbes
2 days ago
- Business
- Forbes
AI Without Data Discipline Is Just Hype, Says JPMorganChase's CPO For Data And AI
Gerard Francis - CPO for data and AI at JPMorganChase There's no shortage of promises in the fast-paced world of AI. Over the last three years, founders and leaders in the industry have bellowed assurances of faster insights, smarter agents, autonomous workflows and even so-called super-intelligent AI systems that will surpass humans at all levels of intelligence. But for Gerard Francis, chief product officer of AI and data at JPMorganChase, all of that hype falls flat without a disciplined, enterprise-wide approach to data. Speaking during a customer spotlight session at Snowflake Summit 2025, where Snowflake's clients discussed how they're building and scaling AI systems, Francis emphasized that 'in the absence of a great data, AI and governance platform, every AI experiment is non-repeatable.' As enterprises rush to harness AI, few have cracked the code on moving from proof-of-concept to large-scale deployment. One big factor behind this, according to Francis, is that many organizations lack the foundational data infrastructure needed to scale beyond early pilots. From AI Experiments To Enterprise Impact The story of AI adoption across Fortune 500 companies has followed a familiar arc: First a proof of concept, then a press release and then comes the plateau. While most firms have dabbled in GenAI, few have moved beyond contained trials into full-scale deployments that deliver repeatable, enterprise-grade value. 'It's all about the data,' Francis began when I asked what enterprise AI truly means at JPMorganChase. He noted that success isn't about flashy models, but about solving real problems across banking, asset management, fraud detection and more — and doing it at scale. 'How do you identify the highest-value use cases and scale them to have maximum business impact?' That scaling is precisely where most AI efforts falter. Research from analyst firm Gartner suggests that at least 30% of generative AI businesses currently testing will be abandoned after proof of concept by the end of 2025. The bottleneck, Francis suggested during our conversation, lies in infrastructure and governance, not in how large or powerful an AI model is. 'Without clear vision and readiness at the infrastructure level,' he told me, 'no amount of AI investment will deliver sustained value.' That understanding helped JPMorganChase pilot generative AI within the organization by building a unified platform that connects data, AI and governance into real-time workflows and repeatable insights. The company's in-house GenAI chat application 'LLM Suite' allows employees to safely interact with large language models, protected by access controls and data usage policies. Initial deployments focused on use cases like document drafting, workflow simplification and internal communication — where value is clear and risk is manageable. 'We had the right governance and controls, ensuring the data is protected,' Francis explained in the interview. 'The concept was simple: Deploy AI where it can immediately deliver value and stay safe doing it.' The Data Discipline Behind AI Readiness What does AI readiness actually look like inside one of the world's largest financial institutions? For JPMorganChase, it begins with data discoverability and access. 'Is your data in a place where it can be discovered?' Francis asked. 'Does it have the right level of entitlement so people can only get the data they should be getting?' These aren't just technical concerns but real compliance imperatives for a firm regulated across multiple jurisdictions and client categories. From there, the focus shifts to unstructured data: Documents, notes, excel sheets, contracts and more. Historically hard to parse, these sources are now becoming valuable thanks to retrieval-augmented generation (RAG) and other GenAI techniques. But even with AI, data quality still matters. 'Avoid duplicate documents,' Francis said. 'Make sure you've got the right version control so people can get accurate answers.' Structured data — scattered across countless internal systems — tends to come last, yet often proves the most powerful when integrated. That's why JPMorganChase built Fusion — an internal data platform for customers that acts as a 'data factory' for orchestrating pipelines, normalizing formats and making datasets AI-ready. JPMorganChase's infrastructure spans multiple vendors and platforms, including Snowflake, which supports its broader efforts to unify enterprise data for AI readiness. 'Think of us as the data factory that operates at scale,' Francis said. Governance As A Backbone Talk to any enterprise AI leader, and governance will eventually come up. But at JPMorgan, said Francis, it's not an afterthought. Rather, it's embedded in the strategy from day one. 'When you are part of a regulated entity,' Francis explained, 'you've got to always make sure that the data you're using for a particular purpose is an approved use of that data.' That means aligning use cases not only with internal policies, but also with country-specific laws, contractual obligations and client privacy terms. Managing those controls manually would be a nightmare. JPMorganChase's goal is to transition 'from a heavy human process aided by technology to an entirely technology-enabled process.' Until then, scalability and compliance depend on how well governance is operationalized into the AI development lifecycle. AI Agents Are The Next Frontier Imagine an AI system that doesn't just summarize a document but reconciles data, files reports, books appointments and updates compliance records. These are the early signals of what's next in enterprise AI: Autonomous agents that can act on behalf of users with limited supervision. While many AI deployments today still focus on summarizing text or generating content, the industry-wide shift to agentic AI is already underway and JPMorganChase is paying close attention. These autonomous systems, capable of reasoning and decision-making, promise immense value, particularly in complex workflows like software development, research, or operations. But Francis isn't rushing. 'Agentic solutions offer phenomenal value,' he said, 'but also bring a lot of risks. That's an area we've got to educate ourselves on.' He's cautious and strategic. Rather than replacing jobs outright, the goal is augmentation: helping teams move faster, armed with better data and smarter suggestions. As Francis noted, 'It's less about agents or not, but more about whether you can really solve a use case well.' If you can, you either lower your cost or improve your revenue opportunity.' For an organization with JPMorganChase's scale and complexity, AI makes sense only when it drives value. 'We determine the values we want to pursue and that determines how we prioritize AI,' Francis said. That value-driven mindset also extends to ROI. While Francis declined to cite exact numbers, he noted that the firm reports publicly on AI value generation — with much of that value still coming from traditional machine learning — though GenAI is advancing quickly. 'If we can dramatically drop the price of any use case, then the return on investment becomes easier to justify and easier to scale.' The Long Game Of AI Leadership Looking ahead, Francis hopes JPMorganChase will be remembered for solving one of enterprise AI's hardest problems: Building a platform that integrates data, AI and governance across multiple technology stacks. 'It's very often you can do this for one vendor,' he said. 'But doing it across vendors is incredibly difficult.' Still, the payoff is clear. If Fusion and platforms like it can eliminate the friction between pilots and production, AI will stop being an experiment and start becoming the enterprise default. And in that world, the winners won't be those with the flashiest models, but those with the strongest data discipline.
Business Wire
4 days ago
- Business
- Business Wire
Airbyte Data Movement Enhances Data Sovereignty and AI Readiness
SAN FRANCISCO--(BUSINESS WIRE)-- Airbyte, the open data movement platform, today announced three significant updates to its on-premises Airbyte Enterprise product that provide organizations with greater flexibility and control over their data while ensuring that data is ready to work with AI. 'All these new capabilities are directed towards making data AI ready with more control, context, and speed because without data, there is no AI, and without the right data, AI is no good,' said Michel Tricot, CEO and co-founder of Airbyte. Airbyte's platform updates include the ability to facilitate data sovereignty and compliance across different global regions; synchronize data with its metadata to assist AI models' ability to improve reasoning and accuracy; and directly load data volumes to BigQuery and Snowflake, which increases data sync speeds and reduces compute costs. 'All these new capabilities are directed towards making data AI ready with more control, context, and speed because without data, there is no AI, and without the right data, AI is no good,' said Michel Tricot, CEO and co-founder of Airbyte. ' Studies have shown that too often, AI projects are abandoned due to poor data quality and escalating costs. We help organizations command their data quickly and securely. Our enhanced data sovereignty feature will appeal to businesses in areas like Australia where compliance rules have been a challenge for many organizations, helping Airbyte expand in those regions.' The new multiple data planes feature can be used by organizations to keep control of their data on-premises in order to maintain data sovereignty and compliance across different regions, but with an improved, centralized user interface (UI) that efficiently manages all of it holistically. Airbyte now enables synchronized unstructured files and structured records to be transferred in the same data pipeline, which is the most efficient way to preserve metadata and data relationships – enabling richer data context and significantly improving the performance of AI Large Language Models (LLMs) using that data. Direct loading represents a new, streamlined way that Airbyte loads data into BigQuery that will soon be available for ClickHouse and Snowflake, plus other destinations. Direct loading can reduce compute costs by 50 to 70%, and increases speed by up to 33% depending on the use case. Airbyte makes moving data easy and affordable across nearly any source and destination, ensuring enterprises have accurate, timely data for analysis, decision-making, and AI. With over 900 contributors and a community of more than 230,000 members, Airbyte supports the largest data engineering community and is the industry's only open data movement platform. The company announced a strong first quarter with a 25% increase in revenue and has recently received multiple industry recognitions for its innovation and growth. For more details, read the blog post and to learn more about Airbyte Enterprise, go here. About Airbyte Airbyte, the open data movement platform, empowers data teams in the AI era by transforming raw data into actionable insights with the industry's largest ecosystem of connectors. Committed to best-in-class security and compliance standards, Airbyte offers low-code, no-code, and AI-powered connector development for structured and unstructured data. Teams can manage pipelines via API, Terraform, AI Connector Builder UI, and Python libraries across multi-cloud and hybrid environments. Trusted by 7,000 enterprises and 18% of the Fortune 500, Airbyte is the go-to solution for modern data management. For more information, visit
Business Wire
4 days ago
- Business
- Business Wire
Zip Named to CNBC's World's Top Fintech Companies 2025
SAN FRANCISCO--(BUSINESS WIRE)-- Zip, the world's leading agentic procurement orchestration platform, today announced its inclusion in CNBC's World's Top Fintech Companies 2025 list in the Enterprise Fintech category. Developed in partnership with Statista, the annual ranking evaluated over 2,000 companies based on comprehensive performance metrics across key fintech sectors. The recognition adds to recent Zip honors, which include Forbes 2025 Fintech 50, Fast Company's Most Innovative Companies of 2025, Inc.'s Best in Business Awards, and more. Zip named to @CNBC World's Top #Fintech Companies 2025 in Enterprise Fintech category alongside Visa, Stripe, and other industry leaders Share 'Being recognized by CNBC validates our belief that procurement is no longer seen as a back-office function, it's become mission-critical for the financial health of every global enterprise,' said Rujul Zaparde, Co-founder and CEO of Zip. 'In just five years, we've gone from a startup to the platform trusted by the world's largest companies to manage their most complex purchasing decisions.' Zip's selection in the Enterprise Fintech category – which recognizes companies delivering technology-driven solutions for financial institutions and businesses – comes as Zip experiences unprecedented growth, driven most recently by its June 2025 launch of its agentic AI suite that allows companies to autonomously handle complex procurement tasks. Zip's specialized agents, each focused on a single function like tariff analysis, contract review, or compliance checking, are helping Fortune 500 companies eliminate millions of hours of manual work while reducing risk and driving savings. The platform's impact on enterprise operations has been profound: Customers average 3.6% in annual spend savings Companies gain 25% in productivity through automated workflows Snowflake alone has saved $305 million annually using Zip Discover Financial increased procurement throughput by 67% The platform maintains 100% retention across strategic enterprise customers Since its founding in 2020, Zip has redefined enterprise procurement, growing from a simple intake solution to a comprehensive orchestration platform processing billions in corporate spending. The company's October 2024 Series D funding of $190 million at a $2.2 billion valuation – the largest investment in procurement technology in over two decades – underscored investor confidence in Zip's vision. Today, Zip serves many of the world's largest and most innovative companies, including AMD, Anthropic, Discover, Northwestern Mutual, OpenAI, Reddit, Sephora, and Snowflake. As supply chain disruptions, inflation, and tariffs continue to challenge global businesses, these enterprises rely on Zip to transform procurement from a cost center into a strategic advantage. To learn more about Zip, visit About CNBC's World's Top Fintech Companies The World's Top Fintech Companies list, produced annually by CNBC and market research firm Statista, recognizes companies transforming financial services through technology innovation. The comprehensive evaluation process analyzes both general and segment-specific KPIs to identify leaders across seven fintech categories including payments, neobanking, digital assets, and enterprise fintech. The 2025 list evaluated over 2,000 companies between February and May 2025. The United States leads with 126 companies on the list, followed by the U.K. with 38 and Singapore with 16. About Zip Zip is the world's leading agentic procurement orchestration platform, empowering businesses to accelerate the procurement process, mitigate risk, and drive growth by offering a single front door to unify the teams, tasks, and tools involved in working with suppliers. With Zip, businesses can maximize employee adoption of purchasing policies and increase spend visibility and control. As the leading solution for optimizing business spend, Zip's AI-powered platform is trusted by hundreds of leading enterprises worldwide, including AMD, Anthropic, Coinbase, Discover, Dollar Tree, Instacart, Invesco, Lyft, Northwestern Mutual, OpenAI, Prudential, Reddit, Sephora, and Snowflake to maximize the ROI of every dollar. To learn more, visit
