Oracle has deployed OpenAI GPT-5 across its database portfolio and suite of SaaS applications, including Oracle Fusion Cloud Applications, Oracle NetSuite, and Oracle Industry Applications, such as Oracle Health. By uniting trusted business data with frontier AI, Oracle is enabling customers to natively leverage sophisticated coding and reasoning capabilities in their business-critical workflows. With the development of GPT-5, Oracle will help customers: Enhance multi-step reasoning and orchestration across business processes; Accelerate code generation, bug resolution, and documentation; Increase accuracy and depth in business insights and recommendations. “The combination of industry-leading AI for data capabilities of Oracle Database 23ai and GPT-5 will help enterprises achieve breakthrough insights, innovations, and productivity,” said Kris Rice, senior vice president, Database Software Development, Oracle. “Oracle AI Vector and Select AI together with GPT-5 enable easier and more effective data search and analysis. Oracle’s SQLcl MCP Server enables GPT-5 to easily access data in Oracle Database. These capabilities enable users to search across all their data, run secure AI-powered operations, and use generative AI directly from SQL—helping to unlock the full potential of AI on enterprise data.” “GPT-5 will bring our Fusion Applications customers OpenAI’s sophisticated reasoning and deep-thinking capabilities,” said Meeten Bhavsar, senior vice president, Applications Development, Oracle. “The newest model from OpenAI will be able to power more complex AI agent-driven processes with capabilities that enable advanced automation, higher productivity, and faster decision making.”
Precisely and Opendatasoft partner to deliver integrated data marketplace combining robust data integrity and self-service sharing for trusted, AI-ready, compliant data across enterprises
Precisely announced a new strategic technology partnership with Opendatasoft, a data marketplace solution provider. Together, they will deliver an integrated data marketplace designed to simplify access to trusted, AI-ready data across businesses and teams – seamlessly and in compliance with governance requirements. The new data marketplace will integrate with the Precisely Data Integrity Suite to solve these challenges by combining the Suite’s robust data management capabilities with the intuitive, self-service experience of Opendatasoft’s data sharing platform. This powerful combination will ensure that accurate, consistent, and contextual data products are not only well-managed behind the scenes – they are also easy to discover, use, and share across the organization, with partners, or even through public channels. The result is improved accessibility, faster adoption, and a frictionless experience that supports enterprise-wide compliance and data-sharing needs. Franck Carassus, CSO and Co-Founder of Opendatasoft said “Together with Precisely, we’re enabling them to support greater data sharing and consumption by business users, unlocking new opportunities for AI and analytics, and maximizing ROI on their data investments.” By creating a flexible foundation for AI, analytics, and automation, customers can streamline operations, reduce the cost of ownership, and accelerate time-to-insight. Precisely enables organizations to modernize with intelligence and resilience – empowering them to build the modern data architectures needed to support dynamic data marketplaces and self-service access across the enterprise.
Klaviyo’s enhanced MCP server securely links AI tools to customer data via real-time APIs and remote access; enabling conversational analytics, audience suggestions, and automated campaign execution.
CRM and marketing automation company Klaviyo Inc. announced the general availability of its enhanced Model Context Protocol server that gives marketers the ability to connect AI tools such as Claude Desktop, Cursor, VS Code, Windsurf and other local or web-based tools directly with Klaviyo. The enhanced MCP server includes improved reporting context and a new remote server for broader accessibility, making it easier for marketers to bring AI into their workflows with more opportunity for speed and automation. The solution assists marketers that want to scale up performance based on training AI platforms to deliver better insights, recommendations and content. The remote MCP server offers secure online setup and real-time access to create, read and update data through Klaviyo’s API without adding complexity to the marketing technology stack. The MCP server makes it easy for marketers to accelerate their work in Klaviyo with AI tools, including a conversational chat interface that allows customers to interact with Klaviyo using natural language prompts. Marketers can quickly ask questions such as which campaign is driving the most revenue, how clickthrough rates have changed over time or compare performance across accounts. Using the platform, marketers can request AI-generated suggestions for new audience segments, subject lines modeled on top performers, or strategies to improve open rates in key flows. Additionally, the MCP server also supports AI-driven execution, letting marketers move from idea to action. With simple prompts, users can upload event profiles, draft promotional emails, or add images directly into Klaviyo.
ParadeDB’s open-source Postgres extension facilitates full-text search and analytics directly in Postgres without the need to transfer data to a separate source and can support heavy workloads that require frequent updating
ParadeDB is an open source Postgres extension that facilitates full-text search and analytics directly in Postgres without users needing to transfer data to a separate source. The platform integrates with other data infrastructure tools, including Google Cloud SQL, Azure Postgres, and Amazon RDS, among others. “Postgres is becoming the default database of the world, and you still can’t do good search over that information, believe it or not,” Philippe Noël, the co-founder and CEO of ParadeDB said. ParadeDB isn’t the first company to try to solve Postgres search. Noël said that Elasticsearch works by moving data back and forth between itself and Postgres, which can work, but this system isn’t great for heavy workloads or processes that require frequent updating. “That breaks all the time,” Noël said. “The two databases are not meant to work together. There’s a lot of compatibility issues, there’s a lot of latency issues, higher costs, and all of that deteriorates the user experience.” ParadeDB claims to eliminate a lot of those challenges by building as an extension on top of Postgres directly, no data transfer required.
MindBridge’s integration of its AI-powered financial decision intelligence with Snowflake to enable finance teams leverage secure data pipelines for automated analysis and real-time risk insights within their existing workflows
MindBridge, the leader in AI-powered financial decision intelligence, announced its integration with Snowflake, enabling finance teams to seamlessly analyze financial data for continuous, AI-powered analysis. With this new integration, organizations can securely connect MindBridge to their data without complicated processes or manual work. By leveraging secure data pipelines within the Snowflake AI Data Cloud, organizations can easily and securely use MindBridge for automated analysis, without adding complexity or risk. Risk scores and insights from MindBridge can also be leveraged in existing workflows, shortening the time to identify and act on findings and minimizing additional training or complex implementations. Every time data is updated, MindBridge automatically runs its analysis, so finance teams always have a consistent, up-to-date view of their financial risk. Key Benefits of the Integration: Simple, scalable integration – MindBridge connects directly to the Snowflake AI Data Cloud, leveraging secure data pipelines to automate analysis within existing governance frameworks. Real-time financial risk insights; Enterprise-grade security and control; Frictionless insights delivery – With automated data delivery and analysis execution, business users can access the latest results in the MindBridge UI or within their existing workflow systems, providing more flexibility to surface insights where and when they’re needed most — without disrupting established processes; Integrated risk intelligence – Risk scores and analysis results are retrieved via API back into the Snowflake platform, enabling continuous risk monitoring, deeper investigations, and integrated reporting alongside other business KPIs.
CapStorm’s AI solution enables business users to ask complex data questions in plain English and receive real-time dashboards, instantly, across Salesforce, ERPs, CRMs, and data warehouses without writing a single line of code
Secure Salesforce data management solutions provider CapStorm has launched CapStorm:AI, an AI-powered solution that lets users “talk to their data” using plain English. Designed for organizations seeking secure, self-hosted insights across their Salesforce and SQL environments, CapStorm:AI enables business users to ask complex data questions and receive real-time dashboards, instantly, and without writing a single line of code. CapStorm:AI brings together CapStorm’s proven near real-time Salesforce data replication with a powerful AI engine that understands how businesses’ data connects. It works with leading SQL databases like SQL Server and PostgreSQL, as well as cloud data warehouses like Snowflake and Amazon Redshift, giving users instant insights across systems, no technical expertise required. Best of all, it keeps everything inside their own environment, so data stays secure and fully under the user’s control. CapStorm:AI is designed with security and compliance in mind, making it ideal for regulated industries and enterprises that demand full control of their data. CapStorm:AI gives users a faster, easier way to get answers: Natural Language Dashboards: Ask a business question in plain English and receive a real-time dashboard, instantly. Instant Access Across Systems: Understand how data connects across Salesforce, ERPs, CRMs, and data warehouses, without needing custom joins or pipelines. Near Real-Time Insights: Built on CapStorm’s trusted replication technology, ensuring your answers are always up to date. Flexible Deployment Options: CapStorm:AI can be deployed using an organization’s own on-prem database for full control, or hosted in a secure AWS environment managed by CapStorm.
iMerit is building expert-led, high-quality data for finetuning generative AI models through use of domain-specific experts for generating and evaluating problems for the model to solve and human-in-the-loop labelling
AI data platform iMerit believes the next step toward integrating AI tools at the enterprise level is not more data, but better data. The startup has quietly built itself into a trusted data annotation partner for companies working in computer vision, medical imaging, autonomous mobility, and other AI applications that require high-accuracy, human-in-the-loop labeling. Now, iMerit is bringing its Scholars program out of beta. The goal of the program is to build a growing workforce of experts to fine-tune generative AI models for enterprise applications and, increasingly, foundational models. iMerit doesn’t claim to replace Scale AI’s core offering of high-throughput, developer-focused “blitz data.” Instead, it’s betting that now is the right moment to double down on expert-led, high-quality data, the kind that requires deep human judgment and domain-specific oversight. iMerit’s experts are tasked with finetuning, or “tormenting,” enterprise and foundational AI models using the startup’s proprietary platform Ango Hub. Ango allows iMerit’s “Scholars” to interact with the customer’s model to generate and evaluate problems for the model to solve. For iMerritt, attracting and retaining cognitive experts is key to success because the experts aren’t just doing a few tasks and disappearing; they’re working on projects for multiple years. The goal is to grow across other enterprise applications, including finance and medicine.
Penske Logistics taps Snowflake AI to develop AI-based program that flags drivers at risk of quitting based on work patterns, route history and behavioral signals
Penske Logistics has leveraged Snowflake Inc.’s evolving artificial intelligence capabilities through a strategic partnership that’s reshaping the supply chain landscape. “We have onboard telematics devices inside our fleet that are generating millions of data points, including things like hard braking, following too closely, fuel consumption and so on,” said Vishwa Ram, vice president of data science and analytics at Penske Logistics. “Getting all of that data in one place and adding it up with other sets of data that we have that are contextual is a huge challenge for us.” “We’re accustomed now to disruption being normal, and as a result, organizations see just how important it is to invest in that visibility element so they can see the disruption as it’s coming, or at least be able to react in real time when it does happen,” he said. For Penske, this means leveraging predictive analytics to foresee supplier delays and reroute resources before bottlenecks occur. Additionally, the company applies AI in workforce retention. With drivers making up over half of its workforce, driver satisfaction is key. Penske developed an AI-based program that flags drivers at risk of quitting based on work patterns, route history and behavioral signals. Armed with these insights, frontline managers proactively engage with drivers, often adjusting schedules or simply checking in, according to Ram.
Arctera.io’s backup and storage solution combines data management, cyber resiliency and data compliance and is designed to monitor customers’ data environments for potential security breaches by tracking deterministic AI, that changes over time
Arctera.io is going full steam ahead on data and artificial intelligence management. Arctera offers three backup and storage options that originated from Veritas Technologies LLC, covering data management, cyber resiliency and data compliance. All three areas are under a microscope in the era of AI adoption. Arctera focuses on data management that meets regulatory requirements and remains secure against ongoing threats from cyberattackers. AI presents a particular challenge to data resilience and recovery because it’s constantly changing, according to Matt Waxman, chief product officer at Arctera.io. “We have built IT around the notion that software is deterministic,” he explained. “The notion that [this] is static, that the software that you’re acquiring is going to be the same software at least for quite a long period of time. That’s not the case with AI. So what you bring in terms of a model is self-learning, and it’s going to adjust over time.” For this reason, it’s crucial to have multiple ways to back up your data and multiple ways to keep track of it. While Waxman advises against “AI whitewashing,” or applying AI to problems indiscriminately, Arctera has successfully implemented use cases for AI related to data compliance and monitoring. Arctera attempts to kill two birds with one stone by employing its data compliance software to monitor customers’ data environments for potential security breaches. The next step is governing the growing host of AI agents, according to Waxman.
Indico unveils embedded data enrichment agents to supercharge insurance decisioning by transforming unstructured submissions, claims, and policy documents into structured, decision-ready data
Indico Data has expanded its Data Enrichment Agents, enhancing document workflows with deeper, native access to proprietary and third-party datasets. The enrichment capabilities combine Indico’s growing library of proprietary data catalogs with seamless integration to proprietary data and trusted third-party providers. The available data spans commercial, personal, and property domains, and includes enriched details such as business credit and risk scores, crime statistics, driver safety and motor vehicle violations, VIN and registration data, proximity-based risk, co-tenancy exposure, property characteristics, permit activity, and more. The Data Enrichment Agents are now generally available to all Indico platform customers and can be activated across workflows including submission ingestion, underwriting clearance, claims FNOL, and policy servicing. By transforming unstructured submissions, claims, and policy documents into structured, decision-ready data, Indico enables insurers to act faster on high-value opportunities, streamline triage and intake, and improve the consistency and transparency of underwriting and claims decisions. Key benefits of Indico’s Data Enrichment Agents include: Embedded data access; Auto-fill missing data; Flexible provider ecosystem; and Proprietary data at a lower cost.