OpenAI is reportedly close to releasing a browser that could potentially take on Google LLC’s market dominance with its Chrome browser, several months after the company said that it would be interested in buying Chrome from Google. The browser is slated to be launched in the coming weeks and uses artificial intelligence to fundamentally change how consumers browse the web. Notably, the browser would also give OpenAI direct access to user data, which it could use to train its models. The browser is expected to be built on Chromium, the open-source codebase that underpins Chrome and most other browsers except Firefox, but with AI tightly integrated into the user experience. The OpenAI browser is said to include a chat-style assistant that can perform complex tasks on behalf of the user, such as summarizing pages, autofilling forms, booking travel or completing online purchases, without requiring users to click through websites manually, instead of simply serving as a traditional interface for web navigation. Where things could get particularly interesting is that the browser may include OpenAI’s Operator agent, an agentic AI offering designed to handle multistep tasks across the web, allowing users to delegate responsibilities such as scheduling appointments or ordering food to an AI agent. Its inclusion could turn the browser into more than just a gateway to the internet versus a fully capable assistant embedded directly in the browsing environment. The move could place OpenAI in direct competition with Google on multiple fronts, not only in search but also in advertising and data collection.
Icon Business Bank’s integration with ZimpleMoney to enable businesses to offer private financing across multiple loan types with automated ledgering, integrated payments, borrower portals and detailed reporting
Icon Business Bank announced a strategic partnership with ZimpleMoney to simplify private party financing for customers. This collaboration gives Icon Business Bank customers access to advanced loan servicing technology that streamlines the management of private loans, leases, and installment payments. Powered by ZimpleMoney’s cloud-based platform and open APIs, businesses can now offer private financing to their customers, creating new revenue streams while improving cash flow management. ZimpleMoney’s platform features multiple loan types, automated ledgering, integrated payments, borrower portals and detailed reporting—all designed to simplify the complexities of private financing and enhance trust between borrowers and lenders. It provides a compliant, professional framework that brings transparency and efficiency to every step of the process. With this offering, Icon Business Bank continues to lead with innovation by offering tools that align with today’s business environment and provide access to more modern solutions.
Moment automates fixed income investments- instantly generates portfolios from email requests, builds transition proposals from PDFs in seconds, and produces client-ready reports with custom commentary
Moment, the company automating trading and portfolio management workflows for fixed income teams, has raised $36 million in Series B funding led by Index Ventures, with participation from Andreessen Horowitz and others. Moment’s platform unifies trading, research, portfolio optimization, reporting, and risk and compliance in a single system, with a layer of automation that allows financial institutions to supercharge their fixed income teams. Leading financial institutions use Moment to: Execute thousands of trades in seconds with automated execution rules; Optimize tax-sensitive, multi-asset class portfolios across hundreds of thousands of accounts; Scan all of their accounts and trades in real-time for compliance violations using custom rules; Use AI-powered workflows to instantly generate portfolios from email requests, build transition proposals from PDFs in seconds, and produce client-ready reports with custom commentary. By embedding forward-deployed engineers with its largest customers, Moment co-develops multi-year transformation roadmaps while delivering near-term solutions in production. Dylan Parker, CEO and co‑founder of Moment said “These firms are partnering with Moment to co-create the future of fixed income – empowering their fixed income teams with a differentiated platform to win new business, unlock eight-figure revenue channels, and genuinely 10x their productivity.”
Prime Day 2025 is seeing a shift from impulse electronics to practical essentials driven by tighter budgets and rising skepticism over perceived value
Prime Day 2025 is seeing a shift from impulse electronics to practical essentials, signaling consumers are buying smarter. According to early reports, spending at the start of Prime Day Tuesday (July 8) was down 14%. PYMNTS Intelligence data reveal spending may have dropped not due to a lack of interest in the event, but because of tighter budgets and rising skepticism over perceived value. Flash deals on electronics, once the hallmark of Prime Day, underperformed per Tuesday sales data, while essentials like home goods, pet care, and household appliances fared better. It’s a shift from impulse to pragmatism. Prime Day’s spending contexts are also a reflection of subtle but seismic changes in how consumers pay. The old model — credit card plus shipping address — is fading. Instead, new habits are being formed around wallets, embedded finance and more payments innovations. BNPL orders for Amazon’s Prime Day, for example, were up 13.6% year over year for Tuesday’s shopping event. Amazon Prime Day 2025 was still a massive success by any traditional measure. But beneath the surface, a critical shift is underway, powered by AI innovation, payments optimization and changing consumer behavior. Adobe said that during Amazon’s Prime Day sales event, it expects the amount of traffic to all U.S. retailers that comes from generative AI chat services and browsers to leap 3,200% year over year.
Graphwise’s tool offers swift integration of data in agentic AI ecosystems and enables AI platforms to tap directly into their enterprise knowledge through support for MCP
Graph AI provider Graphwise announced the availability of GraphDB 11. With MCP protocol support, V11 offers swift integration of data in agentic AI ecosystems and enables AI platforms like Microsoft Copilot Studio to tap directly into their enterprise knowledge. GraphDB 11 introduces powerful new features designed to bridge the gap between LLMs and structured knowledge so enterprises can build more intelligent and context-aware AI applications, including: Broad LLM Compatibility & GraphRAG: The new features expand support for a wide range of large language models, including Qwen, Llama, Gemini, DeepSeek, and Mistral—plus the ability to deploy local or custom models. The improved Talk to Your Graph feature empowers GraphRAG (Retrieval-Augmented Generation), enabling natural language access to enterprise knowledge graphs helps businesses reduce hallucinations, improve accuracy, and drive more reliable AI-driven decisions. MCP Support for Enterprise Agentic AI Integration: This grounds AI in domain data, turning it from a generic tool into a strategic asset. By leveraging GraphDB’s structured knowledge and GraphRAG capabilities, organizations benefit from AI that delivers accurate, context-aware insights—reducing risk, improving decision quality, and driving measurable efficiency across workflows. Precision Entity Linking for Reliable Insights: By connecting language to meaning. Its advanced entity linking accurately maps terms and phrases to the right concepts or entities in the knowledge graph—eliminating ambiguity and improving how information is retrieved and applied. This enhances GraphDB’s Graph RAG capabilities, ensuring outputs are not just fast, but precise, relevant, and grounded in an organization’s data. GraphDB 11 delivers core platform capabilities that make it easier and more cost-effective for organizations to build and scale intelligent applications that fully leverage graph data across multiple use cases. These include: Native GraphQL Support: Enhancements aimed at making life easier for developers to easily use GraphQL to query their rich graph data, making data access straightforward and speeding up the creation of AI-powered applications in a secure, scalable, and reliable environment. Performance at Scale: Improvements boost database performance including high availability, strong security, and flexible multi-tenancy to simplify common operational tasks and development efforts. Optimized Performance for AI-Driven Knowledge Hubs: The advanced repository caching dramatically speeds up operations to ensure the scalability and responsiveness users demand from knowledge hubs that support multiple use cases and projects coming from one knowledge hub.
QR Codes make a splash in the real time payments pool – X9 payment QR code standard introduces a common language for encoding payment data, so single QR code can work across multiple networks, such as FedNow, ACH, and TCH RTP
QR code payments have taken a big step towards becoming not only a mainstream payment option but also one that can accelerate the adoption of real-time payments. Late last week, the technology was used to facilitate a transaction over the FedNow network using the X9 standard. The demonstration transferred funds in one second from a credit union to a Top 4 bank in the United States. During the test, a bill was presented to a payer with a merchant-generated QR code. Upon scanning the code, the payer authorized the transaction via the payer’s credit union’s mobile app. Assisting in the transaction was technology from Matera, a fintech specializing in instant payments and QR code technology. Also involved in the transaction were Tyfone Inc., a digital-banking and -payments platform provider, and real-time payments provider Payfinia Inc., a Tyfone company. Key to making the transaction possible was the X9 payment QR code standard. Developed by the Accredited Standards Committee X9, the X9 standard introduces a common language for encoding payment data in “a secure, structured, and extensible way,” according to Matera. As a result, a single QR code can work across multiple networks, such as FedNow as well as the automated clearing house and The Clearing House’s RTP network. It can also work with different banks. The standard also supports multiple use cases, such as consumer-to-business, business-to-business, and peer-to-peer payments. Matera chief executive and co-founder Carlos Netto said “It opens the door to a broad range of use cases, bill payments, in-store payments and ecommerce, all initiated by QR code and settled in real time. Ultimately, this payment QR Code can accelerate the adoption of instant payments.”
RegASK agentic AI architecture pairs domain-specific vertical LLM with specialized AI agents who perform distinct tasks, are coordinated by a ‘project manager’ agent and their outputs reviewed by an evaluator agent to deliver personalized insights for day-to-day compliance operations
RegASK, a provider of AI-driven regulatory intelligence for Consumer Goods and Life Sciences, has launched the industry’s first agentic AI architecture that pairs RegASK’s vertical large language model (V-LLM) with specialized AI agents to deliver personalized insights and streamline how teams find, understand, and act on regulatory information. These agents each perform a distinct task, such as document retrieval, translation, summarization, and assessment generation. These agents are coordinated by a dedicated ‘project manager’ agent that manages how tasks are assigned and performed across the system, enabling collaborative execution of multi-step workflows. An evaluator agent reviews outputs before they’re delivered to users, helping ensure accuracy and build trust in the results. Together, the enhanced agent network and embedded V-LLM power deeper automation, more tailored insights, and the ability to manage a wider range of day-to-day compliance operations. The launch also brings: A more powerful, embedded vertical language model: RegASK’s domain-specific LLM is now fully integrated into the platform and enhanced with additional structured attributes. The model gives agents deeper context to generate faster, more precise summaries, assessments, and search results, delivering insights that are directly aligned to users’ regulatory priorities. Redesigned user interface with streamlined regulatory change tracking: RegASK’s redesigned user experience significantly improves how regulatory teams identify and respond to critical updates. The new alerts module delivers customizable alert views, streamlined navigation, and faster access to essential regulatory details, enabling professionals to efficiently manage compliance workflows, mitigate risk proactively, and keep their organizations ahead in highly regulated environments.
Blok’s AI agents aim to eliminate friction points in software testing by simulating the behavior of human users and identifying their likes and dislikes using a combination of behavioral science and product data
A startup called Blok Intelligence Inc. has raised $7.5 million to transform the software testing process with AI agents that simulate the behavior of human users. Blok has developed AI agents that are grounded in a combination of behavioral science and product data to try to simulate how different types of people use software. That way, developers can identify the most useful features and uncover and eliminate any friction points in their applications. It’s aiming to transform the software testing process, which often takes weeks, and condense it into a matter of hours. According to the startup, the capabilities its AI agents provide are needed more than ever, given the surging popularity of “vibe coding,” which has led to a flood of new digital products, but the challenge is that many of these new applications aren’t giving people what they want. Blok gets around that with AI agents that behave like humans. It says they’re curious, imperfect and full of nuance, just like people are. By grounding them in the “messy realities” of human decision making, they’re better able to identify what humans will like and dislike about new software products. Co-founder and Chief Executive Tom Charman said he thinks static, one-size-fits-all software products are soon going to become obsolete, replaced by tools that are more adaptive and responsive to each user’s needs. But developers need help to understand what those needs are.
ZeroEntropy is a RAG based AI search tool strictly for developers that grabs data, even across messy internal documents and grabbing the most relevant information first
Startup ZeroEntropy joins a growing wave of infrastructure companies hoping to use retrieval-augmented generation (RAG) to power search for the next generation of AI agents. ZeroEntropy offers an API that manages ingestion, indexing, re-ranking, and evaluation. What that means is that — unlike a search product for enterprise employees like Glean — ZeroEntropy is strictly a developer tool. It quickly grabs data, even across messy internal documents. Houir Alami likens her startup to a “Supabase for search,” referring to the popular open source database that automates much of the database management. At its core is its proprietary re-ranker called ze-rank-1, which the company claims currently outperforms similar models from Cohere and Salesforce on both public and private retrieval benchmarks. It makes sure that when an AI system looks for answers in a knowledge base, it grabs the most relevant information first. “Right now, most teams are either stitching together existing tools from the market or dumping their entire knowledge base into an LLM’s context window. The first approach is time-consuming to build and maintain,” CEO Ghita Houir Alami said. “The second approach can cause compounding errors. We’re building a developer-first search infrastructure — think of it like a Supabase for search — designed to make deploying accurate, fast retrieval systems easy and efficient.”
DigitalOcean’s managed AI platform offers one simple UI with integrations for storage, functions, and database to build AI agents that can reduce costs or streamline user experiences—without requiring deep AI expertise on their team
DigitalOcean Holdings, announced the general availability of its DigitalOcean GradientAI™ Platform, a managed AI platform that enables developers to combine their data with foundation models from Anthropic, Meta, Mistral and OpenAI to add customized GenAI agents to their applications. The DigitalOcean GradientAI Platform is a fully managed service where customers do not need to manage infrastructure and can deploy Generative AI capabilities in minutes to their applications. With the DigitalOcean GradientAI Platform, all tools and data are available through one simple UI with integrations for storage, functions, and database all powered by DigitalOcean’s GPU cloud. This empowers customers to build AI agents that can reduce costs or streamline user experiences—without requiring deep AI expertise on their team. The DigitalOcean GradientAI Platform is built with simplicity in mind to get GenAI-backed experiences into customer applications quickly. By leveraging retrieval augmented generation (RAG), customers can quickly and easily create GenAI agents for use within their applications. These agents offer powerful capabilities that can be enhanced through function routing to integrate with third-party APIs, and agent routing to connect with other GenAI Agents within the platform. Additionally, with Serverless LLM Inference, customers can integrate models from multiple providers via one API, with usage-based billing and no infrastructure to manage.