Spreedly announced a strategic enhancement to its platform through the integration of Just-In-Time Card Updates for Visa Cards powered by Visa Account Updater (VAU). Spreedly’s Just-In-Time Card Updates integration provides merchants with up-to-date card credentials precisely when they’re needed. Unlike traditional card update strategies, which operate on a scheduled batch basis, Just-In-Time Card Updates enable real-time access to refreshed card credentials at the point of transaction to give merchants greater control and responsiveness. Built on the Advanced Vault capabilities of the Open Payments Platform, Spreedly leverages Visa’s powerful network to give merchants control to fetch card updates at the right place and right time. This ability to leverage tools on demand allows businesses to better manage their operational costs and prevent disruption to the customer experience for card-on-file and subscription payments. In addition to integrating with VAU to enable Just-In-Time Card Updates, Spreedly is integrating Visa Acceptance across key gateways—including CyberSource and Authorize.Net—to provide merchants with greater reach and reliability. Key Business Benefits: Improved Authorization Rates: Reduce declines caused by outdated card credentials and recover revenue from failed transactions. Operational Efficiency: On-demand updates eliminate the need for constant background refreshes; this streamlines payment workflows and reduces costs. Customer Retention: Prevent service interruptions and improve customer loyalty by ensuring seamless, uninterrupted transactions. Strategic Flexibility: Merchants control the timing and use of card updates, aligning payment operations with business needs.
Algebrik AI’s integration with TruStage platform is to enable FIs to present lending protection products directly within the digital loan application flow
Algebrik AI announced a partnership with TruStage™, to integrate the education of a broad suite of lending protection offerings from TruStage—including GAP coverage, debt protection, credit insurance, and mechanical repair coverage—directly into Algebrik’s end-to-end digital lending workflows. With this integration, Algebrik enables credit unions and community lenders to present TruStage protection products directly within the digital loan application flow—empowering borrowers to choose coverage that fits their needs without disrupting the journey. Whether for auto loans, personal loans, or other credit products, protection options are embedded natively into Algebrik’s borrower experience and remain easily configurable by loan officers. Key Benefits of the Integration: Comprehensive Coverage Options – Offer GAP coverage, credit insurance, debt protection, and mechanical repair coverage products—all surfaced directly within Algebrik’s LOS. Embedded at the Point of Decision – Borrowers encounter relevant protection choices within the same digital flow, with no need to redirect or re-engage later. Configurable by Loan Type & Member Segment – Institutions can tailor which TruStage products are presented based on loan type, member profile, or risk category. Simplified Operations, Centralized Reporting – Built-in tracking, configuration, and compliance support helps lenders manage enrollment, documentation, and servicing with minimal manual effort.
AI models becoming more specialized with reasoning capabilities to support sector-specific use cases, critical domains, zero-shot robot planning and real world simulation and are more willing to engage with classified information
AI models are maturing and becoming more specialized, with companies shifting from general-purpose chatbots to custom-built systems tailored for the government, robotics and regulated sectors. OpenAI has released o3‑pro, a premium version of its most advanced reasoning model that is optimized for science, education, programming, business and writing assistance. In essence, o3‑pro isn’t bringing new capabilities but rather refining existing ones through compute-intensive reasoning that is better suited to critical domains where hallucinations cost time or money. Google has released an upgraded preview of Gemini 2.5 Pro, its smartest model yet. This model excels at coding, math and science, as well as knowledge and reasoning capabilities. This model also has improved style and structure, making it more creative in responding. Gemini is Google’s flagship family of AI models and the first major natively multimodal model, meaning it was built from the ground up to be able to handle text, images, code and video. Anthropic has unveiled Claude Gov, a custom version of its Claude LLMs tailored for U.S. national security and intelligence applications. Models are more willing to engage with classified information instead of refusing to answer. Greater understanding of intelligence documents. Greater language and dialect proficiency related to national security matters. Improved understanding of cybersecurity data for intelligence analysis. Meta unveiled V‑JEPA 2, a world model trained on video that lets it understand the laws of physics to simulate the real world better. V-JEPA 2 can be used for zero-shot robot planning, meaning the robot doesn’t have to be pre-trained to interact with new objects. Mistral has launched Magistral, which comprises two chain‑of‑thought reasoning models. They are Magistral Small (24 billion parameters and open source) and Magistral Medium (proprietary, for enterprises). As Mistral’s first reasoning model, Magistral works for different enterprise use cases including structured calculations and programmatic logic to decision trees and rule-based systems.
Vertical AI startups targeting specific SaaS businesses with laser-focused solutions capture over $1 billion in combined funding in 2025 year-to-date, surpassing infrastructure and horizontal AI categories
Looking into 2025, fintech leads investor interest, with 52% of investors eyeing disruption in finance, followed closely by healthcare and enterprise tech, according to June reports from Pitchbook. Deep tech bets remain strong, with 58% of investors backing robotics plays from founders. A notable trend is the rise of vertical AI startups, which offer laser-focused solutions targeting specific SaaS incumbents (such as the previously-mentioned healthcare and financial services, as well as the legal sector). Vertical AI companies in these arenas captured over $1 billion in combined funding in 2025 year-to-date, surpassing infrastructure and horizontal AI categories. The push for capital is not limited to one area or sector, as AI investment continues to be the top topic for VC firms and founders right now. When it comes to accessing the gold rush of investor dollars around AI investment, leaders in the world of entrepreneurship need to keep these three key communication principles in mind: Context over Content: the ability to create a story that is real, relatable and powerful is the key to a successful pitch. Relatability and access is the key for AI investment – and that access begins with the context for the concept. That relatability is what creates the relationships that matter, when it comes to finding funding for your startup. Authenticity, Not Hype: accessing capital investment always starts at the same place: a conversation. Even in a high-stakes pitch, like the kind you see on Shark Tank, the conversation is where business decisions are made. Numbers Speak Louder than Words: Stanford’s AI index report says that training OpenAI’s ChatGPT cost more than $78 million in compute resources last year. In the world of AI startups, the cost of compute can eat away at sustainable margins, numbers speak louder than words. That’s why founders have to emphasize data, not adjectives, in order to give investors a clear picture of what an AI startup really needs.
Stablecoins, by enabling instant cross-border payments and costing below $0.01 could allow companies to shift to a financial streaming model with the size of local buffers dramatically reduced and could freeing up trillions in capital
Stablecoins will allow companies to shift to a financial streaming model that could free up trillions in capital for new investment, says Paul Brody. Things may look different in the future. If it costs nothing to move money globally and it can be done nearly instantly, the size of those local buffers can be dramatically reduced. Instead of keeping two weeks’ worth of expenses locally, including payroll, you might just choose to keep only a day’s worth on hand. A slightly larger cash pile can be kept centrally and sent out as needed. Companies could rebalance their global cash holdings every six hours. The result: a significant decrease in working capital requirements. What may start at a global level for large firms could spread quickly, and not just in the B2B space. At 5% interest rates, a $10 debt over the course of a year generates $0.50 in interest at current rates, which is about $0.04 per month. Each week of “float” you can save (or earn) is worth roughly $0.01. Given that payment costs on Ethereum Layer 2 networks are now routinely below $0.01, the answer is yes, it is worth it. Transaction costs are headed in only one direction, which means the economically efficient size and frequency of managing your money only gets more granular. Once upon time, the idea of streaming music on demand – and all the bandwidth and computation needed to do that – was seen as ridiculous. Now, it is barely a drop in the bucket compared to video streaming. There is no reason to think payments are different. Shifting to a financial streaming model could literally free up trillions in capital for new investment. Incentives for things like using services or energy at off-peak times might be much more effective when the payout is immediate.
Gemini’s new foundation model runs locally on bi-arm robotic devices, without accessing a data network and enables rapid experimentation with dexterous manipulation and adaptability to new tasks through fine-tuning
Google DeepMind introduced a vision language action (VLA) model that runs locally on robotic devices, without accessing a data network. The new Gemini Robotics On-Device robotics foundation model features general-purpose dexterity and fast task adaptation. “Since the model operates independent of a data network, it’s helpful for latency sensitive applications and ensures robustness in environments with intermittent or zero connectivity,” Google DeepMind Senior Director and Head of Robotics Carolina Parada said. Building on the task generalization and dexterity capabilities of Gemini Robotics, which was introduced in March, Gemini Robotics On-Device is meant for bi-arm robots and is designed to enable rapid experimentation with dexterous manipulation and adaptability to new tasks through fine-tuning. The model follows natural language instructions and is dexterous enough to perform tasks like unzipping bags, folding clothes, zipping a lunchbox, drawing a card, pouring salad dressing and assembling products. It is also Google DeepMind’s first VLA model that is available for fine-tuning. “While many tasks will work out of the box, developers can also choose to adapt the model to achieve better performance for their applications,” Parada said in the post. “Our model quickly adapts to new tasks, with as few as 50 to 100 demonstrations — indicating how well this on-device model can generalize its foundational knowledge to new tasks.”
“Vibe coding” startup Pythagora enables anyone including noncoders to develop full-stack applications with a series of prompts by unifying both front and back-end development with comprehensive debugging features into a single platform
“Vibe coding” startup Pythagora is looking to take artificial intelligence-powered software development to the next level with the launch of its platform today, saying it will help anyone – including noncoders – to develop full-stack applications with nothing more than a series of prompts. The company says its platform is built for both developers and nontechnical users, and unlike similar generative AI coding tools, unifies both front- and back-end development with comprehensive debugging features to bring the entire app creation experience into a single platform. Pythagora can be thought of as an “AI teammate” that lives inside software development tools such as VS Code and Cursor. It consists of a team of 14 specialized AI agents that can automate various coding-related tasks without supervision, taking care of everything from planning and writing code to testing, debugging and deployment. Pythagora essentially supercharges vibe coding, entirely eliminating the need to actually code. The tool is designed to be less like a coding assistant and more like a co-developer. What that means is it does more than just create the code – it also explains why the code is written as it is, and can walk users through any changes it has made. But users can still intervene and edit the code as they see fit, if they decide it’s necessary to do so.
Digital Asset’s public, permissionless DeFi platform is built from the ground up on Layer-1 blockchain to enable integration of real world assets (RWAs) and allows institutions to tailor privacy settings to their specific needs
Digital Asset has raised $135 million in its strategic funding round. This funding accelerates institutional and decentralized finance adoption on the Canton Network, the only public, permissionless Layer-1 blockchain that offers configurable privacy and institutional-grade compliance at scale. The capital will rapidly expand the integration of hundreds of billions of real-world assets (RWAs) onto Canton, building upon its already substantial deployment of diverse asset classes, including bonds, money market funds, alternative funds, commodities, repurchase agreements (repos), mortgages, life insurance, and annuities. The raise also deepens the relationship with several firms already part of the Canton Network and its Global Synchronizer Foundation, including, BNP Paribas, DRW, Goldman Sachs, Liberty City Ventures, QCP, and Tradeweb, all of whom have played various roles in either the testing, governance, infrastructure, or app development on the Network since its inception. This funding highlights the market’s recognition of Digital Asset’s vision and the pioneering design of the Canton Network, the only network built from the ground up with configurable on-chain privacy. By allowing institutions to tailor privacy settings to their specific needs, Canton overcomes the primary barrier to blockchain adoption: the conflict between transparency and financial confidentiality. As the first comprehensive solution of its kind, Canton bridges the gap between blockchain innovation and real-world financial compliance.
Quinn’s platform seamlessly embeds within financial platforms via API and enables advisors to deliver personalized, bespoke advice at scale in real-time by onboarding clients in under 12 minutes and generating financial plans in 30 seconds
Quinn has emerged from stealth and raised $11 million in Seed funding led by Viola Fintech with participation of existing investors, to transform how financial institutions deliver personalized wealth advice at scale. Traditional financial advisory models are constrained by a 1:100 advisor-to-client ratio, leaving millions underserved. Quinn breaks that barrier by leveraging advanced AI to substantially grow the market that has access to financial planning and advice. The platform seamlessly embeds within financial platforms, offering real-time and bespoke advice to every client, democratizing access to financial guidance. Quinn’s platform is available as an embedded, co-branded or fully white-labeled experience, allowing for seamless API integration with existing systems, enabling rapid deployment and immediate client impact. Key platform capabilities include: Advisor-Level Onboarding in Under 12 Minutes – Clients complete comprehensive financial assessments with unprecedented speed and ease. Instant Financial Plans in 30 Seconds – AI-generated financial plans empower users with actionable insights instantly. Boosted Upsell and Cross-sell Performance – Recommendations delivered in the context of a financial plan drive higher engagement with premium products and services. Scalable Advisor Productivity – By automating core advisory tasks, Quinn enables Certified Financial Planners® (CFP® Professionals) to serve significantly more clients without increasing headcount, freeing them to focus on high-value, human interactions.
Antier to enable real-time stablecoin remittances that bypass the conventional SWIFT system to reduce cross-border transaction costs by up to 80% and offer sub-60-second settlement within its neo-banking platform
Antier, a leading provider of Web3 financial infrastructure, has introduced the world’s first Stablecoin Remittance-as-a-Service (RaaS) embedded within its crypto neo-banking platform. This innovative solution aims to revolutionize traditional remittance by enabling real-time, blockchain-based settlements that bypass the conventional SWIFT system. The system is expected to reduce cross-border transaction costs by up to 80% and achieve settlement finality in less than a minute. The RaaS solution is deeply embedded within Antier’s Blockchain Neo-Banking suite, bridging blockchain speed and efficiency with regulatory rigor and trust. The platform is designed to ensure predictability, speed, and regulatory compliance in a globalized financial environment. Antier’s integrated stablecoin remittance stack includes features like fiat-to-stablecoin on-ramp compatibility, sub-60-second global stablecoin settlements, smart contract-based payout orchestration, and a stablecoin-agnostic architecture. The company is also working on a next-gen Web3 Super-App to unify digital finance, aiming to simplify blockchain protocols and support real-time treasury operations and cross-border financial innovation.