Nubank announces the launch of Automated Pix, a new option to pay recurring bills with convenience and security. The new feature will be accompanied by the ‘Search Upcoming Bills’ feature, which will give customers complete freedom to choose how and when to pay – whether fully automatically or in a facilitated manner, with alerts and simple one-click approvals directly in the app. The “Search Upcoming Bills” feature is ideal for customers who prefer to review their bills before each payment, helping them maintain financial control throughout the month with autonomy. The tool notifies customers about bills that follow the recurring billing model. With Automated Pix, customers can easily set up payments for recurring bills using Pix. The security of Automated Pix follows the high standards already adopted by Nubank for other Pix features, including confirmation via PIN for each manually authorized payment, real-time fraud and suspicious key alerts, Street Mode (Modo Rua), which limits transactions outside secure networks, daily Pix limits controls and a “trusted contacts list” that can be set up. The billing company will provide a QR Code or the option to copy and paste the Pix key for payment. By scanning the code or pasting the key into the Nubank app, the customer will automatically identify if the payment is enabled for Automated Pix. There will be two options: Enable Automated Payment and Pay upon approval.
Digital wealth platform Sidekick’s to offer mass affluents access to high-growth private companies through a professionally managed fund by investing just £10,000
Sidekick, a new UK digital wealth platform built to serve six-figure earners who’ve outgrown basic financial products but don’t have the millions needed to access private banks, has launched. Sidekick is one of a number of entrants targeting the mass affluent market, using technology to offer products and services once reserved for the super rich. Among Sidekick’s offerings is access to private equity-style investing for just £10,000. Eligible individuals can get access to a regulated Long-Term Asset Fund, which allows clients to invest in high-growth private companies through a professionally managed fund without needing the six-figure minimums usually required. Beyond investments, users get access to an account that automatically spreads deposits across a panel of UK-regulated banks behind the scenes, enabling up to £255,000 of FSCS protection – all through a single interface. And, for higher target returns, its Smart Cash product invests short-term funds into actively managed money market instruments, designed to outperform traditional savings rates while keeping funds accessible.
NiCE-Snowflake partnership to enable enterprises to operationalize customer interaction data at scale through seamless, secure sharing of CX data across the front, middle and back office
NiCE announced a strategic collaboration with Snowflake, the AI Data Cloud company, to unlock the full value of customer interaction data by enabling seamless, secure data sharing across the front, middle and back office through Snowflake Secure Data Sharing. This collaboration combines NiCE CXone Mpower’s AI for customer service automation with Snowflake’s easy, connected, and trusted platform, enabling joint customers to seamlessly access and update data to automate customer service at scale. By working with Snowflake, the two companies will be able to deliver immediate value for customers and unlock new opportunities across the enterprise landscape. NiCE selected Snowflake for its ability to power secure, governed data collaboration and its shared commitment to eliminating operational silos. As a core component of every CXone Mpower bundle, Snowflake provides the foundation for the CXone Mpower data lake, centralizing all interaction data from across the platform and enabling that data to be merged with associated data beyond the front office. This extends the depth and breadth of CXone Mpower, enabling customers to leverage reporting, dashboarding, analytics and AI, from a single, trusted and ecosystem-wide source of truth. By expanding the reach of CX data into middle and back-office systems, organizations will be able to automate processes such as service fulfillment, billing, claims handling, and account updates, dramatically improving speed, accuracy, and efficiency. Customers can leverage CXone Mpower’s built-in integration with Snowflake to securely share and activate customer interaction data across their enterprise, either as part of their current CXone Mpower bundle or through expanded enterprise automation initiatives. With CXone Mpower analyzing hundreds of customer attributes per interaction, Snowflake provides the secure, scalable foundation to store, share, and activate this rich data across the enterprise. This collaboration empowers enterprises to operationalize interaction data at scale, integrate it seamlessly into enterprise ecosystems, and accelerate the development of AI-driven CX innovations.
Ubyx aims to provide a clearing system enabling anyone to easily on and off-ramp between bank accounts and stablecoins supporting corporates that want to use stablecoins for cross border payments
Ubyx announced a $10 million seed funding round led by Galaxy Ventures. Other backers in the round include Founders Fund, stablecoin issuer Paxos, Payoneer and others. Ubyx aims to provide a clearing system enabling anyone to easily on and off-ramp between bank accounts and stablecoins. This is a particular issue for corporates that want to use stablecoins for cross border payments, but might find the accounting for holding them on their balance sheet tricky. This challenge has created opportunities for infrastructure providers to fill the gap. While the likes of stablecoin issuer Circle has the scale to build its own Circle Payments Network, not all stablecoin issuers have that luxury. Plus, numerous other stablecoin infrastructure startups are also duplicating effort in building their own distribution. Ubyx aims to provide this distribution and redemption service for numerous stablecoins. “Stablecoins become ubiquitous when there is a shared acceptance network, just like cards. Traditional banks and fintechs should provide wallets to accept a wide range of regulated stablecoins on many public-permissionless blockchains,” said Mike Giampapa, General Partner of Galaxy Ventures.
New report shows while 85% of organizations trust their BI dashboards, only 58% say the same for their AI/ML model outputs, implying trust in AI remains elusive
Ataccama’s new report in partnership with BARC finds that while 58% of organizations have implemented or optimized data observability programs – systems that monitor detect, and resolve data quality and pipeline issues in real-time – 42% still say they do not trust the outputs of their AI/ML models. The findings reflect a critical shift. Adoption is no longer a barrier. Most organizations have tools in place to monitor pipelines and enforce data policies. But trust in AI remains elusive. While 85% of organizations trust their BI dashboards, only 58% say the same for their AI/ML model outputs. The gap is widening as models rely increasingly on unstructured data and inputs that traditional observability tools were never designed to monitor or validate. 51% of respondents cite skills gaps as a primary barrier to observability maturity, followed by budget constraints and lack of cross-functional alignment. But leading teams are pushing it further, embedding observability into designing, delivering, and maintaining data across domains. When observability is deeply connected to automated data quality, teams gain more than visibility: they gain confidence that the data powering their models can be trusted. The report also underscores how unstructured data is reshaping observability strategies. Kevin Petrie, Vice President at BARC said “We’re seeing a shift: leading enterprises aren’t just monitoring data; they’re addressing the full lifecycle of AI/ML inputs. That means automating quality checks, embedding governance controls into data pipelines, and adapting their processes to observe dynamic unstructured objects. This report shows that observability is evolving from a niche practice into a mainstream requirement for Responsible AI.”
TD Bank survey finds 70% of Americans are comfortable with AI being used for fraud detection and 64% for credit score calculations, while 43% would use AI in combination with a human advisor for financial planning
According to a new TD Bank survey, 89% of respondents say they are comfortable using and adapting to new technology in their daily life, while about seven in ten (68%) say they are at least somewhat familiar with artificial intelligence (AI), its uses and applications in their day-to-day lives. Half (50%) of respondents trust AI to provide reliable, competent information, and 65% see its potential to expand access to financial tools, a sign that perceptions are shifting as AI tools become more familiar and visible in everyday life. The survey revealed that Americans trust AI just as much as news stations (50%) and twice as much as social media influencers (25%) to provide information that is honest, reliable and competent. However, consumers still place greater trust in friends and family (90%) and banks (83%) for accurate information. A majority of Americans are comfortable with AI being used for fraud detection (70%) and credit score calculations (64%). While fewer are ready to hand over major decisions, 44% say they are comfortable using self-serve AI enabled tools to manage investments, and 43% would use AI in combination with a human advisor for financial planning, showing significant interest in hybrid solutions. As for personal finance choices, respondents were most comfortable using AI financial tools for budgeting (60%) and automating savings goals (59%) but showed less confidence in AI handling more intricate tasks such as retirement planning (48%) and investing (44%). 51% see value in AI improving financial decision-making, indicating a path forward as comfort and awareness increase. Interestingly, 48% agree that using AI would help them avoid embarrassing discussions with bank representatives, suggesting AI can improve approachability and drive self-service functionality. As a result of banks implementing AI, many Americans expect benefits such as 24/7 banking access (48%), improved transaction efficiency (40%) and reduced costs (32%).
Maven AGI’s AI agents support the full customer journey with a focus on complex, high-friction environments by unifying systems, syncing functions, and orchestrating real-time action across the enterprise
Maven AGI, the enterprise AI company unifying the full customer journey, has raised $50 million in Series B funding. The company’s Business AGI platform integrates seamlessly with enterprise systems to resolve issues, surface real-time insights, and improve performance at every customer touchpoint. Maven AGI builds enterprise-ready AI agents to support the full customer journey, with a focus on complex, high-friction enterprise environments. Its platform serves as a connected, intelligent operating layer that unifies systems, syncs functions, and orchestrates real-time action across the enterprise. Maven’s mission is to build Business AGI. “With fragmented systems slowing innovation, enterprises are urgently seeking a unified approach. Maven delivers on that need with AI that securely connects people, systems, and data across the entire customer lifecycle,” said Jonathan Corbin, CEO and co-founder of Maven AGI. The Series B funding will fuel Maven’s continued expansion, including accelerated product development and go-to-market efforts. In a fast-moving market, the company is prioritizing rapid distribution and working closely with a network of partners and investors who have scaled some of the most successful technology companies in the world.
Peymo’s hybrid banking platform uses AI agents that seamlessly integrate fiat, crypto wallets, tokenised assets, and embedded finance into a single stack and identifies the smartest route, timing, and format for each transaction
Peymo Ltd, a UK-based FinTech, has launched the world’s first AI-powered multi-hybrid bank — a digital finance platform that seamlessly integrates fiat banking, crypto wallets, tokenised assets, and embedded finance into one unified system. Built on proprietary modular architecture, the platform enables users to manage GBP, EUR, crypto assets, and branded debit cards in one place, while enterprises can integrate full banking functions via simple APIs. “We make complex finance invisible,” said Tomas Bartos, Founder of Peymo. “By fusing AI, fiat, crypto and embedded finance into a single stack, we’re delivering the next generation of banking — and it’s ready today.” Branded as “Peymo AI – Smarter Banking for Every User,” the platform delivers powerful AI through a voice-first interface with continuous listening, instant intent recognition, and multimodal confirmations to enable secure, hands-free banking. Behind the interface, five specialised AI agents monitor user behavior, track market activity, optimise payments, and ensure asset protection in real time. A built-in smart referral engine identifies potential users within a network, dispatches personalised invitations via WhatsApp or voice, and tracks referral success. Operationally, Peymo’s AI powers instant onboarding in under five seconds, continuous transaction monitoring for faster clearances and real-time deposits, and self-improving system code through usage-based AI feedback to keep the platform fast, compliant, and lean. As a true hybrid financial engine, Peymo’s AI also helps users navigate their entire portfolio — from crypto to fiat, gold to tokenised assets — identifying the smartest route, timing, and format for each transaction, ensuring efficiency, transparency, and full control. Its autonomous architecture supports scalable growth by identifying high-value B2B leads and ideal embedded finance partners who can adopt Peymo’s wallets, KYC tools, cards, or payment systems at scale. Simultaneously, human-sounding voice agents engage users directly — offering guidance, upsell suggestions, and personalised support to unlock unused features, deliver premium upgrades, and execute activation nudges, with the system scalable to millions of tailored interactions per hour.
Algolia’s MCP Server enables LLMs and agentic AI systems to interact with APIs, retrieve, reason with, and act on real-time business context at scale through a standards-based, secure runtime
Algolia announced the release of its MCP Server, the first component in a broader strategy to support the next generation of AI agents. This new offering enables large language models (LLMs) and autonomous agents to retrieve, reason with, and act on real-time business context from Algolia, safely and at scale. Bharat Guruprakash, Chief Product Officer at Algolia. “By exposing Algolia’s APIs to agents, we’re enabling systems that adapt in real time, honor business rules, and reduce the time between problem and resolution.” With this launch, Algolia enables an agentic AI ecosystem where software powered by language models is no longer limited to answering questions, but can autonomously take actions, make decisions, and interact with APIs. The MCP Server is the first proof point in a long-term roadmap aimed at positioning Algolia as both the retrieval layer for agents and a trusted foundation for agent-oriented applications. With the Algolia MCP Server, agents can now access Algolia’s search, analytics, recommendations, and index configuration APIs through a standards-based, secure runtime. This turns Algolia into a real-time context surface for agents embedded in commerce, service, and productivity experiences. Additionally, Algolia’s explainability framework with its AI comes along for the ride for enhanced transparency. More broadly, agents can: Retrieve business; Make Updates Freely; Chain decisions across workflows. With the MCP Server and upcoming tools, Algolia is eliminating friction in the development of agentic AI systems—empowering developers to increasingly: Define agent behaviors around Algolia’s APIs; Rely on Algolia’s safety scaffolding; Compose agents that span systems.
Typedef turns AI prototypes into scalable, production-ready workloads by managing all the complex properties of mixed AI workloads through a clean, composable interface using APIs, relational models and serverless tech
Typedef Inc., turning AI prototypes into scalable, production-ready workloads that generate immediate business value, has come out of stealth mode with $5.5 million in seed funding. With a new purpose-built AI data infrastructure for modern workloads, Typedef is helping AI and data teams overcome the well-documented epidemic affecting the bulk of enterprise AI projects – failure to scale. The solution is built from the ground up with features to build, deploy, and scale production-ready AI workflows – deterministic workloads on top of non-deterministic LLMs. Typedef makes it easy to run scalable LLM-powered pipelines for semantic analysis with minimal operational overhead. The developer-friendly solution manages all the complex properties of mixed AI workloads like token limits, context windows, and chunking through a clean, composable interface with the APIs and relational models engineers recognize. Typedef allows for rapid, iterative prompt and pipeline experimentation to quickly determine production-ready workloads that will demonstrate value – then realize that potential at scale. Typedef is completely serverless bypassing any infrastructure provisioning or configuration. Users simply download the open-source client library, connect their data sources and start building their AI or agentic pipelines with just a few lines of code. No complex setup, no infrastructure to provision, no brittle custom integrations to troubleshoot.