Apollo Global Management’s tokenized private credit fund, managed by Apollo and Securitize, has reached a $100 million in on-chain assets, highlighting the growing acceptance of blockchain technology in traditional finance. The fund targets key investment areas such as Corporate Direct Lending, Asset-Backed Lending, Performing Credit, Dislocated Credit, and Structured Credit. The $100 million milestone aligns with industry projections, which estimate the global tokenization market will grow from $2.3 billion in 2021 to $5.6 billion by 2026. Securitize’s technology enables the fund to operate across multiple blockchains, enhancing accessibility for institutional investors. The partnership builds on a growing collaboration between traditional finance and digital asset firms, and Securitize’s platform streamlines private market efficiency, offering improved transparency and potentially lower interest rates. However, challenges remain, such as the decentralized nature of blockchain platforms.
Aquant’s “retrieval-augmented conversation” feature allows LLMs to retrieve and present information to users that allows them natively to act as a guided domain expert
Aquant Inc., the provider of an AI platform for service professionals, introduced “retrieval-augmented conversation,” a new way for LLMs to retrieve and present information to users that allows them natively to act as a guided domain expert instead of receiving and presenting knowledge as a single all-in-one answer. RAC can be thought of as an expert technician that is aware of its capacity and capabilities, Indresh Satyanarayana, vice president of product technology and labs, and the father of retrieval-augmented conversation, told. It helps the AI look at a user’s question and ask follow-up questions to fill knowledge gaps and generate tailored solutions. Unlike RAG, RAC introduces dynamic turn-taking, much more like a human conversation with an expert in the field in question. It’s designed to provide “bite-sized actions,” which he says avoids cognitive overload for the user. Not only that, RAC can incorporate even more data points into its conversational context depending on the persona developers want to build into their AI app. “It retrieves not only manuals but transactional data, job history, parts catalogs, internet of things readings, and key performance indicator targets, then reasons over that richer context to recommend the action that best balances cost, risk and time,” said Satyanarayana. RAC does not fundamentally replace RAG; it will still perform the retrieval-augmented portion. Documents still need to be searched and retrieved, and this aspect will guide the conversation for the user. On the other end, developers will have a chance to decide how “chatty” their app acts. It can do one-to-one questions solving one ambiguity at a time and then provide a final answer after they have all been resolved. Alternatively, they could develop an app that can resolve multiple questions at once, the way some people can hold multiple threads of conversation at the same time — like many open tabs in Chrome while researching — before resolving the problem.
Embedded payments technology can help organizations reduce the amount of time finance personnel spend processing expense documentation
Organizations often struggle with managing expenses due to the manual, time-consuming, and prone to delays, errors, and misuse. In a recent podcast, Susie Shyatt, Business Development Executive at B4B Payments, and Hugh Thomas, Lead Commercial Payments Analyst at Javelin Strategy & Research, discussed common challenges businesses face in managing expenses and how embedded payments can help streamline this inefficient process. One of the most common issues in the expense management process is employees being required to use their own funds to cover company expenses. This requires sufficient funds, which can be challenging for costly business trips involving airfare and hotel stays. Additionally, once the employee returns, they must provide documentation for their expenses, which then needs to be manually processed, leading to delays or errors in reimbursement. There is also the risk of abuse in the process, which has been inadvertently encouraged by management. Embedded payments technology can help organizations reduce the amount of time finance personnel spend processing expense documentation, freeing them up to focus on more strategic tasks. It also gives organizations greater control over how funds are being spent, as there is often a lack of transparency into how and where those funds are sourced when using personal funds to cover expenses. Removing the inertia barrier is crucial for organizations to adopt embedded payments in the expense management process. The first step for these organizations is to take a deep dive into their expense management process from end to end. They should talk to their accounts payable and payroll staff, as well as any employee who regularly participates in the expense reimbursement program, and identify the true pain points in their current process. Once the organization has identified its needs, it can begin to address the inefficiencies in this critical function. Knowing exactly what you need not only helps with efficiencies within your company but also helps with cost savings as well.
Lessons learned from agentic AI leaders enterprise leaders now report more complex ROI patterns that demand different technical architectures
On day two of VB Transform 2025, a panel moderated by Joanne Chen, general partner at Foundation Capital, included Shawn Malhotra, CTO at Rocket Companies, Shailesh Nalawadi, head of product at Sendbird, and Thys Waanders, SVP of AI transformation at Cognigy; shared discovery: Companies that build evaluation and orchestration infrastructure first are successful, while those rushing to production with powerful models fail at scale. A key part of engineering AI agent for success is understanding the return on investment (ROI). Early AI agent deployments focused on cost reduction. While that remains a key component, enterprise leaders now report more complex ROI patterns that demand different technical architectures. For Cognigy, Waanders noted that cost per call is a key metric. He said that if AI agents are used to automate parts of those calls, it’s possible to reduce the average handling time per call. Saving is one thing; making more revenue is another. Malhotra reported that his team has seen conversion improvements: As clients get the answers to their questions faster and have a good experience, they are converting at higher rates. Nalawadi highlighted entirely new revenue capabilities through proactive outreach. His team enables proactive customer service, reaching out before customers even realize they have a problem. While there are solid ROI opportunities for enterprises that deploy agentic AI, there are also some challenges in production deployments. Nalawadi identified the core technical failure: Companies build AI agents without evaluation infrastructure. He noted that it’s just not possible to predict every possible input or write comprehensive test cases for natural language interactions. Nalawadi’s team learned this through customer service deployments across retail, food delivery and financial services. Standard quality assurance approaches missed edge cases that emerged in production. “We have a feature that we’re releasing soon that is about simulating potential conversations,” Waanders explained. “So it’s essentially AI agents testing AI agents.” The approach tests demographic variations, emotional states and edge cases that human QA teams can’t cover comprehensively.
CC Signals framework will allow creators to publish a document that specifies how AI models may and may not use their content
Creative Commons has previewed an upcoming framework designed to help creators manage how artificial intelligence models use their content. The framework, which is called CC Signals. The new CC Signals framework will allow creators to publish a document that specifies how AI models may and may not use their content. This document will “range in enforceability, legally binding in some cases and normative in others,” Creative Commons staffers noted. The reason is that the extent to which creators can limit AI models’ use of their works varies by jurisdiction. Creative Commons detailed that the framework will include four content usage stipulations. Each one sets forth a different set of requirements for how AI models may interact with a file. CC Signals will allow creators to apply up to two of the four stipulations to a given file. Using CC Signals, creators can also indicate that they expect compensation from AI developers who use their work. That compensation may take several forms. CC Signals will allow for monetary or in-kind contributions to a file’s creators, as well as to the broader “ecosystem from which you are benefiting.” According to Creative Commons, there will be support multiple definitions of open-source AI. Content creators may require that a neural network’s weights be available under a free license. They can also go further and mandate that the tooling with which the algorithm was developed be open source as well.
Crypto exchange Kraken debuts P2P payments taking on PayPal, Venmo and Block’s CashApp; also plans physical and virtual cards as well as pay-in-advance services like loans
Crypto exchange Kraken launched a peer-to-peer payments app that enables users to send and receive funds – in both cryptocurrency and fiat currency – across more than a hundred countries. The move is a bid to expand Kraken’s offerings beyond its digital asset trading business, and puts the firm in competition with PayPal, Venmo and Block’s CashApp. Krak users will have a dedicated spend account and will be able to instantly send and request payments across 300 different assets, including crypto and local currencies, the company said in a press release. Crypto transfers will be made using blockchain technology, while Kraken will make cash transfers internally without using external banking infrastructure. “We’re able to move money across borders right off the bat, because that’s what we do from a trading perspective in our venues, and we’ve actually already spent over 10 years building out that system for money transmitter licenses in all the jurisdictions,” said Arjun Sethi, co-CEO of Kraken. “You have to do that as an exchange anyways, and so what we realized is that our customers just wanted to do more with their money.” Kraken plans to launch a series of products through Krak in the future, including physical and virtual cards as well as pay-in-advance services like loans, the company said.
Volatility breeds interest in fixed-income investments for the ability to gain earnings even when the market is flat or choppy
Curiosity in fixed income sparked after interest rates started to move higher three years ago, said Erin Lyons, co-head of credit research firm CreditSights. “It didn’t make sense for you to put your cash there. So we saw a lot of investors focusing on equity markets and then moving into alternatives,” she said. “Now that rates are back up … it’s a viable asset class.” Income and yield-focused portfolios are gaining popularity with clients for several reasons, said Mike Casey, president of American Executive Advisors in Washington, D.C. One of the main factors is the ability to gain earnings even when the market is flat or choppy, he said. “A portfolio with strong yield and income can help offset some downside volatility and preserve overall portfolio value,” he said. “There are more income and yield generating options now than ever before including traditional bonds, structured products, private credit funds, equity income ETFs and more.” Dane May, co-founder and principal of DePaolo & May Strategic Wealth has also seen a strong resurgence in interest in fixed income, particularly in shorter-duration instruments. Even more notably, he said, is rising interest in ETFs that stack Treasury bill yields with additional income from risk premiums. These are similar in spirit to structured notes but delivered in ETF form, such as Simplify Enhanced Income ETF (HIGH) and Simplify Treasury Option Income ETF (BUCK). “After back-to-back years of strong equity performance, combined with a new administration pushing meaningful policy shifts, many investors are turning to fixed income. Add in attractive T-bill rates and greater access to ETF-based strategies that reduce correlation without relying on traditional credit or duration, and it’s easy to see why this space is gaining traction.” Henry Yoshida, CEO and founder of Rocket Dollar said “If fixed income serves as a tool in your portfolio to generate an income stream, then it’s fulfilling a specific purpose regardless of the immediate interest rate environment. However, if you are holding fixed income in your portfolio solely for diversification, investors may benefit from other assets that are noncorrelated to equities, such as private credit, real estate and other alternative investments.” When it comes to investing, it is important to have a carefully planned mix of bonds as well as stocks, and to diversify the portfolio within those different types of investments, said David B. Rosenstrock, director of financial planning and investments at Wharton Wealth Planning. This can help investors ride out periods of uncertainty, such as the one we are currently experiencing with tariffs, he said. One role of bonds in a portfolio in addition to providing income is to smooth out and reduce the volatility, said Rosenstrock. Bonds can provide an additional stream of income in a portfolio, with less risk than stocks, he said.
Universities athletic departments enter partnerships with PayPal to enable institutional payments for student-athletes in new revenue sharing model
PayPal announced multi-year agreements with the Big Ten and Big 12 Conferences that will modernize the distribution of institutional payments from universities to student-athletes in a new revenue-sharing model. The new institutional payments initiative enables athletic departments to seamlessly dispense payments through PayPal, ensuring a secure, efficient, and transparent way to distribute funds to payees. With the funds in their wallets, students will have the option to access all the benefits of PayPal’s commerce ecosystem, from seamlessly buying tickets to a sporting event or purchasing their books for the year at the university bookstore. The recent court decision, which allows colleges and universities to share revenue directly with student-athletes, stands to revolutionize college sports. This partnership helps make that real by distributing those funds to student-athletes in a fast, simple, and secure way. Venmo is doubling down in its focus on younger consumers by expanding its position as a cornerstone of campus life and commerce. Venmo will be the presenting partner of the first-ever Big Ten Rivalry Series, spanning football, men’s and women’s basketball, embedding the brand in some of the most iconic matchups in college sports. With the Big 12, Venmo will serve as the official partner of the Big 12 Conference across Big 12 football, basketball, and Olympic sports championships for both men and women. Venmo will also be seen across all 16 institutions’ athletic events. Venmo is accelerating the expansion of its commerce capabilities, introducing even more ways to use a Venmo balance beyond peer-to-peer, from everyday purchases on campus to earning rewards in-store and online 1 with the Venmo Debit Mastercard. Venmo will be working with the Big Ten and Big 12 to enable acceptance for real-world campus spending, including at bookstores, for ticketing, concessions, and merchandise, giving students more flexibility to shop and pay with the app they already use every day. Students who use the Venmo Debit Card can for a limited time unlock up to 15% cash back at select national brands with added features like tap-to-pay when added to a mobile wallet, automatic transfers to top up your balance, and the ability to shop internationally anywhere Mastercard is accepted with no foreign transaction fees.
Wirex launches institutional-grade stablecoin payments on Fireblocks digital asset platform- issuing fully stablecoin-backed Visa debit cards, opening stablecoin checking accounts, and managing high-volume treasury and payments
Wirex Pay Chain is now officially supported on Fireblocks, the leading digital asset and payments infrastructure platform. This integration enables Fireblocks’ institutional clients to easily access Wirex Pay’s self-custodial stablecoin payment infrastructure, offering a secure and scalable gateway to stablecoin innovation. Through this support, Fireblocks customers can now issue fully stablecoin-backed Visa debit cards, open stablecoin checking accounts, and manage high-volume treasury and payments — all while retaining complete control over their assets. Wirex Pay redefines enterprise-grade finance with a focus on control, flexibility, and regulatory alignment: Retail App – Stablecoin Checking Accounts: Open stablecoin-backed current accounts with a Visa debit card, enabling instant global payments and yield on balances. Business Banking – Corporate Stablecoin Accounts: Manage fiat and stablecoins with built-in treasury, corporate cards, and real-time settlement—all fully self-custodial. Stablecoin BaaS – Stablecoin Infrastructure APIsStablecoin Infrastructure APIs: Embed stablecoin accounts and card issuing into any fintech or wallet product using modular APIs and smart contracts. Pavel Matveev, Co-Founder of Wirex said, “This unlocks a powerful new chapter in institutional stablecoin adoption — bringing together security and programmable payments infrastructure to Fireblocks’ digital asset network. Now, institutions can launch stablecoin-backed card programs and checking accounts at speed, with full control and built-in compliance.”
LinkedIn is taking a multi-agent approach, using a collection of agents collaborating to get the job done; a supervisor agent orchestrates all the tasks among other agents
Going beyond its popular recommender systems and AI-powered search, the company’s AI agent sources and recruits job candidates through a simple natural language interface. LinkedIn is taking a multi-agent approach, using a collection of agents collaborating to get the job done. A supervisor agent orchestrates all the tasks among other agents, including intake and sourcing agents that are “good at one and only one job.” All communication occurs through the supervisor agent, which receives input from human users regarding role qualifications and other details. That agent then provides context to a sourcing agent, which culls through recruiter search stacks and sources candidates along with descriptions on why they might be a good fit for the job. That information is then returned to the supervisor agent, which begins actively interacting with the human user. The agent can then refine qualifications and begin sourcing candidates, working for the hiring manager “both synchronously and asynchronously.” “It knows when to delegate the task to what agent, how to collect feedback and display to the user,” said Deepak Agarwal, chief AI officer at LinkedIn. The goal is to “deeply personalize” experiences with AI that adapts to preferences, learns from behaviors and continues to evolve and improve the more that users interact with it. LinkedIn provides engineers with different algorithms based on RL, supervised fine tuning, pruning, quantization and distillation to use out of the box without worrying about GPU optimization or FLOPS, so they can begin running algorithms and training, said Tejas Dharamsi, LinkedIn senior staff software engineer. In building out its models, LinkedIn focuses on several factors, including reliability, trust, privacy, personalization and price, he said. Models must provide consistent outputs without getting derailed. Users also want to know that they can rely on agents to be consistent; that their work is secure; that past interactions are being used to personalize; and that costs don’t skyrocket.