Relyance AI, a data governance platform provider that secured $32.1 million in Series B funding last October, is launching a new solution aimed at solving one of the most pressing challenges in enterprise AI adoption: understanding exactly how data moves through complex systems. The company’s new Data Journeys platform addresses a critical blind spot for organizations implementing AI — tracking not just where data resides, but how and why it’s being used across applications, cloud services, and third-party systems. Data Journeys provides comprehensive view, showing the complete data lifecycle from original collection through every transformation and use case. The system starts with code analysis rather than simply connecting to data repositories, giving it context about why data is being processed in specific ways. Data Journeys delivers value in four critical areas: First, compliance and risk management: The platform enables organizations to prove the integrity of their data practices when facing regulatory scrutiny. Second, precise bias detection: Rather than just examining the immediate dataset used to train a model, companies can trace potential bias to its source. Third, explainability and accountability: For high-stakes AI decisions like loan approvals or medical diagnoses, understanding the complete data provenance becomes essential. Finally, regulatory compliance: The platform provides a “mathematical proof point” that companies are using data appropriately, helping them navigate increasingly complex global regulations. Customers have seen 70-80% time savings in compliance documentation and evidence gathering.
Alacriti’s next-gen ACH solution provides a unified payments infrastructure to process wires and real-time payments through multiple rails while allowing configurable exception handling, posting and settlement
Alacriti has launched its enhanced version of Orbipay Payments Hub for ACH, bringing automation-first design and intelligent processing to the ACH payment lifecycle. By incorporating automation, intelligent routing, and real-time insights, Orbipay Payments Hub for ACH helps financial institutions reduce processing costs, improve transaction accuracy, and enhance customer experiences while maintaining compliance with Nacha operating rules and regulatory standards. This modern ACH processing solution provides seamless integration with the Federal Reserve’s clearing systems, supporting a full range of ACH transactions, including consumer payments, corporate disbursements, bill payments, and Same Day ACH. Designed with advanced automation, configurable exception handling, and embedded compliance tools, Orbipay Payments Hub for ACH helps financial institutions modernize operations and gain full visibility of their ACH performance while keeping their existing core banking systems or without changing their other existing systems. Beyond ACH, Orbipay Payments Hub provides a unified payments infrastructure to process wires and real-time payments through the RTP® network, the FedNow Service, and Visa Direct. By bringing these payment rails together under a single platform, financial institutions can optimize, report, and manage their operations today while preparing for future payment innovations. Key Features and Benefits of Orbipay Payments Hub for ACH: Automated exception handling, Seamless ecosystem integration, Configurable posting and settlement , Advanced fraud prevention and compliance, and Unified reporting and analytics.
Affirm expands beyond Experian to begin reporting all its pay-over-time loans to TransUnion but transactions will not be factored into traditional credit scores nor visible to lenders in the near-term
Affirm is expanding the credit reporting of its pay-over-time products to TransUnion. All Affirm pay-over-time loans issued from May 1, 2025 onward, including Pay in 4 and longer-term monthly installments, will be reported to TransUnion. Consumers will see details about all Affirm transactions on their TransUnion credit files, though these transactions will not be factored into traditional credit scores nor visible to lenders in the near-term. As more pay-over-time providers report account information to the credit bureaus, lenders who request TransUnion credit reports will also be able to view consumers’ pay-over-time history. In the future, as new credit scoring models are developed, this information may factor into consumers’ scores, with the aim of supporting more informed lending decisions and helping consumers build their credit histories. TransUnion research found nearly 40% of consumers who haven’t used buy now, pay later are likely or very likely to use them in the future. Notably, a higher 53% of non-users would be likely or very likely to use them if it had the potential to have a positive impact on credit scores.
New Sequential Monte Carlo algo makes AI-generated codes more accurate by using incremental static and dynamic analysis and instructing the LLM to adhere to the rules of each language
Researchers from MIT, McGill University, ETH Zurich, Johns Hopkins University, Yale and the Mila-Quebec Artificial Intelligence Institute have developed a new method for ensuring that AI-generated codes are more accurate and useful. In the paper, the researchers used Sequential Monte Carlo (SMC) to “tackle a number of challenging semantic parsing problems, guiding generation with incremental static and dynamic analysis.” Sequential Monte Carlo refers to a family of algorithms that help figure out solutions to filtering problems. This method spans various programming languages and instructs the LLM to adhere to the rules of each language. The group found that by adapting new sampling methods, AI models can be guided to follow programming language rules and even enhance the performance of small language models (SLMs), which are typically used for code generation, surpassing that of large language models. João Loula, co-lead writer of the paper, said that the method “could improve programming assistants, AI-powered data analysis and scientific discovery tools.” It can also cut compute costs and be more efficient than reranking methods. Key features of adapting SMC sampling to model generation include proposal distribution where the token-by-token sampling is guided by cheap constraints, important weights that correct for biases and resampling which reallocates compute effort towards partial generations.
Ending the separation of banking and commerce is a myth as bank holding company model and ring-fenced banking organization structure allows both banks and companies to operate as ‘data processing’ entities
U.S. banking organizations spend billions each year on technology as their data, machine learning and artificial intelligence, and cybersecurity needs become larger and more complex. Today’s banks and their nonbanking affiliates are tech companies: They squeeze everything they can into the permissible activity of “data processing.” And to stay competitive, they should Bank holding companies can also make noncontrolling investments in many commercial entities, subject to strict conditions. Under merchant banking powers, financial holding companies can own 100% of any commercial entity generally for 10 years, so long as they don’t manage it Whether the target demographic prefers to shop at big box stores, online retail platforms or both, chances are many customers will be interested in banking with them. Tech companies that develop devices, apps and other solutions are no different. And as the user experience becomes fundamentally more digital, the separation of banking and commerce washes out. It all starts to look like data processing. Digital assets like cryptocurrencies, stablecoins, digital currencies and the metaverse only continue to blur banking and commerce distinctions. One solution would be relatively simple and doesn’t involve abandoning the prudential tools that are the bedrock of banking law. And importantly, the same activities would be regulated and supervised in the same way. Any company, generally, should be able to own a ring-fenced depository institution. A ring-fenced banking organization more broadly would allow any company to own a bank holding company and its subsidiaries. Imagine a commercial org chart with an intermediate holding company — the true bank holding company — with a bank subsidiary: All the banking and financial activities would be within the ring-fenced structure. The Fed would keep its privileged purview. It could even impose commitments, source-of-strength, disclosure and other requirements on commercial parent companies. Antitrust law would serve as a backstop for other competitive concerns. The federal or state banking regulators could focus on the banks. There would be the same strong capital and liquidity requirements, limitations on transactions with affiliates and loans to insiders — all of it.
Crypto firms are seeking bank charters and trust licenses with an eye to get direct access to Federal Reserve payment systems, hold customer deposits, custody reserves for stablecoins and to offer loans or other banking services
In a sign of the evolving times, Circle, the FinTech firm best known for the USDC stablecoin, unveiled Monday an initiative called the Circle Payments Network (CPN), which aims to modernize how value flows worldwide. While Circle is building out the CPN platform, it’s also part of a broader movement of crypto companies pushing into the regulated banking sector. If successful, a company like Circle could hold customer deposits, custody reserves for stablecoins, and make loans or offer other banking services, all under the supervision of bank regulators. By obtaining bank charters or trust licenses now, crypto companies could get ahead of impending regulations and shape them. Chartered institutions also have certain advantages. They can potentially get direct access to Federal Reserve payment systems, hold customer dollar balances in central bank accounts, and operate across all 50 states without needing a patchwork of state licenses. Separately, crypto companies like Paxos and Coinbase, as well as Circle, are pursuing bank charters, essentially seeking to become part of the very banking system that has historically kept them at arm’s length. It’s worth noting that not all these firms are pursuing the same type of charter. Circle and BitGo are reportedly aiming for full-service national bank charters. Others have considered national trust bank charters or even industrial loan company (ILC) charters.
Amazon Bedrock serverless endpoint system dynamically predicts the response quality of each model and efficiently routes it to the most appropriate model based on cost and response quality
Amazon Bedrock has announced the general availability of its Intelligent Prompt Routing, a serverless endpoint that efficiently routes requests between different foundation models within the same model family. The system dynamically predicts the response quality of each model for a request and routes the request to the model it determines is most appropriate based on cost and response quality. The system incorporates state-of-the-art methods for training routers for different sets of models, tasks, and prompts. Users can use the default prompt routers provided by Amazon Bedrock or configure their own prompt routers to adjust for performance linearly between the performance of two candidate LLMs. The system has reduced the overhead of added components by over 20% to approximately 85 ms (P90), resulting in an overall latency and cost benefit compared to always hitting the larger/more expensive model. Amazon Bedrock has conducted internal tests with proprietary and public data to evaluate the system’s performance metrics.
Codacy’s solution integrates directly with AI coding assistants to enforce coding standards using MCP server, flagging or fixing issues in real-time
Codacy, provider of automated code quality and security solutions, launched Codacy Guardrails, a groundbreaking new product designed to bring real-time security, compliance, and quality enforcement to AI-generated code. Guardrails is the first technology to make AI-generated code trustworthy and compliant by checking it before it ever reaches the developer. Codacy Guardrails is the first solution of its kind that integrates directly with AI coding assistants to enforce coding standards and prevent non-compliant code from being generated in the first place. Built on Codacy’s SOC2-compliant platform, Codacy Guardrails empowers teams to define their own secure development policies and apply them across every AI-generated prompt. With Codacy Guardrails, AI-assisted tools gain full access to the security and quality context of a team’s codebase. At the core of the product is the Codacy MCP server, which connects development environments to the organization’s code standards. This gives LLMs the ability to reason about policies, flag or fix issues in real time, and deliver code that’s compliant by default. Guardrails integrates with popular IDEs like Cursor AI and Windsurf as well as VSCode and IntelliJ through Codacy’s plugin, allowing developers to apply guardrails directly within their existing workflows.
Docker to simplify AI software delivery by containerizing MCP servers along with offering an enterprise-ready toolkit and a centralized platform to discover and manage them from a catalog of 100+ servers
Software containerization company Docker is launching the Docker MCP Catalog and Docker MCP Toolkit, which bring more of the AI workflow into the existing Docker developer experience and simplify AI software delivery. The new offerings are based on the emerging Model Context Protocol standard created by its partner Anthropic PBC. Docker argues that the simplest way to use Anthropic’s MCP to improve LLMs is to containerize it. To do that, it offers tools such as Docker Desktop for building, testing and running MCP servers, as well as Docker Hub to distribute their container images, and Docker Scout to ensure they’re secure. By packaging MCP servers as containers, developers can eliminate the hassles of installing dependencies and configuring their runtime environments. The Docker MCP Catalog, integrated within Docker Hub, is a centralized way for developers to discover, run and manage MCP servers, while the Docker MCP Toolkit offers “enterprise-ready tooling” for putting AI applications to work. At launch, there are more than 100 MCP servers available within Docker MCP Catalog. President and Chief Operating Officer Mark Cavage explained that “The Docker MCP Catalog brings that all together in one place, a trusted, developer-friendly experience within Docker Hub, where tools are verified, secure, and easy to run.”
PayPal to offer users a 3.7% annual rewards rate on holdings of the PayPal USD (PYUSD) stablecoin in their PayPal or Venmo wallets
PayPal Holdings will launch a rewards program this summer that will allow users to earn rewards on holdings of the PayPal USD (PYUSD) stablecoin in their PayPal or Venmo wallets. The company expects to offer a 3.7% annual rewards rate upon the launch of the program, although it can change the rate at any time. Users will be able to immediately use the rewards to send to other PayPal or Venmo users, fund international transfers, exchange for fiat, convert to other cryptocurrencies or make purchases at merchants with PayPal Checkout. “Consumers and businesses use PYUSD today for commerce, crypto, peer-to-peer transfers and B2B payments,” PayPal President and CEO Alex Chriss said. Michelle Gill, general manager of small business and financial services at PayPal, said the company expects to use the stablecoin to power a new B2B bill pay offering. “B2B bill pay is tapping into a $2 trillion market,” Gill said. “This is exciting not just for our merchants, but also for PayPal in that it opens up a brand-new network. … They now get to invite their vendors and their suppliers to join the PayPal ecosystem. … By the end of 2025, we hope to power all of this through PYUSD.”