Cybersecurity compliance startup Vanta has launched Vanta AI Agent, a new agent designed to handle end-to-end workflows autonomously across a company’s entire compliance program. The new agent contextually guides organizations through key tasks, accurately identifies issues and inconsistencies humans might miss and proactively takes action on their behalf, while keeping governance, risk and compliance teams informed and in control. The agent uses program context to offer timely support and surface issues before they become costly errors. It reduces human error by taking on manual, time-consuming tasks and, in doing so, frees teams to focus on higher-value work that builds trust while strengthening their security and compliance posture. In addition to its core functions, Vanta AI Agent also generates clear and actionable policy change summaries, streamlining the process of updating compliance documentation during annual reviews. The result reduces the need for manual input, allowing teams to focus on strategic decision-making. Other features of the agent include the ability to proactively detect inconsistencies between policy-defined service level agreements and the outcomes of continuous testing. When mismatches occur, the agent flags them and suggests fixes, helping teams address issues before they escalate into audit risks. Vanta AI Agent further simplifies information retrieval by answering policy and compliance-related questions in real time. Teams can quickly access critical details such as password requirements, vendor risk management information and compliance with standards like Service Organization Control 2 and the Health Insurance Portability and Accountability Act.
Zencoder’s UI testing AI agent imitates how humans behave when interacting with web applications by combining images with snapshots and generating test artifacts to capture the expected visual and functional outcomes
Zencoder has announced a public beta for Zentester, its new end-to-end UI testing AI agent. Zentester imitates how humans behave when interacting with web applications, such as navigating the layout, and identifying and using interactive elements. It does this by combining images (screenshots) with DOM (snapshot) information. As it runs through test scenarios, it generates test artifacts that capture the actions performed and the expected visual and functional outcomes. According to the company, these tests are designed to be maintainable over time and less prone to having issues when an application changes. It also automatically follows end-to-end testing best practices, such as proper wait strategies, error handling, and test isolation.
Postman’s platform improves API discoverability by enabling any public API on its network of over 100,000 public APIs to be turned into an MCP server, with a verified domain, auth controls and good documentation
API discoverability has always been important, but it’s becoming increasingly more important as AI agents become more prevalent, says Abhinav Asthana, CEO and co-founder of Postman. Sterling Chin, senior developer advocate at Postman, said that the industry needs to get to a point where an API is so easy to digest that it’s just like building with LEGO. Postman launched a network for verified MCP servers. “We basically took all the remote MCP servers available, verified them, and put them on the public network because everybody’s gonna need a verified place soon.” Postman also released an update to its platform that enables any public API on its network of over 100,000 public APIs to be turned into an MCP server, making it more important than ever that API developers ensure their APIs are discoverable by the people that will want to use them. Chin said that what is typically seen of APIs is only the tip of the iceberg. “We only see the top maybe 10 percent. Those are the external APIs that get all the hype. The majority of services are internal to us, and those are the ones that when MCP starts to really take off, those are the APIs that are going to blow everyone away.” Allen Helton, ecosystem engineer at Momento, maker of reliability solutions and a customer of Postman, told that the most important benefit they get out of Postman is that it allows their APIs to be easily discovered by developers. Another recommendation is to make sure your public profile is filled out. The public profile includes everything an API publisher owns, including workspaces, collections, and API specs. He advises everyone to have a profile picture and links to their social media and website on that page. Getting verified by Postman will also help, as verified publishers get a badge that essentially proves that you’re the domain owner, increasing confidence among API consumers. Postman’s requirements for getting verified include things like having a verified domain, setting up authentication for public APIs, and having good documentation.
Open talent platform Torc uses LinkedIn data for parsing out developer skills, integrates with GitHub to assess previous technical projects and scores the candidate on Java assessment to determine the level of skill and fitness for placement
In a report, done jointly by Randstad, Staffing Industry Analysts (SIA) and Open Assembly, 62% of respondents said they currently are or are planning to use a talent platform. Morris said he expects that number to grow because developers skilled in certain modern technology areas are hard to find. With AI doing the initial search for talent, then collecting and analyzing resumes, recruiters are spending less time finding talent than they are now nurturing it, according to Mike Morris, the founder of talent communities Topcoder and Torc. The recruiter/advisor can guide developers on how to upskill in certain areas, how to take assessment tests that increase their value and prove their ability, and even how to turn project engagements into full-time positions. First, he said, Torc takes in data from LinkedIn, parsing out skills and tangential skills for categorization by AI. Next, to assess technical talent, the platform integrates with GitHub to pull in all of their work from the previous 12 months. “We pull in all the ranks from GitHub, GitLab and Hacker and pull in their stats,” Morris said. “So now they said they were good at, say, Java, and look, in the last 12 months, they’ve done 64 pull requests and they were all in the Java programming language, and they did this many code pushes.
Blockchains could guide AI towards user ownership and open standards through use of self-custodial wallets for storing agent passports and chain-based ID layer for verifiable records of payments
Andreessen Horowitz’s a16z crypto arm suggests that blockchains could guide artificial intelligence towards user ownership and open standards. The report suggests that core context and agent passports should be stored in self-custodial wallets, allowing instant access to preferences without repeated training. A chain-based identity layer would allow agents to carry verifiable records of owners, capabilities, and payment details across platforms. Proof-of-personhood systems could help screen bots as generative models proliferate. The report also promotes decentralized physical infrastructure networks, on-chain synchrony layers, micropayments, and immutable ledgers for managing intellectual property. It also suggests smart contract licensing and wallet-based zero-knowledge proofs for advertising. The report concludes that intertwining blockchains and machine learning could preserve an open internet by embedding incentives, provenance, and governance directly at the protocol layer.
‘Fintech 3.0’ to be shaped by adaptive and inclusive financial tools that would address the needs and challenges of growing federal debt, income inequality, poverty and rapid job loss due to AI
Founder of early-stage venture firm Inspired Capi, Alexa von Tobel says that while Inspired is a generalist firm, she said she feels both “urgent and optimistic” about fintech. “We think of this wave as fintech 3.0,” von Tobel said. “The next wave of innovation won’t come from superficial tweaks but from fundamental deep product reinvention — tools that meet the needs of a changing economy and a more diverse, digitally native population. The growing federal debt, rising income inequality, and increasing poverty — especially among older Americans — underscore the need for more adaptive and inclusive financial tools. Not to mention the rapid job loss due to AI. This moment presents a major opportunity for startups to reimagine financial products from the ground up. We think of this wave as fintech 3.0. The next wave of innovation won’t come from superficial tweaks but from fundamental deep product reinvention — tools that meet the needs of a changing economy and a more diverse, digitally native population.
Deepgram’s Voice Agent API combines speech-to-text, text-to-speech, and LLM orchestration with contextualized conversational logic into a unified architecture to enable deploying real-time, intelligent voice agents at scale
Deepgram has announced the general availability of its Voice Agent API, a single, unified voice-to-voice interface that gives developers full control to build context-aware voice agents that power natural, responsive conversations. Combining speech-to-text, text-to-speech, and LLM orchestration with contextualized conversational logic into a unified architecture, the Voice Agent API gives developers the choice of using Deepgram’s fully integrated stack or bringing their own LLM and TTS models. It delivers the simplicity developers love and the controllability enterprises need to deploy real-time, intelligent voice agents at scale. Deepgram’s Voice Agent API provides a unified API that simplifies development without sacrificing control. Developers can build faster with less complexity, while enterprises retain full control over orchestration, deployment, and model behavior, without compromising on performance or reliability. Deepgram’s Voice Agent API also provides a single, unified API that integrates speech-to-text, LLM reasoning, and text-to-speech with built-in support for real-time conversational dynamics. Capabilities such as barge-in handling and turn-taking prediction are model-driven and managed natively within the platform. This eliminates the need to stitch together multiple vendors or maintain custom orchestration, enabling faster prototyping, reduced complexity, and more time focused on building high-quality experiences. The platform enables model-level optimization at every layer of the interaction loop. This allows for precise tuning of latency, barge-in handling, turn-taking, and domain-specific behavior in ways not possible with disconnected components.
Startup Yupp’s platform crowdsources responses to evaluate AI models by allowing users to build consensus with multiple models and rewards them with crypto tokens for providing feedback
Yupp, officially known as Ber Sarai Labs Inc., launched with $33 million seed funding led by a16z crypto, the cryptocurrency-focused arm of Andreessen Horowitz, to build an AI model evaluation platform with crypto incentives. The core idea behind the platform is simple: Instead of having a single AI respond to a prompt, users will get two responses — or more. This can be good if they want to see more than one opinion or avoid bad answers. It can also allow users to build a consensus with multiple AI models. The company says that it has more than 500 models under the hood. This includes access to OpenAI’s ChatGPT, Anthropic PBC’s Claude, Google LLC’s Gemini and DeepSeek. It also features a wide range of open-source models, including Meta Platform Inc.’s Llama, as well as various text and image models from lesser-known research labs and small companies. As users browse answers from different AI models, feedback will allow users to share which one they liked and why. This feedback will help tailor future responses on Yupp to their needs. To provide an incentive for users to stay on the platform, the company will offer users a type of token called Yupp credits. These credits go toward using the AI models. Users are rewarded these credits for providing feedback: The higher the quality of the feedback, the more credits. The token can be exchanged for other cryptocurrency payouts. Yupp’s technology crowdsources assessment and uses the rewards to bring in users, but it also uses blockchain technology to provide transparency and an underlying immutable record of the evaluations that cannot be tampered with.
Applicant trust platform Snappt offers automated, reliable verification of an applicant’s rent payment history delivering 25x more coverage than credit bureaus and over 80% verification success
Snappt, a leading platform for applicant trust in multifamily housing, has announced the addition of Verification of Rent (VOR) powered by Trigo. The platform also includes enhanced Verification of Assets (VOA) and bank account linking, supported by a new partnership with Mastercard’s open banking platform, Finicity. VOR enables property managers to automatically and accurately verify applicant rental payment history, eliminating the need for manual outreach to landlords. With less than 5% of rental history available through traditional credit reporting, VOR delivers 25x more coverage than credit bureaus and achieves over 80% verification success. Key features of Snappt’s Applicant Trust Platform: Verification of Rent (VOR): Automated, reliable verification of an applicant’s rent payment history. Bank Account Linking: Reduce friction for applicants by offering the option of instant verification and speed up application processing. Verification of Assets (VOA): Approve creditworthy applicants with significant assets who may not meet traditional income requirements, directly improving occupancy rates and NOI. Industry-Leading Fraud Detection: Snappt’s proven AI-driven detection technology and fraud forensics team have analyzed over 13 million documents, ensuring accurate results. Connected Payroll: Direct integration with 90% of US payroll providers instantly verifies income and employment status in real-time. ID Verification: Best-in-class biometric technology, complete with 30+ checks on an ID and the ability to scan 4,600+ global ID types.
Autobook integrates Fundbox’s embedded capital infrastructure tech into its platform to enable small business owners to apply for and access funds without ever leaving their banking app
Autobook has launched Autobooks Capital, powered by Fundbox, the embedded capital infrastructure for small businesses. This new offering adds fast, flexible funding directly within the Autobooks platform—no redirects, no extra accounts—just seamless access to capital where businesses already manage their finances. By layering in embedded capital infrastructure from Fundbox, financial institutions can offer small businesses a seamless way to access working capital, right when and where it’s needed. Because Autobooks Capital is embedded directly within digital banking, small business owners can apply for and access funds without ever leaving their banking app. This direct-to-account experience simplifies cash flow management and reinforces the financial institution’s position as the primary operating hub for small businesses. Fully integrated into the Autobooks platform, Autobooks Capital offers fast underwriting, competitive rates, and flexible repayment options—allowing businesses to apply for and receive funding without ever leaving the platform. Whether it’s restocking inventory, expanding operations, or navigating cash flow challenges, capital is now just a few clicks away. Autobooks Capital compliments traditional lending programs by giving business owners convenient access to short-term working capital for everyday needs. This enables financial institutions to better retain primacy of the customer relationship and compete more effectively with online lending providers — delivering modern capital access without pushing business customers to third-party platforms.