The Federal Trade Commission issued a proposed order requiring Workado, LLC to stop advertising the accuracy of its AI detection products unless it maintains competent and reliable evidence showing those products are as accurate as claimed. The settlement will be subject to public comment before becoming final. The order settles allegations that Workado promoted its AI Content Detector as “98 percent” accurate in detecting whether text was written by AI or human. But independent testing showed the accuracy rate on general-purpose content was just 53 percent, according to the FTC’s administrative complaint. The FTC alleges that Workado violated the FTC Act because the “98 percent” claim was false, misleading, or non-substantiated. The proposed order settling the complaint is designed to ensure Workado does not engage in similar false, misleading, or unsupported advertising in the future. Under the proposed order, Workado: 1) Is prohibited from making any representations about the effectiveness of any covered product unless it is not misleading, and the company has competent and reliable evidence to support the claim at the time it is made; 2) Is required to retain any evidence it uses to support such efficacy claims; 3) Must email eligible consumers about the consent order and settlement with the Commission; and 4) Must submit compliance reports to the FTC one year after the order is issued and every year for the following three years.
Microsoft’s most capable new Phi 4 AI model rivals the performance of far larger systems, yet small enough for low-latency environments
Microsoft launched several new “open” AI models, the most capable of which is competitive with OpenAI’s o3-mini on at least one benchmark. All of the new pemissively licensed models — Phi 4 mini reasoning, Phi 4 reasoning, and Phi 4 reasoning plus — are “reasoning” models, meaning they’re able to spend more time fact-checking solutions to complex problems. Phi 4 mini reasoning was trained on roughly 1 million synthetic math problems generated by Chinese AI startup DeepSeek’s R1 reasoning model. Around 3.8 billion parameters in size, Phi 4 mini reasoning is designed for educational applications, like “embedded tutoring” on lightweight devices. Parameters roughly correspond to a model’s problem-solving skills, and models with more parameters generally perform better than those with fewer parameters. Phi 4 reasoning, a 14-billion-parameter model, was trained using “high-quality” web data as well as “curated demonstrations” from OpenAI’s o3-mini. It’s best for math, science, and coding applications. As for Phi 4 reasoning plus, it’s Microsoft’s previously released Phi-4 model adapted into a reasoning model to achieve better accuracy on particular tasks. Phi 4 reasoning plus approaches the performance levels of R1, a model with significantly more parameters (671 billion). The company’s internal benchmarking also has Phi 4 reasoning plus matching o3-mini on OmniMath, a math skills test. “Using distillation, reinforcement learning, and high-quality data, these [new] models balance size and performance,” wrote Microsoft in a blog post. “They are small enough for low-latency environments yet maintain strong reasoning capabilities that rival much bigger models. This blend allows even resource-limited devices to perform complex reasoning tasks efficiently.”
UiPath launches the first enterprise-grade platform for agentic automation – controlled agency model ensures AI agents operate within clearly defined guardrails
UiPath launched its next-generation UiPath Platform™ for agentic automation, a groundbreaking platform designed to unify AI agents, robots, and people on a single intelligent system. The UiPath Platform for agentic automation is enabling everyone to begin building, deploying, and managing agents. Key Capabilities of the UiPath Platform for Agentic Automation: 1) UiPath Maestro™— It automates, models, and optimizes complex business processes end to end with built-in process intelligence and KPI monitoring to enable continuous optimization. 2) Through a controlled agency model, UiPath ensures AI agents operate within clearly defined guardrails—ensuring security, predictability, and performance. The platform features robust governance, real-time vulnerability assessments, and stringent data access controls to protect enterprise environments. “We are targeting 95%+ agent accuracy with every launch,” commented Raghu Malpani, Chief Technology Officer at UiPath. 3) Developers can rapidly prototype agents in UiPath Agent Builder within UiPath Studio, while having the opportunity to customize when needed. This means both technically oriented business professionals and experienced programmers can easily create sophisticated, scalable automations that can adapt to complex business requirements and evolving enterprise needs. 4) UiPath integrates with third-party agent frameworks including LangChain, Anthropic, and Microsoft. We partnered with Google Cloud on its new, open protocol called Agent2Agent (A2A), which will allow AI agents to communicate with each other, securely exchange information, and coordinate actions on top of various enterprise platforms or applications. This open approach breaks down silos and future-proofs enterprise automation strategies. 5) The new UiPath IXP (Intelligent Xtraction & Processing) solution introduces multi-modal, AI-based classification and extraction for unstructured data. Built for high-complexity use cases like claims adjudication, loan origination, and electronic batch records, IXP brings enterprise-grade scale to document processing. 6) UiPath has also introduced UI Agent for computer use, now in private preview—a natural language-driven agent that understands user intent, plans multi-step tasks, and executes actions across interfaces autonomously.
Snaplogic’s tool includes no-code visual prompt editor that enables any user to build, visualize, and refine intelligent agents for complex workflows in real time on a single screen
Snaplogic announced AgentCreator 3.0, a groundbreaking evolution in agentic AI technology that eliminates the complexity of enterprise AI adoption. The new release empowers organizations to build and scale their own AI solutions with no coding required. With AgentCreator 3.0, businesses are no longer constrained by human resource limitations. Instead, they gain access to a limitless workforce powered by AI-driven digital labor that works tirelessly, scales infinitely, and augments their best talent with PhD-level intelligence. Key additions to AgentCreator 3.0 include Prompt Composer and Agent Visualizer, making it easier than ever for customers to build, visualize, and refine intelligent agents for complex workflows. Prompt Composer is a visual prompt editor that simplifies prompt creation for faster iteration and stronger results, enabling anyone, from business users to engineers, to create, test, and refine AI instructions in real time on a single screen. This ensures high precision and adaptability as LLMs evolve. Agent Visualizer provides full transparency into AI decision-making, ensuring enterprises can trust, audit, and refine agent behavior. The visualization tool delivers a step-by-step breakdown of an agent’s decision-making process. SnapLogic is also introducing support for the Model Context Protocol (MCP) to further accelerate the adoption and deployment of Agentic AI. AgentCreator 3.0 empowers organizations with: AI-ready data, AI as digital labor, DIY AI without complexity, Security and governance, AI workforce collaboration.