PlainID, global provider of Identity Security, introduces Policy Management for Agentic AI. Policy Management for Agentic AI enables organizations to define granular policies that control what data AI agents can access, how they process it, and which actions they may take—ensuring that every AI-driven workflow abides by corporate and regulatory mandates. Key capabilities include: Identity-aware control – Enforce access based on human and non-human identity (NHI). Dynamic, fine-grained policies – Apply adaptable controls to every AI Agent interaction with data, APIs and services. Centralized policy management – Manage and govern all policies in one unified, standardized interface. Seamless integration – With popular AI platforms and orchestration frameworks Zero Trust Alignment – Ensure AI operations align with enterprise security and compliance frameworks, by design. Auditability – Gain full visibility into AI decision chains, access attempts, and policy outcomes. “As enterprises accelerate AI initiatives, PlainID empowers teams to govern AI data and decisions without compromising innovation. Through policy management and access enforcement, we ensure every AI interaction is secure, compliant, and policy-aware,” said Gal Helemski, Chief Product Officer and Co-Founder of PlainID.
Regula Rolls privacy compliance tool allows document experts to blur or hide PII directly within forensic workflows
Regula, a global identity verification solution developer, has added personal data masking functionality to its Regula Forensic Studio (RFS) software. This feature allows document experts to protect personal data with a single click, meeting growing privacy demands without disrupting workflows. The Regula ecosystem, from real-time ID verification to in-depth forensic analysis, now supports robust privacy controls natively. The new capability allows document experts to blur or hide personally identifiable information (PII) directly within forensic workflows, ensuring sensitive data is handled responsibly while meeting global requirements. In addition to the personal data masking feature, the latest RFS release includes 40+ updates focused on speed, customization, and forensic precision: New analysis tools: Yellow dot analysis for tracing document origins and detecting unauthorized duplicates. Smarter imaging: Per-light-source gamma correction and full-spectrum HDR imaging (not just UV), improving clarity across all materials. Streamlined collaboration: Video screen capture and camera recording capabilities support team training and case reviews. Faster insights: Hyperspectral imaging is now 20% faster without compromising detail. Improved digital zoom: Expanded up to 16x for detailed inspections. Visual reporting: Ability to generate composite images under varied lighting, ideal for expert reports or courtroom presentations. Integrated workflows: Automated document searches in the Information Reference System (IRS) after MRZ reading to reduce manual steps. Flexible video modes: Three options for different examination tasks—real-time viewing without frame skipping, high-resolution capture, and an expanded A4 field-of-view mode. Wider OS compatibility: Now supports Rocky and Debian Linux distributions, expanding deployment options.
Monte Carlo’s low-code observability solution lets users apply custom prompts and AI-powered checks to unstructured fields, to monitor for the quality metrics that are relevant to their unique use case
Monte Carlo has launched unstructured data monitoring, a new capability that enables organizations to ensure trust in their unstructured data assets across documents, chat logs, images, and more, all without needing to write a single line of SQL. With its latest release, Monte Carlo becomes the first data + AI observability platform to provide AI-powered support for monitoring both structured and unstructured data types. Monte Carlo users can now apply customizable, AI-powered checks to unstructured fields, allowing users to monitor for the quality metrics that are relevant to their unique use case. Monte Carlo goes beyond the standard quality metrics and allows customers to use custom prompts and classifications so as to make monitoring truly meaningful. Monte Carlo continues its strategic partnership with Snowflake, the AI Data Cloud company, to support Snowflake Cortex Agents, Snowflake’s AI-powered agents that orchestrate across structured and unstructured data to provide more reliable AI-driven decisions. In addition, Monte Carlo is extending its partnership with Databricks to include observability for Databricks AI/BI – a compound AI system built into Databricks’ platform that generates rich insights from across the data + AI lifecycle – including ETL pipelines, lineage, and other queries. By supporting Snowflake Cortex Agents and Databricks AI/BI, Monte Carlo helps data teams ensure their foundational data is reliable and trustworthy enough to support real-time business insights driven by AI.
Fenergo’s agentic AI for compliance allows users to interact with all operational, policy and entity data through natural language and harness real-time insights on process efficiency, operations and risk
Fenergo, a Dublin-based provider of client lifecycle management and compliance solutions, has launched its FinCrime Operating System. The system uses “agentic AI” to help firms cope with rising operational costs and compliance demands. The FinCrime OS unifies client lifecycle events, including onboarding, KYC, screening, ID&V, and transaction monitoring, on a single platform. The system can automate tasks and save up to 93% of operational costs. Fenergo’s initial six AI agents can streamline periodic KYC reviews, cutting review timeframes by up to 45%. The Six AI agents available today include: Data sourcing agent: Sources data from one or more third-party data provider, compares against entity data and auto-completes tasks; Screening agent: Runs screening checks against third-party integrations, auto-resolves hits and returns results to providers; Document agent: Extracts, classifies and links documents using AI to automate document-management processes; Significance agent: Performs a check against data changes to determine significance to define next action; Autocompletion agent: Automates the completion of tasks based on pre-defined rules, policy and configured guardrails; and Insights agent: Fenergo’s co-pilot allows users to interact with all operational, policy and entity data through natural language and harness real-time insights on process efficiency, operations and risk.
Fenergo launches compliance operating system, eyes big cost savings
Fenergo, a Dublin-based provider of client lifecycle management and compliance solutions, has launched its FinCrime Operating System. The system uses “agentic AI” to help firms cope with rising operational costs and compliance demands. The FinCrime OS unifies client lifecycle events, including onboarding, KYC, screening, ID&V, and transaction monitoring, on a single platform. The system can automate tasks and save up to 93% of operational costs. Fenergo’s initial six AI agents can streamline periodic KYC reviews, cutting review timeframes by up to 45%. The Six AI agents available today include: Data sourcing agent: Sources data from one or more third-party data provider, compares against entity data and auto-completes tasks; Screening agent: Runs screening checks against third-party integrations, auto-resolves hits and returns results to providers; Document agent: Extracts, classifies and links documents using AI to automate document-management processes; Significance agent: Performs a check against data changes to determine significance to define next action; Autocompletion agent: Automates the completion of tasks based on pre-defined rules, policy and configured guardrails; and Insights agent: Fenergo’s co-pilot allows users to interact with all operational, policy and entity data through natural language and harness real-time insights on process efficiency, operations and risk.
Agentic AI’s role in taking down DanaBot malware-as-a-service through orchestrating predictive threat modeling cuts months of forensic analysis to weeks validates its value for SOC teams
U.S. Department of Justice unsealed a federal indictment in Los Angeles against 16 defendants of DanaBot, a Russia-based malware-as-a-service (MaaS) operation responsible for orchestrating massive fraud schemes, enabling ransomware attacks and inflicting tens of millions of dollars in financial losses to victims. Agentic AI played a central role in dismantling DanaBot, orchestrating predictive threat modeling, real-time telemetry correlation, infrastructure analysis and autonomous anomaly detection. These capabilities reflect years of sustained R&D and engineering investment by leading cybersecurity providers, who have steadily evolved from static rule-based approaches to fully autonomous defense systems. Taking down DanaBot validated agentic AI’s value for Security Operations Centers (SOC) teams by reducing months of manual forensic analysis into a few weeks. All that extra time gave law enforcement the time they needed to identify and dismantle DanaBot’s sprawling digital footprint quickly. DanaBot’s takedown signals a significant shift in the use of agentic AI in SOCs. SOC Analysts are finally getting the tools they need to detect, analyze, and respond to threats autonomously and at scale, attaining the greater balance of power in the war against adversarial AI. Agentic AI directly addresses a long-standing challenge, starting with alert fatigue. Microsoft research reinforces this advantage, integrating gen AI into SOC workflows and reducing incident resolution time by nearly one-third. DanaBot’s dismantling signals a broader shift underway: SOCs are moving from reactive alert-chasing to intelligence-driven execution. At the center of that shift is agentic AI. SOC leaders getting this right aren’t buying into the hype. They’re taking deliberate, architecture-first approaches that are anchored in metrics and, in many cases, risk and business outcomes.
Mastercard launches Small Business Navigator a new curated offering of digital education, insights, protection, and planning tools to help entrepreneurs
By uniting data, digital tools and offers across three core areas, Small Business Navigator is built to help small businesses work smarter, stay safer, and grow stronger.
Knowledge and insights: Business owners get information they need to make smarter decisions, including:
An AI-powered chatbot that acts as a mentor by answering questions and guiding small businesses through their most pressing business challenges
Access to actionable insights and data from The Mastercard Economics Institute and Mastercard SpendingPulse™ reports with state-level consumer spending trends
Educational content from Mastercard and partners such as Square, covering cybersecurity, marketing, and digital tools like tap-on-phone payments
Security and protection: Small businesses can stay ahead of threats with simple, practical, powerful cybersecurity tools:
Access to My Cyber Risk powered by RiskRecon, providing prioritized guidance to help small businesses strengthen their defenses3
A personalized report with recommendations tailored to each business based on their individual Cybersecurity Assessment Quiz results
PlainID’s Policy Management for Agentic AI allows organizations to define dynamic, fine-grained policies that apply adaptable controls to every AI Agent interaction with data, APIs and services
PlainID, global provider of Identity Security, introduces Policy Management for Agentic AI. Policy Management for Agentic AI enables organizations to define granular policies that control what data AI agents can access, how they process it, and which actions they may take—ensuring that every AI-driven workflow abides by corporate and regulatory mandates. Key capabilities include: Identity-aware control – Enforce access based on human and non-human identity (NHI). Dynamic, fine-grained policies – Apply adaptable controls to every AI Agent interaction with data, APIs and services. Centralized policy management – Manage and govern all policies in one unified, standardized interface. Seamless integration – With popular AI platforms and orchestration frameworks Zero Trust Alignment – Ensure AI operations align with enterprise security and compliance frameworks, by design. Auditability – Gain full visibility into AI decision chains, access attempts, and policy outcomes. “As enterprises accelerate AI initiatives, PlainID empowers teams to govern AI data and decisions without compromising innovation. Through policy management and access enforcement, we ensure every AI interaction is secure, compliant, and policy-aware,” said Gal Helemski, Chief Product Officer and Co-Founder of PlainID.
Discord’s new virtual reward system allows users to redeem exclusive digital items from Discord’s Shop using the rewards earned by watching product videos or playing games
Discord is experimenting with a new virtual reward system aimed at encouraging more users to engage with its interactive ads. This new feature, called “Orbs,” comes on the heels of the company preparing for a potential IPO. Users can earn Orbs by completing “Quests,” Discord’s ad format where advertisers incentivize users to watch product videos or play games by rewarding them with virtual items. The addition of Orbs gives users the chance to redeem exclusive digital items from Discord’s Shop, including Nitro credits, profile badges, avatar decorations, profile effects, and items from main collections. The goal of Orbs is to encourage more interaction with Quests as Discord seeks to demonstrate to partners that it can offer a scalable ad business. The Orbs experiment may also entice users who don’t have a subscription to try Nitro, as they can spend Orbs on credits instead of using a payment method. For instance, users need 1,400 Orbs to get three free days of Nitro, which typically costs $10 per month.
Akool’s Live Camera uses AI that simulates human presence dynamically, analyzing live audio/visual inputs to generate responsive avatars, translate video calls and swap faces in real-time
Akool Live Camera uses AI to capture human movement and mimic that movement with a generated virtual avatar in real time. Akool can also translate speech in real time during a virtual meeting and also provide instant face swapping during a call. The AI technology listens to conversations in one language and instantly translates them into the selected target language, providing real-time, synchronized audio that matches the avatar’s lip movements and facial expressions. The company also offers lip-syncing for avatars in real time, where the avatar lip movements can match the words being spoken by a person in real time. This Akool Live Camera tool is a part of the Akool Live Suite, a first-of-its-kind collection of products that features live, real-time video generation with minimal delay. The suite includes live avatars, live face swap, video translation, and real-time video generation. Akool Live Camera sets a new standard in AI-powered video generation technology, going well beyond scripted, text-based prompts. This opens up a new array of possibilities for virtual meetings and live streams, especially when connecting with international audiences. Akool Live Camera is an interactive engine that simulates human presence dynamically, analyzing live audio/visual inputs to generate responsive avatars with expressions and contextual awareness. The combination of Akool’s AI and intuitive design empowers creators, educators and enterprises to connect more authentically and efficiently than ever. Key capabilities of Akool Live Camera include: Unmatched live interaction, Real-time multilingual translation, Dynamic expression and gesture mapping, Cross-platform versatility, Privacy-forward design,` and Market- and audience-specific customization.