The Pure AI Blog Short Dispatches from AI's Front Lines
The Pure AI Blog is researched, fact-checked, edited and updated by the editors of PureAI.com, with writing assistance from AI. To submit your company's press release for consideration, contact [email protected].
Cribl, a data engine for IT and security, has introduced agentic artificial intelligence capabilities for Cribl Search, designed to help IT and security teams analyze operational data more efficiently. The new features allow AI-driven agents to assist users with searching, analyzing and interpreting machine data collected from across enterprise systems. The enhancements are intended to help teams investigate operational issues and security events more quickly by automating portions of the data analysis process. Cribl Search unifies human-generated context with log ingestion, storage and analysis across data stores.
Cribl Search is used by organizations to explore large volumes of telemetry and log data from infrastructure, applications and security tools. Agentic telemetry delivers AI-speed performance, structures data at ingestion, remains schema-agnostic and uses agentic AI to fuse machine data with human context. By adding agentic AI capabilities, Cribl aims to simplify how teams interact with complex datasets and reduce the time required to identify potential problems. Enterprises are increasingly exploring AI agents that can help automate operational and security tasks.
Posted by Pure AI Editors on 03/11/20260 comments
CData Software, the data layer between AI and ROI, has expanded its Connect AI platform with new tools designed to help organizations develop and deploy AI agents in production environments. The update introduces agent development capabilities intended to help developers connect artificial intelligence models to enterprise data sources. The platform also adds security and governance features aimed at controlling how AI applications access corporate data across databases, SaaS applications and cloud systems. Expanding its managed MCP, new capabilities cover connectivity, context and control, moving AI from experimentation phases to production.
The enhancements are designed to address challenges enterprises face when integrating AI systems with operational data while maintaining compliance and security requirements. The platform focuses on enabling secure data connectivity while supporting the development of AI-powered workflows and automation. Enterprises are increasingly exploring AI agents to automate tasks such as data analysis, reporting and business process execution.
Posted by Pure AI Editors on 03/10/20260 comments
Smartria, a leading cloud-based compliance software platform, has launched two artificial intelligence–driven tools designed to help financial advisory firms automate compliance monitoring and documentation reviews. The new capabilities, called SmartReview and SmartAssist, are intended to help compliance teams analyze communications, documents and regulatory records more efficiently. The tools use AI to identify potential compliance issues and generate summaries or recommendations that help firms evaluate whether activity meets regulatory requirements. Both are powered by hyper-trained LLMs built to respect privacy and confidentiality of customer data.
Smartria demonstrated the new features at the Future Proof Citywide conference, where technology providers and financial firms discussed the growing role of automation in regulatory compliance. Compliance technology vendors are increasingly incorporating AI to reduce manual review workloads. As firms handle larger volumes of digital communications and records, automated analysis tools are becoming a key part of compliance operations.
Posted by Pure AI Editors on 03/10/20260 comments
Teradata, an automation specialist for enterprises, announced new capabilities designed to enable AI agents to autonomously process multiple types of enterprise data, including text, images and audio. The update allows organizations to build and run AI agents that can analyze and act on multimodal data within Teradata’s analytics and data platform. These agents can automate tasks such as extracting insights from documents, analyzing media content and supporting decision-making workflows across enterprise systems. Enterprises can make use of the integrated approach with its diverse data processing capabilities, autonomous workflows, context-aware intelligence, accelerated development and deployment and the reduction of data silos.
The goal is to help organizations operationalize AI agents within large-scale data environments without requiring teams to move data across multiple platforms. The capability is intended to integrate with existing analytics, data governance and machine learning workflows already running on the platform. Enterprises are increasingly experimenting with AI agents that can carry out multi-step tasks using corporate data. The new agentic capabilities will be generally available to all Teradata customers from April 2026.
Posted by Pure AI Editors on 03/10/20260 comments
Privacera, rebranded to Trust3 AI, provides a unified data and AI access governance platform designed to help organizations govern data access, security and compliance across artificial intelligence and analytics environments. Trust3 AI builds on Privacera’s existing data governance capabilities while adding tools intended to help enterprises manage policies for AI applications and large data platforms. The platform focuses on controlling access to sensitive data, enforcing compliance rules and monitoring how information is used across cloud and AI workloads. Trust3 AI aims to bridge the gap between data policies and AI tools, offering a comprehensive, compliant solution.
Organizations are increasingly concerned about governance as generative AI systems rely on large datasets that may contain regulated or sensitive information. Enterprises adopting AI technologies must ensure data access policies remain consistent across data lakes, machine learning pipelines and analytics tools. As companies deploy more AI-driven applications, managing data usage and compliance policies has become a key requirement for enterprise IT and security teams.
Posted by Pure AI Editors on 03/09/20260 comments
BigTXN, a leader in financial data solutions, has introduced sanctions.com, a platform using agentic AI to produce real-time, newsroom-quality coverage of global sanctions. The platform uses AI to analyze large volumes of transaction data and identify potential sanctions violations more efficiently than traditional rule-based systems. According to BigTXN, the technology can generate detailed reports and investigative summaries intended to help compliance professionals review alerts and determine whether transactions require escalation. It is able to interpret content while maintaining transparency, paired with audit trail to help reduce workloads while keeping within compliance strategies.
Sanctions compliance has become increasingly complex as governments expand financial restrictions related to geopolitical conflicts and anti–money laundering efforts. Banks and fintech companies must screen large numbers of transactions against frequently updated sanctions lists while maintaining detailed audit records for regulators. Automated analysis can help reduce false positives and allow compliance teams to focus on higher-risk cases rather than manually reviewing large volumes of alerts.
Posted by Pure AI Editors on 03/09/20260 comments
Nutanix, a hybrid multicloud computing leader, has released findings from its latest Enterprise Cloud Index, reporting that artificial intelligence initiatives are driving rapid adoption of containers and Kubernetes across enterprise IT environments. The survey indicates that organizations are increasingly modernizing infrastructure to support AI-powered applications, with containerized workloads becoming a core part of that strategy. Key findings of the report include new AI risks formed as a result of organizational silos, Shadow IT creates AI challenges. Agents can unlock potential for organizations, data sovereignty is non-negotiable and infrastructure to deploy AI is not necessarily able to support the directives.
According to the report, enterprises are prioritizing hybrid and multicloud architectures to handle the compute and data demands of AI. Kubernetes adoption continues to expand as organizations seek portability, scalability and operational consistency across environments. The findings suggest that while AI investment is accelerating, many organizations are still navigating operational complexity, security considerations and skills gaps tied to containerized infrastructure. For IT leaders, the report underscores the growing intersection between AI strategy and cloud-native modernization efforts, with containers playing a central role in enterprise transformation roadmaps.
Posted by Pure AI Editors on 03/03/20260 comments
Deloitte, a leading audit, tax and advisory firm, has unveiled a suite of physical AI solutions developed with NVIDIA Omniverse libraries, targeting industrial organizations seeking to modernize operations through simulation and intelligent automation. The offerings are designed to help manufacturers, energy providers and other asset-intensive enterprises build and manage digital twins, optimize workflows and improve operational decision-making. Key capabilities include helping clients visualize operations with immersive solutions, scale deployment of physical AI and interpreting the physical world digitally to help reduce operational downtime and support faster decision cycles.
Physical AI refers to the application of AI models to real-world systems, combining data from sensors, robotics and industrial equipment with advanced simulation environments. NVIDIA Omniverse provides a platform for creating physically accurate digital environments that can model facilities, supply chains and production processes. By integrating consulting expertise with NVIDIA’s simulation and AI technologies, Deloitte is positioning its new solutions as part of broader industrial transformation initiatives.
Posted by Pure AI Editors on 03/02/20260 comments
Simplilearn, a leader in digital upskilling, in collaboration with Microsoft has launched the Applied Agentic AI: Systems, Design & Impact Program, a new educational offering designed to help technology professionals develop expertise in building AI-driven systems on Microsoft platforms. The program targets product managers, architects and engineering leaders seeking to design and deploy agentic AI solutions in enterprise environments.
The curriculum focuses on applied systems design, governance, and real-world implementation strategies, with an emphasis on Microsoft AI technologies. As organizations move from experimental generative AI pilots to production-scale deployments, demand is growing for leaders who can translate AI capabilities into operational systems. By centering the program on agentic AI and Microsoft’s ecosystem, Simplilearn is positioning it to address enterprise needs for structured AI adoption. For IT and product leaders, the launch reflects a broader trend toward formalized training programs aimed at building practical, production-ready AI leadership skills rather than theoretical model development alone.
Posted on 03/02/20260 comments
TQA, an Austin-based AI and automation consultancy, unveiled a new agentic-focused identity and broadened technology partnerships with Microsoft and ServiceNow to help enterprise customers move beyond experimentation to practical AI adoption. TQA will integrate Microsoft Copilot, Azure AI and Power Platform into enterprise core systems, while its ServiceNow practice will focus on Workflow Data Fabric and AI agents to modernize legacy processes. The company continues to build on its strong UiPath partnership, holding Diamond and Fast Track partner accreditations.
The expanded partnerships reflect broader industry momentum toward interoperable enterprise AI. ServiceNow and Microsoft have been enhancing platform integration and governance capabilities to support enterprise-wide AI agents. TQA’s repositioning underscores a trend among consultancies to combine platform-agnostic frameworks with specialist expertise to help clients scale AI more reliably.
Posted by Pure AI Editors on 02/23/20260 comments