News from the AI & ML world
DeeperML - #agenticai
|
@cloud.google.com
//
References:
AI & Machine Learning
, google.github.io
Google Cloud is offering Financial Services Institutions (FSIs) a powerful solution to streamline and enhance their Know Your Customer (KYC) processes by leveraging the Agent Development Kit (ADK) in combination with Gemini models and Search Grounding. KYC processes are critical for regulatory compliance and risk mitigation, involving the verification of customer identities and the assessment of associated risks. Traditional KYC methods are often manual, time-consuming, and prone to errors, which can be challenging in today's environment where customers expect instant approvals. The Agent Development Kit (ADK) is a flexible and modular framework for developing and deploying AI agents. While optimized for Gemini and the Google ecosystem, ADK is model-agnostic, deployment-agnostic, and is built for compatibility with other frameworks. ADK was designed to make agent development feel more like software development, to make it easier for developers to create, deploy, and orchestrate agentic architectures that range from simple tasks to complex workflows.
The ADK simplifies the creation and orchestration of agents, handling agent definition, tool integration, state management, and inter-agent communication. These agents are powered by Gemini models hosted on Vertex AI, providing core reasoning, instruction-following, and language understanding capabilities. Gemini's multimodal analysis, including image processing from IDs and documents, and multilingual support further enhances the KYC process for diverse customer bases. By incorporating Search Grounding, the system connects Gemini responses to real-time information from Google Search, reducing hallucinations and increasing the reliability of the information provided. Furthermore, integration with BigQuery allows secure interaction with internal datasets, ensuring comprehensive data access while maintaining data security. The multi-agent architecture offers several key benefits for FSIs including improved efficiency through the automation of large portions of the KYC workflow, reducing manual effort and turnaround times. AI is leveraged for consistent document analysis and comprehensive external checks, leading to enhanced accuracy. The solution also strengthens compliance by improving auditability through clear reporting and source attribution via grounding. Google Cloud provides resources to get started, including $300 in free credit for new customers to build and test proof of concepts, along with free monthly usage of over 20 AI-related products and APIs. The combination of ADK, Gemini models, Search Grounding, and BigQuery integration represents a significant advancement in KYC processes, offering FSIs a robust and efficient solution to meet regulatory requirements and improve customer experience. Recommended read:
References :
@techstrong.ai
//
References:
siliconangle.com
, techstrong.ai
Agentic AI is rapidly reshaping enterprise data engineering by transforming passive infrastructure into intelligent systems capable of acting, adapting, and automating operations at scale. This new paradigm embeds intelligence, governance, and automation directly into modern data stacks, allowing for autonomous decision-making and real-time action across various industries. According to Dave Vellante, co-founder and chief analyst at theCUBE Research, the value is moving up the stack, emphasizing the shift towards open formats like Apache Iceberg, which allows for greater integration of proprietary functionalities into the open world.
The rise of agentic AI is also evident in the healthcare sector, where it's already being implemented in areas like triage, care coordination, and clinical decision-making. Unlike generative AI, which waits for instructions, agentic AI creates and follows its own instructions within set boundaries, acting as an autonomous decision-maker. This is enabling healthcare organizations to optimize workflows, manage complex tasks, and execute multi-step care protocols without constant human intervention, improving efficiency and patient care. Bold CIOs in healthcare are already leveraging agentic AI to gain a competitive advantage, demonstrating its practical application beyond mere experimentation. To further simplify the deployment of AI agents, Accenture has introduced its Distiller Framework, a platform designed to help developers build, deploy, and scale advanced AI agents rapidly. This framework encapsulates essential components across the entire agent lifecycle, including agent memory management, multi-agent collaboration, workflow management, model customization, and governance. Lyzr Agent Studio is another platform which helps to build end-to-end agentic workflows by automating complex tasks, integrating enterprise systems, and deploying production-ready AI agents. This addresses the current challenge of scaling AI initiatives beyond small-scale experiments and accelerates the adoption of agentic AI across various industries. Recommended read:
References :
@www.microsoft.com
//
References:
Data Phoenix
, www.marktechpost.com
,
Microsoft is making significant strides in the realm of agentic AI, particularly in telecommunications and code research. At TM Forum DTW Ignite 2025, Microsoft showcased how Open Digital Architecture (ODA) and agentic AI can drive measurable business outcomes for telecom companies. This involves transforming operations from reactive to proactive through autonomous decision support systems, addressing key industry priorities such as breaking down operational silos, unlocking data value, and increasing efficiency. Microsoft has been a key contributor to TM Forum initiatives for over two decades, aligning its Azure cloud-native foundations with ODA's composable blueprint, and helping operators assemble best-of-breed solutions without the constraints of proprietary systems.
Microsoft AI has introduced Code Researcher, an agent designed for deep research into large systems code and commit history. This addresses the challenges of debugging complex, large-scale systems code, like operating systems, which have evolved over decades and consist of thousands of interdependent files. Code Researcher helps in navigating intricate software environments, understanding architectural context, interdependencies, and historical evolution, and synthesizing fixes with minimal human intervention. With AI's growing role in software development, this agent aids in diagnosing and repairing issues, which often involve raw crash reports without clear natural language hints. Microsoft has also launched the Bing Video Creator, a free AI-powered tool utilizing OpenAI's Sora technology. This tool allows users to generate 5-second videos from text prompts, offering a novel way to express creativity and ideas. Initially available on mobile, with desktop support coming soon, the Bing Video Creator lets users describe what they want to see in a video and experiment with different styles. Microsoft has incorporated robust safety measures, including OpenAI's existing Sora safeguards and content moderation, to minimize misuse and ensure responsible video generation, marking a significant step in consumer generative AI. Recommended read:
References :
@www.microsoft.com
//
References:
syncedreview.com
, Source
Advancements in agentic AI are rapidly transforming various sectors, with organizations like Microsoft and Resemble AI leading the charge. Microsoft is demonstrating at TM Forum DTW Ignite 2025 how the synergy between Open Digital Architecture (ODA) and agentic AI is converting industry ambitions into measurable business outcomes within the telecommunications sector. They are focusing on breaking down operational silos, unlocking data's value, increasing efficiency, and accelerating innovation. Meanwhile, Resemble AI is advancing AI voice agents, anticipating the growing momentum of voice-first technologies, with over 74% of enterprises actively piloting or deploying these agents as part of their digital transformation strategies by 2025, according to an IDC report.
Researchers from Penn State University and Duke University have introduced "Multi-Agent Systems Automated Failure Attribution," a significant development in managing complex AI systems. This innovation addresses the challenge of identifying the root cause of failures in multi-agent systems, which can be difficult to diagnose due to the autonomous nature of agent collaboration and long information chains. The researchers have developed a benchmark dataset and several automated attribution methods to enhance the reliability of LLM Multi-Agent systems, transforming failure identification from a perplexing mystery into a quantifiable problem. Microsoft's contributions to TM Forum initiatives, including co-authoring Open APIs and donating hardened code, highlight the importance of standards-based foundations in AI development. By aligning Microsoft Azure's cloud-native foundations with ODA's composable blueprint, Microsoft is helping operators assemble solutions without proprietary silos, leading to faster interoperability, reduced integration costs, and quicker time-to-value for new digital services. This approach addresses fragmented observability by prescribing a common logging contract and integrating with Azure Monitor, reducing the time to detect anomalies and enabling teams to focus on proactive optimization. Recommended read:
References :
Ellie Ramirez-Camara@Data Phoenix
//
References:
Data Phoenix
Wordsmith AI, an Edinburgh-based legal technology startup, has secured $25 million in Series A funding led by Index Ventures. This investment values the company at over $100 million, marking it as one of Scotland's fastest-growing tech companies. The funding will be used to scale its AI agent platform and expand operations to London and New York, further developing its AI infrastructure capabilities.
Wordsmith AI is focused on transforming legal departments from operational bottlenecks into revenue accelerators. Their AI agent platform embeds legal intelligence directly into business workflows, streamlining processes like contract review, query answering, and decision-making. These AI agents integrate seamlessly into existing tools such as Slack, email, and Google Docs, enabling legal teams to scale their expertise without increasing headcount. CEO Ross McNairn emphasizes the company's vision of "legal engineering," where legal intelligence is embedded directly into business workflows through intelligent agents. Major clients like Deliveroo, Trustpilot, Remote.com, and Multiverse are already using the platform to reduce deal cycles and eliminate bottlenecks. Wordsmith AI is also pioneering the "legal engineer" role, combining legal expertise with technical skills to manage AI agent deployments, facilitating a future where legal teams engineer solutions rather than simply firefighting. Recommended read:
References :
@futurumgroup.com
//
References:
www.windowslatest.com
, futurumgroup.com
Microsoft is doubling down on its commitment to the developer community by embracing agentic AI, a move highlighted at the recent Microsoft Build conference. CEO Satya Nadella emphasized the shift from AI as merely an assistant to a proactive agent capable of performing complex tasks and workflows for software teams. This signifies a pivotal moment for Microsoft, placing AI at the forefront of software development and reshaping the industry's future. Microsoft leadership acknowledged the need to collaborate with the development community to navigate this new era and build the path toward agentic AI development together, recognizing that they don't have all the answers themselves.
Microsoft is actively integrating AI agents into its development tools, notably GitHub Copilot. The new coding agent in GitHub Copilot enables developers to assign issues to the agent, which then works asynchronously to create fully tested pull requests. This is more than just autocomplete; it's a new class of software engineering agent that works like a teammate, planning work, writing code, running tests, and soliciting feedback. By automating repetitive tasks and assisting with code maintenance, the coding agent aims to free up developers to focus on more critical and creative aspects of their work, increasing efficiency and productivity. Microsoft is also emphasizing the importance of cybersecurity in the age of AI. They are rolling out free cybersecurity support for European governments, offering AI-generated insights, early warnings about security flaws, and support against state-backed attacks. Microsoft is also encouraging users to upgrade to Windows 11 for enhanced security features, as Windows 10 support is ending in October 2025. Microsoft is also showcasing its AI-first security platform at the Gartner Security & Risk Management Summit, aiming to help organizations manage risk and protect assets effectively in the face of evolving threats. Recommended read:
References :
@www.insightpartners.com
//
References:
futurumgroup.com
, www.insightpartners.com
,
Flank, a Berlin-based company, has secured $10 million in funding to advance its autonomous AI legal agent designed for enterprise teams. The funding round was led by Insight Partners, with participation from Gradient Ventures, 10x Founders, and HV Capital. The investment will be used to accelerate product development, expand the engineering and commercial teams, and strengthen enterprise partnerships. Flank's AI agent seamlessly integrates into existing workflows, reviewing, drafting, and redlining legal documents, as well as answering legal and compliance questions swiftly.
Flank differentiates itself from chatbots and copilots by autonomously resolving requests directly within tools like email, Slack, and Microsoft Teams, eliminating the need for new interfaces or employee retraining. The agent is designed to handle high-volume workflows, such as NDAs and compliance checks, freeing up legal departments to focus on strategic tasks. CEO Lili Breidenbach emphasizes that Flank allows legal teams to concentrate on high-value work while the agent handles routine tasks invisibly and autonomously. Sophie Beshar from Insight Partners recognizes Flank as a pioneer in autonomous agents capable of real work at scale, addressing the strains faced by legal teams. Microsoft Build 2025 showcased Microsoft's strategic shift towards agentic AI, emphasizing its potential to transform software development. CEO Satya Nadella highlighted the evolution of AI from an assistant to an agent capable of performing complex workflows. Microsoft aims to collaborate with the development community to build the future of agentic AI development. The conference addressed concerns about the role of developers in the age of agentic AI, reaffirming Microsoft's commitment to software development and highlighting AI's role in enhancing, not replacing, human capabilities. AI is also becoming integral in cybersecurity. Impart Security, with recent backing, is developing an agentic approach to runtime security, empowering security teams to proactively address cyberattacks. The increasing complexity of digital interactions and the expansion of attack surfaces necessitate AI-driven efficiency in security. Traditional security systems struggle to keep pace with modern attacks. Impart Security aims to provide comprehensive, actionable, and automated responses to security threats, moving beyond mere detection. Recommended read:
References :
Clint Boulton,@Dell Technologies
//
AI is rapidly transforming several key areas, including software development, AI security, and customer interactions. In software development, prompting GenAI systems to create code is reducing repetitive processes, accelerating production cycles and freeing up developers to focus on higher-value projects. Databricks and Noma are addressing critical AI inference vulnerabilities, while Impel is enhancing customer experiences in the automotive sector through fine-tuned AI models. Furthermore, agentic AI is enabling autonomous, goal-driven decision-making across the IoT, paving the way for smarter and more efficient smart environments.
Databricks and Noma Security are partnering to tackle AI inference vulnerabilities, helping CISOs confidently scale secure enterprise AI deployments. CISOs recognize that the vulnerable stage of AI deployment is inference, where live models encounter real-world data, leading to potential exposure to prompt injection, data leaks, and model jailbreaks. To combat these threats, Databricks Ventures and Noma Security are embedding real-time threat analytics, advanced inference-layer protections, and proactive AI red teaming directly into enterprise workflows. This joint approach is bolstered by a $32 million Series A funding round led by Ballistic Ventures and Glilot Capital, with strong support from Databricks Ventures. Impel is revolutionizing automotive retail by improving customer experience using fine-tuned LLMs on Amazon SageMaker. Their core product, Sales AI, provides personalized customer engagement 24/7, answering vehicle-specific questions and handling automotive trade-in and financing inquiries. By switching from a third-party LLM to a fine-tuned Meta Llama model on Amazon SageMaker AI, Impel achieved a 20% improvement in accuracy and greater cost control. Impel's Sales AI uses generative AI to provide instant responses around the clock to prospective customers through email and text, with features that provide consistent follow-up to engaged customers to help prevent stalled customer purchasing journeys and personalizes responses to align with retailer messaging and customer’s purchasing specifications. Recommended read:
References :
@pub.towardsai.net
//
References:
nordicapis.com
, pub.towardsai.net
,
Anthropic's Model Context Protocol (MCP) is rapidly gaining traction as a pivotal technology for AI agents, poised to revolutionize how these agents interact with external tools and APIs. MCP provides a standardized method for Large Language Models (LLMs) to access and utilize real-world services and data. This addresses a critical limitation of LLMs, which, while adept at processing information, traditionally lack the ability to directly trigger actions or retrieve live data from external sources. The protocol acts as a universal adapter, streamlining the integration of AI models with diverse tools and workflows, eliminating the need for custom integrations for each tool.
The MCP operates through a client-host-server architecture, enabling AI agents to discover available tools, invoke them as needed, and receive structured responses in a consistent format. This structured approach, using a declarative metadata model, greatly simplifies the development of scalable, tool-using AI agents and promotes efficient communication between the AI agent and the external resources. By standardizing the interaction process, MCP fosters autonomous consumption and multi-modal integrations, allowing AI agents to perform complex tasks with greater ease and efficiency. Netlify has embraced the Model Context Protocol with the release of its Netlify MCP Server, empowering AI agents to directly deploy code from within the development environment. This integration significantly enhances the agent experience, allowing AI agents to complete the entire development cycle, from code generation to deployment, without requiring manual intervention. The Netlify MCP Server provides agents with direct access to the Netlify API and CLI, enabling them to create projects, manage infrastructure, and deploy applications using natural language prompts. This capability marks a significant step towards seamless AI-driven development workflows, transforming the way developers interact with their tools and infrastructure. Recommended read:
References :
@orases.com
//
AI agents are rapidly transforming industries by automating tasks and enhancing decision-making, moving beyond simple automation to intelligent autonomy. These agents are being implemented across various sectors, promising significant improvements in efficiency and productivity. A strategic roadmap is essential for successful AI agent implementation, aligning technology with workflows and business objectives to ensure that these systems have a real impact on operations and decision-making. Without a clear structure, companies risk wasting investments on generic tools and isolated pilot projects.
The impact of AI agents is particularly evident in customer experience (CX), with companies increasingly integrating AI agents into their technology interactions. Cisco's recent Agentic AI Report highlights the transformative impact of these autonomous agents, which can retain memory, reason about tasks, and autonomously select actions to optimize outcomes with minimal human intervention. Cisco's data anticipates that enterprises expect 56% of their interactions with technology partners will be managed by AI agents within the next 12 months, increasing to 68% over three years. This accelerated adoption necessitates that vendors rapidly develop and deploy scalable, robust agentic AI solutions. Thomson Reuters is also leveraging this trend with agentic AI capabilities in its CoCounsel assistant, enabling autonomous, multi-step task execution in tax and accounting workflows. Early results show that processes like tax jurisdiction reviews have been drastically reduced from half a week to under an hour. The company plans to extend agentic AI to legal, risk, and compliance domains, connecting firm knowledge, codes, and internal documents into one workspace where AI handles complete workflows, rather than individual queries. This integration allows professionals to focus on higher-level tasks, ensuring that human expertise guides judgment and validates outputs. Recommended read:
References :
staff@insideAI News
//
IBM has launched watsonx AI Labs, a developer-first innovation hub located in New York City. The new lab is designed to accelerate the adoption of AI at scale by connecting IBM's enterprise resources and expertise with AI developers focused on building AI applications for business. Located in Manhattan at IBM's new offices at One Madison, watsonx AI Labs aims to connect IBM’s network of engineering labs, bringing together IBM researchers and engineers in a collaborative hub for co-creating and advancing agentic AI solutions.
The watsonx AI Labs is intended to co-create generative AI solutions with IBM clients, nurture AI talent within New York City, and advance enterprise AI implementations. IBM plans to work with startups, scale-ups, and enterprises to discover AI value through this initiative. New York City has a growing AI ecosystem, with more than 2,000 AI startups and an AI workforce that grew by almost 25% from 2022 to 2023. Since 2019, over 1,000 AI-related companies in New York City have collectively raised $27 billion in funding. As part of its investment in AI and commitment to the local startup ecosystem, IBM also announced the acquisition of Seek AI. Seek AI is a New York City-based startup that specializes in building AI agents that leverage enterprise data, providing businesses with a natural language interface to query and analyze corporate data stores. Seek AI's expertise will be integrated into watsonx AI Labs, helping businesses leverage agentic AI to extract value from their data and improve data analysis and summarization capabilities. Recommended read:
References :
Mahnoor Faisal@Latest from Laptop Mag
//
Opera has launched Opera Neon, marking what they call the "first AI agentic browser". This new browser aims to redefine the user experience by automating web actions based on user intent, essentially transforming the browser into a digital assistant. Opera Neon is designed to recognize what users want to achieve online and then execute those tasks autonomously. According to Opera, Neon is intended to function as a helpful digital coworker, rather than just a passive window to the internet.
Opera Neon will come equipped with a built-in conversational agent capable of searching, summarizing pages, and providing contextual answers directly within the browser's interface. Complementing this is a "Browser Operator" agent designed to handle routine tasks such as filling out forms, booking hotels, and managing online shopping carts. Opera emphasizes that these interactions will be processed locally to ensure user privacy. Beyond local tasks, Neon connects to a cloud-based AI engine that can conduct research, design content, and even build entire websites and games on the user's behalf. The company is inviting developers and power users to shape Neon’s roadmap, framing the release as the first step toward what it calls “the AI agentic web.” The product is slated to launch as a premium subscription service, with pricing and release date details yet to be announced. A waitlist is currently open at operaneon.com. This move follows Opera’s earlier integration of Browser Operator into its flagship browser and its existing Aria chatbot feature, solidifying the company’s strategy to leverage AI as a key differentiator against competitors like Microsoft Edge, Google Chrome, and Apple Safari. Opera hopes this shift will allow users to focus on higher-value work. Recommended read:
References :
@www.marktechpost.com
//
The development of AI agents capable of performing human tasks on computers is gaining momentum, with a particular focus on multi-agent communication systems. Several research labs and companies are actively exploring this area, aiming to build agents that can effectively coordinate and collaborate. A key aspect of this research involves establishing robust communication protocols that enable seamless interaction between multiple AI agents. Recent articles highlight the progress being made in constructing code using these multi-agent communication systems, paving the way for more sophisticated and autonomous AI applications.
Mistral AI recently released its Agents API, providing public access through La Plateforme for developers to create autonomous agents. This API allows agents to plan tasks, utilize external tools, and maintain long-term context. The interface comes equipped with connectors for Python execution, web search, Flux 1.1 image generation, and a document library. The Agents API supports the mistral-medium-latest and mistral-large-latest models, allowing agents to delegate subtasks to each other via the Model Context Protocol, creating coordinated workflows across multiple services. A tutorial was recently released which provides a coding guide to building scalable multi-agent communication systems using the Agent Communication Protocol (ACP). This guide implements ACP by building a flexible messaging system in Python, leveraging Google's Gemini API for natural language processing. The tutorial details the installation and configuration of the google-generativeai library, introduces core abstractions, message types, performatives, and the ACPMessage data class for standardizing inter-agent communication. Through ACPAgent and ACPMessageBroker classes, the guide demonstrates how to create, send, route, and process structured messages among multiple autonomous agents, also showing how to implement querying, requesting actions, broadcasting information, maintaining conversation threads, acknowledgments, and error handling. Recommended read:
References :
@www.microsoft.com
//
Microsoft is leading the charge in AI-driven automation with the introduction of new tools and protocols designed to empower businesses through AI agents. At Microsoft Build 2025, the company announced the Model Context Protocol (MCP) servers for Microsoft Dynamics 365 ERP and CRM business applications. These servers aim to streamline the integration of AI agents into business processes, enabling customers and partners to build AI-powered agents more quickly and efficiently. This move is part of a broader vision of the "autonomous enterprise," where AI and automation drive innovation and adaptation.
Microsoft's initiatives also include advancements in agentic user experience (AUX). The company recently unveiled Magentic-UI, an open-source agentic web interface built on the Magentic-One architecture. Magentic-UI is designed to support complex, multi-step task workflows through human-AI collaboration. By combining large language models (LLMs), containerized execution environments, and real-time user feedback, Magentic-UI offers a cohesive platform for dynamic and secure task automation, moving beyond simple chat interfaces to provide more sophisticated agent interactions. In addition to these developments, Microsoft is also focused on ensuring the security and interoperability of AI agents. The company recognizes the need for evolving identity standards, particularly OAuth, to manage how agents access data and act across connected systems. Microsoft has launched the public preview of its Conditional Access Optimizer Agent, a multi-functional AI agent that analyzes an organization's Conditional Access policies, identifies security gaps, and recommends policy improvements. Furthermore, Microsoft is investing in agents for developer and operations workflows, such as SWE and SRE agents, to boost productivity in application development and maintenance, reinforcing the importance of standardization in the AI ecosystem. Recommended read:
References :
@www.marktechpost.com
//
OpenAI is pushing the boundaries of AI development with a strategic focus on agentic APIs, enabling developers to build more sophisticated and autonomous AI agents. The OpenAI Responses API stands out as the first truly agentic API, allowing developers to integrate multiple functionalities like code interpretation, reasoning, web search, and Retrieval-Augmented Generation (RAG) within a single API call. This advancement streamlines the creation of the next generation of AI agents, simplifying complex tasks.
The shift towards agentic APIs, pioneered by OpenAI, is seeing convergence among major Large Language Model (LLM) API vendors. Key features include code execution in a secure Python sandbox, web search capabilities, document libraries for hosted RAG, image generation, and Model Context Protocol (MCP) tools. The ability to combine these elements into a single API call will enable developers to build agents capable of performing real-world tasks, managing interactions across conversations, and dynamically orchestrating multiple agents. Beyond its focus on agentic APIs, OpenAI's future roadmap includes a focus on healthcare and robotics, indicating a broader application of AI in solving complex, real-world problems. Additional developments include a partnership with Jony Ive on a mystery AI device, signaling a move into AI-driven hardware. These advancements signal a continued investment in AI development and its application across diverse sectors. Recommended read:
References :
Jaime Hampton@AIwire
//
References:
AIwire
Microsoft has announced a new AI-powered orchestration system designed to revolutionize cancer care planning. This system, accessible through the Azure AI Foundry Agent Catalog, utilizes a healthcare agent orchestrator to consolidate and analyze diverse medical data sources such as imaging, genomics, clinical notes, and pathology. The goal is to assist clinicians in developing personalized treatment plans by streamlining the tumor board process, which traditionally involves in-depth reviews of patient records by multidisciplinary specialists.
The current tumor board model, while effective, is resource-intensive and only available to a small fraction of patients worldwide. Microsoft's AI-driven solution seeks to democratize access to comprehensive cancer care by automating key tasks within the tumor board workflow. The orchestrator employs both general-purpose and domain-specific AI agents to expedite processes that typically take hours. These agents can review and summarize medical images, pathology slides, and electronic health record (EHR) data, assess cancer stages according to established guidelines, identify relevant clinical trials, and compile current medical research into actionable reports. The AI system is designed to integrate seamlessly into platforms already used by clinicians, including Microsoft Teams, Word, and the broader Microsoft 365 suite. Early adopters of the technology include leading healthcare institutions such as Stanford Health Care, Johns Hopkins, Providence Genomics, and UW Health. Clinicians at Stanford are already using foundation model-generated summaries during tumor board meetings to reduce data fragmentation and surface insights that were previously difficult to access. The new healthcare agent orchestrator holds the potential to transform cancer care planning by enhancing efficiency, improving data accessibility, and ultimately enabling more personalized treatment strategies. Recommended read:
References :
Ken Yeung@Ken Yeung
//
Microsoft is significantly expanding its AI capabilities to the edge, empowering developers with tools to create innovative AI agents. This strategic move, unveiled at Build 2025, focuses on enabling smarter and faster experiences across various devices. Unlike previous strategies centered on single-use AI assistants, Microsoft is now emphasizing dynamic agents that seamlessly integrate with third-party systems through the Model Context Protocol (MCP). This shift aims to create broader, integrated ecosystems where agents can operate across diverse use cases and integrate with any digital infrastructure.
Microsoft is empowering developers by offering the OpenAI Responses API, which allows the combination of MCP servers, code interpreters, reasoning, web search, and RAG within a single API call. This capability enables the development of next-generation AI agents. Among the announcements at Build 2025 were a platform to build on-device agents, the ability to bring AI to web apps on the Edge browser, and developer capabilities to deploy bots directly on Windows. The company hopes the developments will lead to broader use of AI technologies and a significant increase in the number of daily active users. Microsoft is already demonstrating the impact of its agentic AI platform, Azure AI Foundry, in healthcare, including streamlining cancer care planning. In addition to their AI initiatives, Microsoft has introduced a new AI-powered orchestration system that streamlines the complex process of cancer care planning. This orchestration system, available through the Azure AI Foundry Agent Catalog, brings together specialized AI agents to assist clinicians with the analysis of multimodal medical data, from imaging and genomics to clinical notes and pathology. Early adopters include Stanford Health Care, Johns Hopkins, Providence Genomics, and UW Health. Recommended read:
References :
@devblogs.microsoft.com
//
Microsoft is aggressively pushing AI innovation to the edge, with a series of announcements highlighting the company's vision for an AI-powered future where humans partner with autonomous agents. At the Build developer conference, Microsoft unveiled tools designed to help developers build this agentic future, embedding bots into browsers, websites, operating systems, and everyday workflows. Unlike previous Copilot-centric approaches, Microsoft is placing greater emphasis on dynamic agents, powered by integrations with third-party systems through the Model Context Protocol (MCP), shifting from single-use AI assistants to broader, integrated ecosystems.
Microsoft is also introducing the Agent Store for Microsoft 365 Copilot, a centralized, curated marketplace designed to help automate tasks, streamline workflows, and boost productivity. The Agent Store offers a new experience within Microsoft 365 Copilot that enables users to browse, install, and try agents tailored to their needs, and features agents built by Microsoft, trusted partners, and customers. With over 70 agents available at launch, the Agent Store aims to make it easier to discover, share, and deploy agents across teams and organizations, using both low-code and pro-code tools. Furthermore, Microsoft’s agentic AI platform, Azure AI Foundry, is powering key healthcare advances with Stanford. Beyond healthcare, Microsoft is exploring ways to bring AI to web apps on the Edge browser and enable developers to deploy bots directly on Windows, as the company recognizes the full potential of its AI agents ecosystem is still unfolding. Recommended read:
References :
@www.bigdatawire.com
//
Starburst is enhancing its data platform with new agentic AI capabilities, marking a significant step in the evolution of enterprise AI. These updates include the introduction of Starburst AI Workflows, a suite designed to expedite AI experimentation and deployment, alongside Starburst AI Agent, a pre-built natural language interface for the platform. This move aims to empower data analysts and application-layer AI agents, enabling them to extract faster and more insightful business insights from the data lakehouse. Starburst is also launching Starburst Data Catalog, a modern enterprise-grade metastore solution purpose-built to replace Hive Metastore in Starburst Enterprise.
The new AI capabilities address the growing need for enterprises to leverage AI for better-informed decision-making and increased efficiency. With fragmented data spread across various clouds and formats, many organizations struggle to build effective AI workflows. Starburst's platform updates aim to remove the friction between data and AI, enabling enterprise data teams to rapidly build AI applications and analytics on a single, governed foundation. Starburst uniquely helps enterprises speed up AI adoption, reduce costs, and realize value faster by enabling access to all their data, no matter where it lives, across clouds, on-premises, or hybrid environments, so they don’t need to move or migrate it to build, train, or tune their AI models. Justin Borgman, CEO and co-founder of Starburst, emphasized that AI's power is directly tied to the data it can access. The company's aim is to remove the barriers between data and AI by bringing distributed, hybrid data lakeside capabilities, enabling enterprise data teams to rapidly build AI and analytics on a governed foundation. Kevin Petrie, an analyst at BARC U.S., noted the significance of Starburst's new tools, highlighting their focus on addressing key risks associated with AI development, such as data access, quality, privacy, and incompatible systems. Recommended read:
References :
Michael Nuñez@AI News | VentureBeat
//
References:
techstrong.ai
, AI News | VentureBeat
,
Microsoft has significantly expanded its Copilot Studio platform at Build 2025, introducing multi-agent systems designed to revolutionize enterprise workflows. This expansion allows AI agents built with Copilot Studio, Microsoft 365, Azure AI Agents Service, and Azure Fabric to collaborate on complex business tasks, delegating tasks to each other to complete processes. According to Ray Smith, VP of AI Agents at Microsoft, this approach addresses the challenges of creating reliable processes within a single agent, improving maintainability, simplifying solution building, and enhancing overall reliability. An example scenario involves a Copilot Studio agent pulling sales data from a CRM, handing it to a Microsoft 365 agent to draft a proposal in Word, and then triggering another agent to schedule follow-ups in Outlook.
Microsoft is also committed to building an open agentic AI ecosystem, demonstrated by its support for Anthropic’s Model Context Protocol (MCP). GitHub and Microsoft have joined the steering committee for MCP, an open-source standard designed to enable AI tools to directly access data systems. This initiative aims to simplify data connections for AI models, allowing them to fetch information from apps and data stores more easily and safely. The MCP allows any AI client to communicate with any MCP server through a standard interface, eliminating the need for custom connectors for each data source. Microsoft plans to add first-party support across Azure and Windows to assist developers in exposing app features as MCP servers. Furthering its commitment to open AI, Microsoft is making available a Model Router and a Model Leaderboard to optimize model selection for specific tasks. The Model Router enables real-time selection of the best model for a given query, while the Model Leaderboard ranks AI models based on their performance across various categories. Additionally, Microsoft is offering pre-built agents, custom agent building blocks, and a software development kit (SDK) based on MCP. The company is also extending the observability capabilities of its Azure AI Foundry to agents, offering comprehensive tools and platforms to foster an open and collaborative AI ecosystem, referred to as the Agentic Web. Recommended read:
References :
@www.salesforce.com
//
References:
Salesforce
, Salesforce
,
Salesforce is placing significant emphasis on data security as it rolls out its AI agent implementations. According to recent research, a strong data foundation and robust governance capabilities are critical for businesses to securely implement agentic AI. While IT security leaders are largely optimistic about the potential benefits of AI agents, a majority acknowledge that there are significant readiness gaps in deploying the necessary security safeguards. This highlights the importance of prioritizing security measures as AI adoption accelerates across various industries.
As AI becomes more prevalent and cyber threats continue to evolve, a considerable number of IT security leaders recognize the need to transform their security practices. In fact, nearly 8 in 10 acknowledge that their security protocols require upgrades to address the challenges posed by AI. This transformation includes building AI fluency within organizations, redesigning workflows to incorporate AI agents effectively, and ensuring adequate human supervision to mitigate risks and maintain ethical standards. It's also worth noting that Salesforce's own data indicates unanimous optimism among IT leaders regarding the potential of AI agents. Salesforce is actively developing and acquiring technologies to enhance its Agentforce platform and empower developers to build secure and effective AI agents. The acquisition of Convergence, an AI automation startup, will integrate advanced AI agent design and automation capabilities into Agentforce. Furthermore, the launch of the Salesforce Developer Edition, which includes access to Agentforce and Data Cloud, provides developers with the tools to create, customize, and deploy autonomous AI agents with appropriate guardrails. By emphasizing secure data handling and governance, Salesforce aims to enable businesses to leverage the benefits of AI agents while minimizing potential security risks. Recommended read:
References :
|
BenchmarksBlogsResearch Tools |