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SAP systems and applications handle massive amounts of sensitive data that is hosted on Azure, Google Cloud Platform (GCP), Amazon Web Services (AWS), or on-premises infrastructure. The SAP ecosystem is complex and difficult for security operations (SecOps) teams to effectively monitor and protect. The Microsoft Sentinel solution for SAP® applications allows you to monitor, detect, and respond to suspicious activities and guard your business-critical data against sophisticated cyberattacks.
Microsoft Security Exposure Management is a comprehensive security solution designed to provide organizations with unified visibility into their security posture across various assets and workloads. By continuously discovering and assessing assets, it enables security teams to proactively identify vulnerabilities, prioritize critical risks, and implement effective remediation strategies to reduce the attack surface and enhance overall security. Key Features and Functionality: - Attack Surface Management: Offers a continuous and comprehensive view of the organization's attack surface, allowing teams to monitor exposure and focus on protecting critical assets. - Attack Path Analysis: Visualizes potential attack paths, enabling security teams to identify and prioritize remediation efforts to reduce risks effectively. - Unified Exposure Insights: Aggregates security posture data from various sources, providing decision-makers with a consolidated view of the organization's threat exposure to facilitate informed decision-making. - Integration with Security Tools: Seamlessly integrates with both Microsoft and non-Microsoft security and infrastructure tools, including Microsoft Defender for Endpoint, Microsoft Defender for Identity, and Microsoft Defender for Cloud Apps, to provide a holistic view of the security environment. Primary Value and Problem Solved: Microsoft Security Exposure Management addresses the challenge of fragmented security data and siloed management by unifying disparate data sources into a single, comprehensive view. This integration empowers organizations to proactively manage their attack surfaces, protect critical assets, and mitigate exposure risks. By providing continuous visibility and actionable insights, it enables security teams to transition from reactive vulnerability management to a proactive, risk-based approach, thereby enhancing the organization's overall security posture and resilience against evolving cyber threats.
Smaller Phi-3 model variant with extended 8k token context and instruction capabilities.
Microsoft Copilot for Security is an AI-powered cybersecurity assistant designed to enhance the efficiency and effectiveness of security professionals. By integrating advanced generative AI with Microsoft's extensive threat intelligence, Copilot enables rapid detection, analysis, and response to security incidents, empowering defenders to operate at machine speed and scale. Key Features and Functionality: - Incident Investigation and Response: Provides step-by-step guidance for triaging, investigating, containing, and remediating security incidents, streamlining the response process. - Threat Hunting and Intelligence Gathering: Assists in identifying and analyzing potential threats by leveraging vast datasets and advanced analytics. - Security Posture Management: Offers insights into organizational security posture, highlighting vulnerabilities and recommending improvements. - Integration with Microsoft Security Products: Seamlessly integrates with tools like Microsoft Defender XDR, Microsoft Sentinel, Microsoft Intune, and Microsoft Entra, providing a unified security experience. - Custom Promptbooks and Knowledge Base Integrations: Allows creation of tailored prompts for common security tasks and integration with organizational knowledge bases for context-specific guidance. Primary Value and Problem Solved: Copilot for Security addresses the challenges of modern cybersecurity, including the increasing volume and sophistication of threats, the complexity of security environments, and the shortage of skilled professionals. By automating routine tasks, providing actionable insights, and enhancing collaboration, Copilot enables security teams to respond more swiftly and accurately to incidents, ultimately strengthening organizational defenses.
CertWatch for Azure Certificates & Secrets Tracking is an advanced multi-tenant solution developed by Enkaytech to simplify the challenges of managing certificate and secret expirations in Azure application registrations. It enables users to easily track expiry dates for secrets and certificates tied to their Azure resources, including Application Registrations and Integration Accounts. With timely renewal alerts, it helps prevent disruptions and ensures smooth operations.
Phi-4-mini-reasoning is a compact, transformer-based language model developed by Microsoft, specifically optimized for mathematical reasoning tasks. With 3.8 billion parameters and support for a 128K token context length, it delivers high-quality, step-by-step problem-solving capabilities in environments where computational resources or latency are constrained. Fine-tuned using synthetic mathematical data generated by a more advanced model, Phi-4-mini-reasoning excels in multi-step, logic-intensive problem-solving scenarios, making it suitable for applications such as formal proof generation, symbolic computation, and advanced word problems. Key Features and Functionality: - Optimized for Mathematical Reasoning: Designed to handle complex, multi-step mathematical problems with structured logic and analytical thinking. - Compact Architecture: Balances reasoning ability with efficiency, enabling deployment in resource-constrained environments. - Extended Context Length: Supports up to 128K tokens, allowing for comprehensive context retention across problem-solving steps. - Fine-Tuned with Synthetic Data: Trained on a diverse set of over one million math problems, enhancing its reasoning performance. Primary Value and Problem Solving: Phi-4-mini-reasoning addresses the need for efficient, high-quality mathematical reasoning in scenarios where computational resources are limited. Its compact size and optimized performance make it ideal for educational applications, embedded tutoring systems, and deployments on edge or mobile devices. By maintaining context across multiple steps and applying structured logic, it provides accurate and reliable solutions for complex mathematical problems, thereby enhancing learning experiences and supporting advanced analytical tasks.
The Phi-3 Mini-4K-Instruct is a lightweight, state-of-the-art language model developed by Microsoft, featuring 3.8 billion parameters. It is part of the Phi-3 model family and is designed to support a context length of 4,000 tokens. Trained on a combination of synthetic data and filtered publicly available websites, the model emphasizes high-quality, reasoning-dense content. Post-training enhancements, including supervised fine-tuning and direct preference optimization, have been applied to improve instruction adherence and safety measures. The Phi-3 Mini-4K-Instruct demonstrates robust performance across benchmarks assessing common sense, language understanding, mathematics, coding, long-context comprehension, and logical reasoning, positioning it as a leading model among those with fewer than 13 billion parameters. Key Features and Functionality: - Compact Architecture: With 3.8 billion parameters, the model offers a balance between performance and resource efficiency. - Extended Context Length: Supports processing of up to 4,000 tokens, enabling handling of longer inputs effectively. - High-Quality Training Data: Utilizes a curated dataset combining synthetic data and filtered web content, focusing on high-quality and reasoning-intensive information. - Enhanced Instruction Following: Post-training processes, including supervised fine-tuning and direct preference optimization, improve the model's ability to follow instructions accurately. - Versatile Performance: Excels in various tasks such as common sense reasoning, language understanding, mathematical problem-solving, coding, and logical reasoning. Primary Value and User Solutions: The Phi-3 Mini-4K-Instruct addresses the need for a powerful yet efficient language model suitable for environments with limited memory and computational resources. Its compact size and extended context capabilities make it ideal for applications requiring low latency and strong reasoning abilities. By delivering state-of-the-art performance in a resource-efficient package, it enables developers and researchers to integrate advanced language understanding and generation features into their applications without the overhead associated with larger models.
The Phi-3-Small-128K-Instruct is a 7-billion-parameter, state-of-the-art language model developed by Microsoft. It is part of the Phi-3 family and is designed to handle a context length of up to 128,000 tokens. Trained on a combination of synthetic data and filtered publicly available web content, the model emphasizes high-quality, reasoning-dense properties. Post-training processes, including supervised fine-tuning and direct preference optimization, have been applied to enhance its instruction-following capabilities and safety measures. The Phi-3-Small-128K-Instruct demonstrates robust performance across benchmarks testing common sense, language understanding, mathematics, coding, long-context comprehension, and logical reasoning, positioning it competitively among models of similar and larger sizes. Key Features and Functionality: - Extensive Context Handling: Supports a context length of up to 128,000 tokens, enabling the processing of long and complex inputs. - High-Quality Training Data: Utilizes a blend of synthetic and curated web data, focusing on content rich in reasoning and quality. - Advanced Post-Training Techniques: Incorporates supervised fine-tuning and direct preference optimization to improve instruction adherence and safety. - Versatile Performance: Excels in tasks requiring common sense, language understanding, mathematical reasoning, coding proficiency, and logical analysis. Primary Value and User Solutions: The Phi-3-Small-128K-Instruct model offers developers and researchers a powerful tool for building AI systems that require deep reasoning and the ability to process extensive contextual information. Its efficient architecture makes it suitable for memory and compute-constrained environments, while its strong performance in various reasoning tasks addresses the needs of applications demanding high levels of understanding and analysis. By providing a robust foundation for generative AI features, the model accelerates the development of advanced language and multimodal applications.
The Phi-3 Mini-4K-Instruct is a lightweight, state-of-the-art language model developed by Microsoft, featuring 3.8 billion parameters. It is part of the Phi-3 model family and is designed to support a context length of 4,000 tokens. Trained on a combination of synthetic data and filtered publicly available websites, the model emphasizes high-quality, reasoning-dense content. Post-training enhancements, including supervised fine-tuning and direct preference optimization, have been applied to improve instruction adherence and safety measures. The Phi-3 Mini-4K-Instruct demonstrates robust performance across benchmarks assessing common sense, language understanding, mathematics, coding, long-context comprehension, and logical reasoning, positioning it as a leading model among those with fewer than 13 billion parameters. Key Features and Functionality: - Compact Architecture: With 3.8 billion parameters, the model offers a balance between performance and resource efficiency. - Extended Context Length: Supports processing of up to 4,000 tokens, enabling handling of longer inputs effectively. - High-Quality Training Data: Utilizes a curated dataset combining synthetic data and filtered web content, focusing on high-quality and reasoning-intensive information. - Enhanced Instruction Following: Post-training processes, including supervised fine-tuning and direct preference optimization, improve the model's ability to follow instructions accurately. - Versatile Performance: Excels in various tasks such as common sense reasoning, language understanding, mathematical problem-solving, coding, and logical reasoning. Primary Value and User Solutions: The Phi-3 Mini-4K-Instruct addresses the need for a powerful yet efficient language model suitable for environments with limited memory and computational resources. Its compact size and extended context capabilities make it ideal for applications requiring low latency and strong reasoning abilities. By delivering state-of-the-art performance in a resource-efficient package, it enables developers and researchers to integrate advanced language understanding and generation features into their applications without the overhead associated with larger models.
Microsoft Reviews
Francisco Javier S.
Product Manager en QuilosaThe ultimate control center for my workday, despite a slightly dated interface
Francisco Javier S.
Product Manager en QuilosaUnmatched data modeling and visualization, but expects a steep learning curve
Francisco Javier S.
Product Manager en QuilosaReliable hub for daily collaboration, though it can be a resource hog
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Every company has a mission. What's ours? To empower every person and every organization to achieve more. We believe technology can and should be a force for good and that meaningful innovation contributes to a brighter world in the future and today. Our culture doesn’t just encourage curiosity; it embraces it. Each day we make progress together by showing up as our authentic selves. We show up with a learn-it-all mentality. We show up cheering on others, knowing their success doesn't diminish our own. We show up every day open to learning our own biases, changing our behavior, and inviting in differences. Because impact matters. Microsoft operates in 190 countries and is made up of approximately 8,000 passionate employees worldwide.