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Reveille Introduces AI-Powered Observability for Microsoft 365, SharePoint and Teams with Winter 2025 Update

Reveille Software announced the Reveille Winter 2025 Update, featuring Reveille AI Dynamic Thresholding. 

This latest release expands support for Microsoft 365, SharePoint Embedded, and Microsoft Teams and incorporates AI-driven machine learning to optimize automation monitoring and reduce operational inefficiencies.

The Reveille AI Dynamic Thresholding feature minimizes manual threshold adjustments, reduces false positive alerts, and dynamically adapts to workload variations within intelligent automation environments. Unlike traditional AI implementations focused on generative content, Reveille AI leverages machine learning models to enhance real-time operational performance, making AI more actionable and transparent for enterprises and Managed Service Providers (MSPs).

"Reveille's new AI support for intelligent automation solutions enhances the comprehensive coverage provided by Reveille's observability and monitoring," said Brian DeWyer, Co-Founder and Chief Technology Officer of Reveille. "Dynamic thresholds are just the first of multiple AI-based solutions planned for 2025, reinforcing our commitment to delivering smarter, more efficient monitoring capabilities."

Key Features of the Reveille Winter 2025 Update

  • Reveille AI Dynamic Thresholding – Utilizes open-source machine learning models to automatically set upper and lower thresholds, improving alert accuracy and reducing unnecessary notifications.
  • Expanded Microsoft 365 Observability – Enhanced monitoring support for SharePoint Embedded, Microsoft Teams, and Copilot, providing deeper insights into user activity and system performance.
  • New Reveille User Analytics Application Support – Advanced data-driven insights to improve automation efficiency and ensure optimal service levels.

Reveille AI is purpose-built for enterprises and MSPs operating in complex, intelligent automation environments. Unlike black-box AI solutions, Reveille AI provides forecast accuracy assessments and can run on-premises or in the cloud, ensuring flexibility and control. The system is designed to provide immediate business impact by leveraging data gathered during normal operations rather than relying on pre-trained datasets.

The Reveille Winter 2025 Update will be available for shipping on February 18, 2025. The software update is included in Reveille’s standard subscription and maintenance plans. The Reveille AI solution package, which provides licensing, consulting, and support, will be available as an add-on.

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Reveille Introduces AI-Powered Observability for Microsoft 365, SharePoint and Teams with Winter 2025 Update

Reveille Software announced the Reveille Winter 2025 Update, featuring Reveille AI Dynamic Thresholding. 

This latest release expands support for Microsoft 365, SharePoint Embedded, and Microsoft Teams and incorporates AI-driven machine learning to optimize automation monitoring and reduce operational inefficiencies.

The Reveille AI Dynamic Thresholding feature minimizes manual threshold adjustments, reduces false positive alerts, and dynamically adapts to workload variations within intelligent automation environments. Unlike traditional AI implementations focused on generative content, Reveille AI leverages machine learning models to enhance real-time operational performance, making AI more actionable and transparent for enterprises and Managed Service Providers (MSPs).

"Reveille's new AI support for intelligent automation solutions enhances the comprehensive coverage provided by Reveille's observability and monitoring," said Brian DeWyer, Co-Founder and Chief Technology Officer of Reveille. "Dynamic thresholds are just the first of multiple AI-based solutions planned for 2025, reinforcing our commitment to delivering smarter, more efficient monitoring capabilities."

Key Features of the Reveille Winter 2025 Update

  • Reveille AI Dynamic Thresholding – Utilizes open-source machine learning models to automatically set upper and lower thresholds, improving alert accuracy and reducing unnecessary notifications.
  • Expanded Microsoft 365 Observability – Enhanced monitoring support for SharePoint Embedded, Microsoft Teams, and Copilot, providing deeper insights into user activity and system performance.
  • New Reveille User Analytics Application Support – Advanced data-driven insights to improve automation efficiency and ensure optimal service levels.

Reveille AI is purpose-built for enterprises and MSPs operating in complex, intelligent automation environments. Unlike black-box AI solutions, Reveille AI provides forecast accuracy assessments and can run on-premises or in the cloud, ensuring flexibility and control. The system is designed to provide immediate business impact by leveraging data gathered during normal operations rather than relying on pre-trained datasets.

The Reveille Winter 2025 Update will be available for shipping on February 18, 2025. The software update is included in Reveille’s standard subscription and maintenance plans. The Reveille AI solution package, which provides licensing, consulting, and support, will be available as an add-on.

The Latest

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...