Problem Statement

As a Broadcom NetOps customer supporting over 100 clients, the company needed to go beyond basic fault detection and achieve true situational awareness across its entire environment. While NetOps delivered excellent and detailed insight into device-level events, the customer wanted more contextualized intelligence across all events, uncover patterns, recommend optimizations, and highlight emerging business risks. The company also wanted a way to leverage an agentic workforce model to gain a competitive edge, one that could synthesize vast volumes of telemetry across disparate monitoring domains and inform their decisions with insight, not just information.

Proposed Solution and Architecture

The company partnered with A&I Solutions to embed ScoutITAi as an intelligent AI layer across its Broadcom observability stack. With a five-year commitment to the platform, the company is using ScoutITAi in two key ways:

• Internally: to deliver clearer visibility, faster decisions, and more efficient operations across the service landscape.
• Externally: with plans to offer ScoutITAi as a value-added service, extending AI observability to hundreds of managed environments.

ScoutITAi integrates seamlessly with the company’s Broadcom tools. Key components include:

• DX NetOps delivers deep fault and performance visibility across client networks.
• AppNeta: expands monitoring into hybrid WAN environments.
• ScoutITAi unifies and interprets telemetry through generative AI, providing natural-language insights, surfacing patterns, and enabling contextual decision-making across diverse client infrastructures.

Outcomes and Success Highlights

Although adoption is still early, the company has already seen meaningful wins with ScoutITAi’s AI-native model.

• The CTO tested ScoutITAi’s Agentic architecture by asking real operational questions and was impressed by the quality and depth of the insights.
• Those results accelerated the rollout of ScoutITAi and AppNeta to more sites and led to additional monitoring points.
• Cross-domain analysis and clear context are setting the stage for smarter service delivery and proactive issue resolution at scale.

As the company continues to deploy ScoutITAi, it’s building an AI-driven MSP operating model, helping teams think and act faster with unified insight across customers, tools, and technologies.

TCO Considerations

A formal TCO analysis is forthcoming, but the company already expects significant operational value from:

• Consolidated analysis across all monitored domains, reducing tool fragmentation and manual correlation.
• Enhanced decision support that speeds incident detection and enables proactive management.
• Scalable insight delivery that strengthens both internal operations and client-facing services.

Lessons Learned

• Early experimentation with ScoutITAi’s Agentic model delivered clear value and helped fast-track the rollout.
• Global context and AI-driven analysis are key differentiators compared to traditional monitoring tools.
• The company is well-positioned to extend ScoutITAi to its customers, creating a new value stream that blends service delivery with intelligent observability.

With ScoutITAi, the company isn’t just monitoring networks; it’s reimagining how AI can elevate MSP performance, insight, and scale.