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Redwood Software Unveils Redwood Insights

Redwood Software announced the launch of Redwood Insights, an AI-powered observability solution integrated into Redwood's flagship orchestration platform RunMyJobs. 

This launch represents a pivotal moment in Redwood's broader AI vision: to empower organizations with the intelligence and autonomy needed to scale operations, drive efficiency and focus human potential on strategic outcomes.

Redwood Insights transforms how businesses monitor, analyze and act on critical workflows by delivering workflow analytics, AI-powered narratives and real-time operational intelligence. The result is total visibility and orchestration precision, allowing teams to anticipate bottlenecks before they occur and optimize performance for critical business processes across complex IT and business environments.

These role-based views offer strategic benefits, including:

  • Enhanced observability: Reduce failures, minimize downtime and lower operational costs with deep visibility of the health and performance of your critical business processes.
  • From insights to action: Take proactive action and deliver faster time to resolution with real-time analytics that predict bottlenecks and rapidly optimize workflows.

"Redwood's AI vision is grounded in delivering real value and real outcomes—not hype," said Charles Crouchman, Chief Product Officer at Redwood Software. "With Redwood Insights, we're helping our customers go beyond dashboards. We're empowering our customers with observability that leads directly to action—powered by AI, tailored to every role and designed to keep your business in perfect sync."

Redwood Insights follows the release of Redwood's AI documentation assistant as part of a broader roadmap that introduces AI capabilities across the entire automation lifecycle. It leverages both agentic and generative AI technologies and is focused on delivering three core outcomes for customers:

  • AI agents for autonomous operations and optimization: Operate autonomously to optimize performance, resolve issues and interact with remote systems, making automation more accessible across your organization.
  • AI co-pilots for automation and collaboration: Collaborate directly with users to accelerate the automation and management of critical business processes, cutting hours from automation development.
  • AI assistants for information and guidance: Be empowered by contextual guidance, instant information and actions to take, eliminating human error and significantly accelerating response time.

Together, these capabilities define Redwood's commitment to seamlessly integrating AI into Redwood products to collaborate, inform and optimize—moving users from reactive to predictive and proactive orchestration.

Redwood Insights is currently in preview with customers and will roll out broadly later this year. The new capabilities support Redwood's mission of delivering autonomous operations, intelligent collaboration and actionable guidance — all natively embedded in the way teams already work today.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Redwood Software Unveils Redwood Insights

Redwood Software announced the launch of Redwood Insights, an AI-powered observability solution integrated into Redwood's flagship orchestration platform RunMyJobs. 

This launch represents a pivotal moment in Redwood's broader AI vision: to empower organizations with the intelligence and autonomy needed to scale operations, drive efficiency and focus human potential on strategic outcomes.

Redwood Insights transforms how businesses monitor, analyze and act on critical workflows by delivering workflow analytics, AI-powered narratives and real-time operational intelligence. The result is total visibility and orchestration precision, allowing teams to anticipate bottlenecks before they occur and optimize performance for critical business processes across complex IT and business environments.

These role-based views offer strategic benefits, including:

  • Enhanced observability: Reduce failures, minimize downtime and lower operational costs with deep visibility of the health and performance of your critical business processes.
  • From insights to action: Take proactive action and deliver faster time to resolution with real-time analytics that predict bottlenecks and rapidly optimize workflows.

"Redwood's AI vision is grounded in delivering real value and real outcomes—not hype," said Charles Crouchman, Chief Product Officer at Redwood Software. "With Redwood Insights, we're helping our customers go beyond dashboards. We're empowering our customers with observability that leads directly to action—powered by AI, tailored to every role and designed to keep your business in perfect sync."

Redwood Insights follows the release of Redwood's AI documentation assistant as part of a broader roadmap that introduces AI capabilities across the entire automation lifecycle. It leverages both agentic and generative AI technologies and is focused on delivering three core outcomes for customers:

  • AI agents for autonomous operations and optimization: Operate autonomously to optimize performance, resolve issues and interact with remote systems, making automation more accessible across your organization.
  • AI co-pilots for automation and collaboration: Collaborate directly with users to accelerate the automation and management of critical business processes, cutting hours from automation development.
  • AI assistants for information and guidance: Be empowered by contextual guidance, instant information and actions to take, eliminating human error and significantly accelerating response time.

Together, these capabilities define Redwood's commitment to seamlessly integrating AI into Redwood products to collaborate, inform and optimize—moving users from reactive to predictive and proactive orchestration.

Redwood Insights is currently in preview with customers and will roll out broadly later this year. The new capabilities support Redwood's mission of delivering autonomous operations, intelligent collaboration and actionable guidance — all natively embedded in the way teams already work today.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.