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Apiphani Raises $25M in Series A Funding

Apiphani announced $25 million in Series A funding led by global software investor Insight Partners. 

The new capital will accelerate apiphani's growth, expanding its footprint in regulated industries such as energy, utilities, and telecommunications, where uptime, security, and performance are paramount.

"At a time when global integrators will assign hundreds of people to support a relatively vanilla, mid-sized enterprise IT environment — and still miss service levels — we're proving there's a better way," says Justin Folkers, Co-Founder and CEO of apiphani. "CIOs and CFOs know that downtime is unacceptable. It's our belief that a combination of expert engineers and AI-driven automation is the only model that scales with resilience."

At the core of apiphani's approach is luumen, its proprietary observability platform powered by the company's AI-based Deep Automation™ technology. Originally developed to support apiphani's managed services, it is now a product offering available directly to enterprises. Luumen gives engineers real-time visibility into environments and integrates seamlessly with IT toolchains across monitoring, alerting & escalation, ITSM, security, and backups. Designed as both an ecosystem and an engineer's workbench, luumen includes a library of preconfigured automations for common application and infrastructure tasks. It also offers extensive add-ons and integrations that let teams tailor the platform to their environment. Beyond observability, luumen enables enterprises to build and monitor bespoke automations that reduce manual work, eliminate ticket sprawl, and increase the value of existing IT investments.

"We didn't inherit the technical debt of legacy providers, so we built from the ground up with automation at the center," says Cynthia Borgman, apiphani Co-Founder and Chief Delivery Officer. "This isn't about labor arbitrage. It's about enabling exceptional talent to do meaningful work in an environment that is both rewarding and supportive."

"Enterprises have heard many promises over the past decade — resilience, better security, and workflow automations that save time and resources, to name a few. Today, outages and security breaches are even more common, and enterprises are investing millions in AI without seeing ROI. Apiphani has built the software product and managed services offering to meet those promises for their customers, and we're thrilled to be partnering with them in this next chapter," says Richard Matus, Principal at Insight Partners.

Founded in 2018, apiphani began with on-premise SAP support and has since expanded its model to meet the needs of modern cloud and hybrid infrastructures. With new funding, the company plans to scale its engineering and go-to-market teams in Boston and Lisbon, while continuing to expand capabilities and broaden industry reach. "Our thesis was bold," says Folkers. "But we've proven it works at scale. With the support of Insight Partners, we're ready to help enterprises realign their operations with business objectives in ways that simply weren't possible before." Moelis & Company served as exclusive financial advisor to apiphani.

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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 ...

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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 ...

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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.

Apiphani Raises $25M in Series A Funding

Apiphani announced $25 million in Series A funding led by global software investor Insight Partners. 

The new capital will accelerate apiphani's growth, expanding its footprint in regulated industries such as energy, utilities, and telecommunications, where uptime, security, and performance are paramount.

"At a time when global integrators will assign hundreds of people to support a relatively vanilla, mid-sized enterprise IT environment — and still miss service levels — we're proving there's a better way," says Justin Folkers, Co-Founder and CEO of apiphani. "CIOs and CFOs know that downtime is unacceptable. It's our belief that a combination of expert engineers and AI-driven automation is the only model that scales with resilience."

At the core of apiphani's approach is luumen, its proprietary observability platform powered by the company's AI-based Deep Automation™ technology. Originally developed to support apiphani's managed services, it is now a product offering available directly to enterprises. Luumen gives engineers real-time visibility into environments and integrates seamlessly with IT toolchains across monitoring, alerting & escalation, ITSM, security, and backups. Designed as both an ecosystem and an engineer's workbench, luumen includes a library of preconfigured automations for common application and infrastructure tasks. It also offers extensive add-ons and integrations that let teams tailor the platform to their environment. Beyond observability, luumen enables enterprises to build and monitor bespoke automations that reduce manual work, eliminate ticket sprawl, and increase the value of existing IT investments.

"We didn't inherit the technical debt of legacy providers, so we built from the ground up with automation at the center," says Cynthia Borgman, apiphani Co-Founder and Chief Delivery Officer. "This isn't about labor arbitrage. It's about enabling exceptional talent to do meaningful work in an environment that is both rewarding and supportive."

"Enterprises have heard many promises over the past decade — resilience, better security, and workflow automations that save time and resources, to name a few. Today, outages and security breaches are even more common, and enterprises are investing millions in AI without seeing ROI. Apiphani has built the software product and managed services offering to meet those promises for their customers, and we're thrilled to be partnering with them in this next chapter," says Richard Matus, Principal at Insight Partners.

Founded in 2018, apiphani began with on-premise SAP support and has since expanded its model to meet the needs of modern cloud and hybrid infrastructures. With new funding, the company plans to scale its engineering and go-to-market teams in Boston and Lisbon, while continuing to expand capabilities and broaden industry reach. "Our thesis was bold," says Folkers. "But we've proven it works at scale. With the support of Insight Partners, we're ready to help enterprises realign their operations with business objectives in ways that simply weren't possible before." Moelis & Company served as exclusive financial advisor to apiphani.

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.