Optanix announced its official launch.
Optanix offers a platform and related services for seamless IT operations management in the digital age, with a patented approach to optimizing the service delivery infrastructure that powers today’s critical business operations. The company was spun off from ShoreGroup following a majority investment in June 2015 by Francisco Partners. Optanix, led by CEO Robert Kennedy, counts the world’s top banks, media and technology companies, and federal government agencies among it’s customers. Headquartered in New York City, the company employs more than 400 people aligned around its common mission of delivering predictable IT services to its global customer base.
“In today’s ultra-competitive digital economy, achieving service availability and performance management targets is only possible by ensuring the reliability of service delivery infrastructure. Yet historically, this process has been largely reactive, putting undue pressure on IT teams and leaving too much room for error,” explained Kennedy. “Not anymore. Distilling down our many years of real-world IT operations support experience, Optanix equips organizations worldwide with turnkey proactive, predictable IT service delivery via a SaaS model.”
Armed with the Optanix platform and related services, IT organizations can shift from reactive, ad hoc processing of millions of unqualified events to a predictable, proactive approach which quickly identifies the root cause of issues impacting their digital services and applications. Leveraging its patented Advanced Logic Automation (ALA), Optanix is able to continuously audit any event stream across any monitored system – automatically sifting through large volumes of data to pinpoint the exact corrective action, and get it to the right people, in the right way, at the right time.
This multi-stage approach is built on four key principles:
- Complete Visibility: Optanix closes the visibility gap once and for all, offering a complete picture of the IT environment through a continuous audit of the current state of performance for truly proactive monitoring and management.
- Targeted Focus: Optanix leverages four patented filtering methodologies to pinpoint and validate the cause of each event, mapping trends and patterns with custom thresholds and alert criteria based on the organization’s specific environment.
- Accelerated Remediation: Optanix gathers the right information to properly assess and classify event impacts and resolve issues fast – delivering issues and suggested remediation steps to the right personnel in seconds, and enabling the resolution of more than 90 percent of events the first time.
- Continuous Improvement: Optanix continually identifies and analyzes a myriad of events each day, and feeds that knowledge back into its platform. The result is a library of more than two million best practices resident in its correlation and decision engine, accumulated from the collective experience in more than a thousand managed environments at some of the world’s largest organizations. This experiential learning is available to Optanix clients immediately, and on an ongoing basis.
The Optanix Platform is built on the collective experience gained by monitoring and managing some of the world’s largest enterprise, service provider, and government environments. Optanix’s platform and services are delivered through leading channel partners, including, Cisco, IBM, Arrow, Presidio and more.
“Francisco Partners has a long history of investing in companies that effectively leverage leading technology to drive tangible change,” said Andrew Kowal, Partner at Francisco Partners. “We embrace the shared vision to change the status quo in IT operations management by delivering predictable business outcomes to organizations around the globe. Congratulations to our partners on the management team as we reach this exciting milestone of launching Optanix as an independent entity.”
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.