Automox announced Turnkey Results, a new offering that combines the most advanced Autonomous Endpoint Management with a prescriptive blueprint built from field-tested best practices that are personalized to an IT team's specific environment, requirements, and goals.
For years, endpoint management tools have promised automation and flexibility. But IT and security teams still struggle with inconsistent outcomes, configuration risk, and dependence on individual heroics to keep the lights on. The real risk isn't the tool teams choose, it's choosing one without a tailored blueprint built in. Turnkey Results removes that risk by embedding operational best practices, proven across millions of endpoints under management, to drive predictable endpoint management outcomes from the get-go.
"Endpoint management has evolved, but the hardest problems never disappeared," said Justin Talerico, CEO of Automox. "Teams are still expected to figure out safe automation, rollout strategy, and operational cadence on their own. Turnkey Results upends that model by delivering a clear blueprint for success, tailored to each environment and continuously validated over time."
With Turnkey Results, IT and Security teams get a tailored blueprint designed specifically for their environment, aligning policies, configurations, and operational cadence to meet unique infrastructure needs. Customers choose whether to implement the blueprint themselves or have Automox experts do it; the cost is the same, either way. With ongoing monthly alignment, Automox validates the blueprint, surfaces drift before it becomes a problem, and supports fast remediation. As an organization's goals change, Automox adjusts the blueprint to align accordingly.
Instead of relying on trial and error, Turnkey Results gives organizations a clear plan. By shifting operational knowledge from individual administrators' heads to a durable, repeatable blueprint, outcomes no longer depend on who configured the tool or how much time they had to get it right.
"Buying endpoint management has traditionally meant buying software and owning all the risk of making it work (and keeping it working)," added Jason Kikta, CTO of Automox. "Turnkey Results de-risks that decision by ensuring the platform delivers desired outcomes, from day one."
Turnkey Results is available immediately to IT and security teams worldwide. Additional details are available
The Latest
AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...
Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...
Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...
When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...
In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...
Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...
AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...
Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...
For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...
Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...