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ServiceNow Acquires FriendlyData

ServiceNow has agreed to acquire the technology of FriendlyData, which makes it easy for non‑technical users to ask quantitative questions in plain English and get fast results through direct answers or data visualizations.

FriendlyData’s natural language query (NLQ) technology will help reduce the amount of time spent figuring out how to ask questions technically; rather, it allows users to just ask a question, and then use the freed up time to act on the answer. NLQ technology will be embedded into the interfaces of the Now Platform and guide users to relevant and related Performance Analytics dashboards and reporting.

When used in the Now Platform, the technology will reduce some of the complexity that slows down work, including:

- Outdated customer and employee work experiences that are not intuitive and easy to use like the ones people experience as consumers.

- Inability to act due to reliance on time‑consuming manual processes.

- Burdens on business analysts and data engineers who can’t keep pace with the increasing volume of requests coming from non‑technical users within their company.

“ServiceNow is bringing NLQ capabilities to the Now Platform, enabling companies to ask technical questions in plain English and receive direct answers,” said Pat Casey, SVP, Development and Operations at ServiceNow. “With this technical enhancement, our goal is to allow anyone to easily make data driven decisions, increasing productivity and driving businesses forward faster.”

ServiceNow plans to re‑platform FriendlyData’s NLQ technology, extending the Now Platform’s intelligence capabilities by making NLQ interfaces available across ServiceNow applications for IT, Human Resources, Security Operations, Customer Service Management, partner products and for developers.

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ServiceNow Acquires FriendlyData

ServiceNow has agreed to acquire the technology of FriendlyData, which makes it easy for non‑technical users to ask quantitative questions in plain English and get fast results through direct answers or data visualizations.

FriendlyData’s natural language query (NLQ) technology will help reduce the amount of time spent figuring out how to ask questions technically; rather, it allows users to just ask a question, and then use the freed up time to act on the answer. NLQ technology will be embedded into the interfaces of the Now Platform and guide users to relevant and related Performance Analytics dashboards and reporting.

When used in the Now Platform, the technology will reduce some of the complexity that slows down work, including:

- Outdated customer and employee work experiences that are not intuitive and easy to use like the ones people experience as consumers.

- Inability to act due to reliance on time‑consuming manual processes.

- Burdens on business analysts and data engineers who can’t keep pace with the increasing volume of requests coming from non‑technical users within their company.

“ServiceNow is bringing NLQ capabilities to the Now Platform, enabling companies to ask technical questions in plain English and receive direct answers,” said Pat Casey, SVP, Development and Operations at ServiceNow. “With this technical enhancement, our goal is to allow anyone to easily make data driven decisions, increasing productivity and driving businesses forward faster.”

ServiceNow plans to re‑platform FriendlyData’s NLQ technology, extending the Now Platform’s intelligence capabilities by making NLQ interfaces available across ServiceNow applications for IT, Human Resources, Security Operations, Customer Service Management, partner products and for developers.

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...