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Nastel Introduces Comprehensive Mobile Data Analysis Platform

Nastel Technologies announced AutoPilot Mobile, its next-generation set of mobile-centric analysis tools available as part of its flagship AutoPilot Insight software platform.

New streaming data and real-time tracking features, combined with extensive forensic diagnostics, provide the broad array of capabilities needed by users ranging from developers and IT admins to telecom managers and business analysts.

Charley Rich, Nastel’s VP-Product Management, stated: “We all know about the huge role mobile technology is playing in the digital transformation sweeping through today’s enterprises. With mobile now the preferred interface for customer-facing business applications, fast deployment of high-quality apps is the name of the game. Nastel provides complete situational awareness of user behaviors, performance, and the data transactions between mobile apps and the back-end infrastructure supporting them.”

Rich continued: “Our flexible open source APIs and analytics-as-a-service model enables developers to build, test, and deploy custom mobile apps much faster—with precision performance and crash analysis available to quickly address any problems as they arise. IT admins benefit from better monitoring of app resource consumption and other important metrics. Telecom managers gain exact knowledge of device service costs, reliability, and performance across multiple carriers, which is critical for determining SLA adherence and negotiating favorable contract terms with service providers. Lastly, business analysts eliminate guesswork when optimizing user interaction pathways and behaviors because they can understand individual and aggregated behaviors, and track mobile transactions at a fundamental IT level, stitching them to back-end server and database event activities.”

On a technical level, Rich said Nastel’s commitment to the open source paradigm is reflected in the availability of both its streaming data and real-time tracking APIs as GitHub projects. Both leverage the open-source dependency manager called Cocoapods to help developers easily scale their application projects.

“Enterprise organizations,” Rich continued, “now have an easy means of streaming data from mobile applications to AutoPilot Insight for analysis. Customer applications can stream data, submit interactive queries, and subscribe to real-time analytics. Our RESTful API, available on GitHub, can be used with any iOS-based application using Objective C or Swift. Other technical users can leverage Nastel’s built-in natural query language, jKQL, to easily ask questions, subscribe to answers, and extract actionable intelligence from app data streams. Business users can use AutoPilot Insight to enrich data acquired from their custom mobile apps with data from other sources for additional business perspectives. This API can even be employed as a means to store application data without setting up a database solution.”

The second API, available on GitHub, provides real-time tracking of user interactions within any custom iOS mobile app. Mobile app developers can use this API to provide analytics to their applications. Added to an app in minutes, this API transmits user actions, touch events, navigation paths, locations, and timings to AutoPilot Insight. App crash data can be streamed as well. This adds in-depth, real user monitoring and tracking for any custom application native to iOS.

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Nastel Introduces Comprehensive Mobile Data Analysis Platform

Nastel Technologies announced AutoPilot Mobile, its next-generation set of mobile-centric analysis tools available as part of its flagship AutoPilot Insight software platform.

New streaming data and real-time tracking features, combined with extensive forensic diagnostics, provide the broad array of capabilities needed by users ranging from developers and IT admins to telecom managers and business analysts.

Charley Rich, Nastel’s VP-Product Management, stated: “We all know about the huge role mobile technology is playing in the digital transformation sweeping through today’s enterprises. With mobile now the preferred interface for customer-facing business applications, fast deployment of high-quality apps is the name of the game. Nastel provides complete situational awareness of user behaviors, performance, and the data transactions between mobile apps and the back-end infrastructure supporting them.”

Rich continued: “Our flexible open source APIs and analytics-as-a-service model enables developers to build, test, and deploy custom mobile apps much faster—with precision performance and crash analysis available to quickly address any problems as they arise. IT admins benefit from better monitoring of app resource consumption and other important metrics. Telecom managers gain exact knowledge of device service costs, reliability, and performance across multiple carriers, which is critical for determining SLA adherence and negotiating favorable contract terms with service providers. Lastly, business analysts eliminate guesswork when optimizing user interaction pathways and behaviors because they can understand individual and aggregated behaviors, and track mobile transactions at a fundamental IT level, stitching them to back-end server and database event activities.”

On a technical level, Rich said Nastel’s commitment to the open source paradigm is reflected in the availability of both its streaming data and real-time tracking APIs as GitHub projects. Both leverage the open-source dependency manager called Cocoapods to help developers easily scale their application projects.

“Enterprise organizations,” Rich continued, “now have an easy means of streaming data from mobile applications to AutoPilot Insight for analysis. Customer applications can stream data, submit interactive queries, and subscribe to real-time analytics. Our RESTful API, available on GitHub, can be used with any iOS-based application using Objective C or Swift. Other technical users can leverage Nastel’s built-in natural query language, jKQL, to easily ask questions, subscribe to answers, and extract actionable intelligence from app data streams. Business users can use AutoPilot Insight to enrich data acquired from their custom mobile apps with data from other sources for additional business perspectives. This API can even be employed as a means to store application data without setting up a database solution.”

The second API, available on GitHub, provides real-time tracking of user interactions within any custom iOS mobile app. Mobile app developers can use this API to provide analytics to their applications. Added to an app in minutes, this API transmits user actions, touch events, navigation paths, locations, and timings to AutoPilot Insight. App crash data can be streamed as well. This adds in-depth, real user monitoring and tracking for any custom application native to iOS.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

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In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...