AdRem NetCrunch
NetCrunch is a next-gen, agentless infrastructure and traffic network monitoring system designed for hybrid, multi-site, and fast changing infrastructures. It combines real-time observability with alert automation and intelligent escalation to eliminate the overhead and limitations of legacy tools like PRTG or SolarWinds. NetCrunch supports agentless monitoring of thousands of nodes from a single server-covering physical devices, virtual machines, servers, traffic flows, cloud services (AWS, Azure, GCP), SNMP, syslogs, Windows Events, IoT, telemetry, and more.
Unlike sensor-based tools, NetCrunch uses node-based licensing and policy-driven configuration to streamline monitoring, reduce costs, and eliminate sensor micromanagement. 670+ built-in monitoring packs apply instantly based on device type, ensuring consistency across the network.
NetCrunch delivers real-time, dynamic maps and dashboards that update without manual refreshes, giving users immediate visibility into issues and performance. Its smart alerting engine features root cause correlation, suppression, predictive triggers, and over 40 response actions including scripts, API calls, notifications, and integrations with Jira, Teams, Slack, Amazon SNS, MQTT, PagerDuty, and more.
Its powerful REST API makes NetCrunch perfect for flow automation, including integration with asset management, production/IoT/operations monitoring and other IT systems with ease.
Whether replacing an aging platform or modernizing enterprise observability, NetCrunch offers full-stack coverage with unmatched flexibility. Fast to deploy, simple to manage, and built to scale-NetCrunch is the smarter, faster, and future-ready monitoring system. Designed for on-prem (including air-gapped), cloud self-hosted or hybrid networks.
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TRACTIAN
Tractian is the Industrial Copilot for maintenance and reliability, combining hardware and software solutions to monitor asset performance, manage industrial operations, and implement predictive maintenance strategies. Its AI-driven platform empowers businesses to prevent unplanned equipment downtime and boost production output. The company is headquartered in Atlanta, GA, and extends its presence globally with offices in Mexico City and Sao Paulo. Learn more at tractian.com.
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Lumada IIoT
Implement sensors tailored for IoT applications and enhance the data collected by integrating it with environmental and control system information. This integration should occur in real-time with enterprise data, facilitating the deployment of predictive algorithms to uncover fresh insights and leverage your data for impactful purposes. Utilize advanced analytics to foresee maintenance issues, gain insights into asset usage, minimize defects, and fine-tune processes. Capitalize on the capabilities of connected devices to provide remote monitoring and diagnostic solutions. Furthermore, use IoT analytics to anticipate safety risks and ensure compliance with regulations, thereby decreasing workplace accidents. Lumada Data Integration allows for the swift creation and expansion of data pipelines, merging information from various sources, including data lakes, warehouses, and devices, while effectively managing data flows across diverse environments. By fostering ecosystems with clients and business associates in multiple sectors, we can hasten digital transformation, ultimately generating new value for society in the process. This collaborative approach not only enhances innovation but also leads to sustainable growth in an increasingly interconnected world.
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AWS IoT Analytics
The data generated by IoT devices is predominantly unstructured, posing challenges for analysis using conventional analytics and business intelligence tools that cater to structured data formats. This type of data is often derived from devices that capture inherently noisy processes like temperature, motion, or sound, leading to frequent occurrences of significant gaps, corrupted messages, and erroneous readings that necessitate cleansing prior to any analytical work. Moreover, the significance of IoT data frequently relies on supplementary inputs from third-party data sources. For instance, vineyard irrigation systems enhance moisture sensor readings with rainfall data, assisting farmers in making informed decisions on when to irrigate their crops, thereby optimizing water usage and boosting harvest yields. AWS IoT Analytics simplifies and automates the complex steps involved in analyzing data from IoT devices, making it easier for users to gain insights. This service is fully managed and operates on a pay-as-you-go model, ensuring automatic scaling to accommodate varying data volumes. Consequently, organizations can leverage AWS IoT Analytics to advance their operational efficiencies and make data-driven decisions with greater ease.
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