AdRem NetCrunch
NetCrunch is a powerful, scalable, all-in-one network monitoring system built for modern IT environments. It supports agentless monitoring of thousands of devices, covering SNMP, servers, virtualization (VMware, Hyper-V), cloud (AWS, Azure, GCP), traffic flows (NetFlow, sFlow), logs, and custom data via REST or scripts.
With 670+ monitoring packs and dynamic views, it automates discovery, configuration, alerting, and automates self-healing actions for efficient remote remediation in response to alerts. Its node-based licensing eliminates sensor sprawl and complexity, providing a clear, cost-effective path to scale.
Real-time dashboards, policy-driven setup, advanced alert tuning and 40+ alert actions including remote script execution, service restart, process kill or device reboot-make NetCrunch ideal for organizations replacing legacy tools like PRTG, SolarWinds, or WhatsUp Gold. Fast to deploy and future-proof.
Can be installed on prem, self hosted in the cloud, or mixed.
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Vertex AI
Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case.
Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.
Vertex AI Agent Builder enables developers to create and deploy enterprise-grade generative AI applications. It offers both no-code and code-first approaches, allowing users to build AI agents using natural language instructions or by leveraging frameworks like LangChain and LlamaIndex.
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PawSQL
PawSQL integrates the best practices of query optimization in database industry, provides advanced SQL rewrite optimization, and sophisticate index recommendation capabilities for slow queries. Based on the professional PawSQL optimization engine (used by more than 10,000 database practitioners around the world), it provides rich SQL optimization suggestions and intelligent index recommendations. PawSQL provides a comprehensive and balanced audit rule set for multiple databases such as MySQL, PostgreSQL, openGauss, Oracle, etc., providing enterprises with a consistent audit experience no matter how diverse their database environment is. Rule-based SQL review, covering potential correctness and performance optimization issues. Rich rewrite optimization, recommending semantically equivalent but more efficient SQL queries. Cost-based verification ensures that new solutions based on SQL rewrite and index recommendation have better performance. Intelligent index recommendation.
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