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What the AI platforms say after searching the web.
Dynatrace
Mention Share % (latest day)
0.52% -0.27 pp ▼
0.52% -0.27 pp ▼
Mentions (latest day)
1
1
Total Mentions
85
85
Avg Rank (latest day)
5.0
5.0
Latest tracking day
2026-09-29
2026-09-29
dynatrace.com · google unverified
Daily Mentions Trendⓘ
Average Rankⓘ
By Platformⓘ
| Platform | Dynatrace | Algoroo | Δ mentions |
|---|---|---|---|
| 31 rank 7.26 | 94 rank 6.64 | +63 | |
| OpenAI | 31 rank 5.81 | 92 rank 6.87 | +61 |
| Anthropic | 0 | 4 rank 4.5 | +4 |
Daily Citations Trendⓘ
Citation Shareⓘ
| Dynatrace | Algoroo | Δ | |
|---|---|---|---|
| Citations | 8 | 14 | +6 |
| Citation share | 0.1% | 0.2% | — |
| Blended Share of Voice | 0.3% | 1.1% | +0.8 |
Of 6,706 selected citations, all-time. Δ is Algoroo minus Dynatrace (green means your owned brand leads); bars show citations by platform.
Recent Mentionsⓘ
| Date | Platform | Mentioned For | Rank | Sentiment | Context |
|---|---|---|---|---|---|
| 2026-09-29 | Algorithm monitoring | 5 | — | Dynatrace An enterprise observability platform featuring automated root-cause analysis and end-to-end tracing for AI pipelines, ensuring algorithms stay performant, accurate, and cost-effective across complex cloud architectures. | |
| 2026-07-07 | OpenAI | Algorithm monitoring | 5 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection and root-cause analysis across complex systems. |
| 2026-07-06 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace Enterprise-grade observability platform for monitoring complex software systems, anomalies, dependencies, and AI-assisted root-cause analysis. |
| 2026-07-02 | OpenAI | Algorithm monitoring | 7 | — | Dynatrace Enterprise-grade observability with AI-assisted anomaly detection and root-cause analysis across complex distributed systems. |
| 2026-07-01 | OpenAI | Algorithm monitoring | 5 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection and root-cause analysis across complex systems. |
| 2026-06-30 | OpenAI | Algorithm monitoring | 2 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection, useful for monitoring algorithm behavior across complex software environments. |
| 2026-06-29 | OpenAI | Algorithm monitoring | 4 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection and root-cause analysis across complex systems. |
| 2026-06-28 | OpenAI | Algorithm monitoring | 2 | — | Dynatrace Good for enterprise algorithm monitoring where automated root-cause analysis, dependency mapping, and AI-assisted incident detection matter. |
| 2026-06-27 | OpenAI | Algorithm monitoring | 3 | — | Dynatrace Best fit for large enterprises that need automated anomaly detection, root-cause analysis, and full-stack observability across complex systems. |
| 2026-06-26 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection, root-cause analysis, and full-stack monitoring. |
| 2026-06-26 | Algorithm monitoring | 6 | — | Dynatrace An enterprise-grade monitoring solution that provides full-stack observability, leveraging its Davis AI engine to continuously analyze model metrics, track performance trends, and detect anomalies in algorithmic systems. | |
| 2026-06-25 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace Useful for AIOps-style monitoring, anomaly detection, and performance monitoring across complex software systems. |
| 2026-06-24 | OpenAI | Algorithm monitoring | 7 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection and root-cause analysis across complex systems. |
| 2026-06-23 | OpenAI | Algorithm monitoring | 2 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection, root-cause analysis, and full-stack monitoring. |
| 2026-06-22 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace Enterprise-focused observability platform with AI-powered anomaly detection, root-cause analysis, and full-stack monitoring. |
| 2026-06-18 | OpenAI | Algorithm monitoring | 3 | — | Dynatrace Enterprise-oriented monitoring platform with AI-assisted root-cause analysis, useful when “algorithm monitoring” means detecting anomalies across complex systems. |
| 2026-06-14 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace Enterprise-grade observability platform with AI-assisted anomaly detection and root-cause analysis across complex systems. |
| 2026-06-13 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace Strong for enterprises that want full-stack observability with AI-assisted anomaly detection and root-cause analysis. It is more of a broad observability platform than a pure ML-monitoring tool, but it can be relevant when algorithms are embedded in complex production applications. |
| 2026-06-12 | OpenAI | Algorithm monitoring | 12 | — | Dynatrace A good enterprise observability platform for organizations that want automated anomaly detection, root-cause analysis, application monitoring, infrastructure visibility, and AI-assisted operations. It is strongest when algorithm monitoring is part of a much larger enterprise software environment. |
| 2026-06-11 | Algorithm monitoring | 8 | — | Dynatrace An AI-powered observability platform that provides deep insights into application performance and algorithmic workflows. It automatically discovers, maps, and monitors complex microservices and the algorithms running within them. | |
| 2026-06-10 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace A strong enterprise choice for monitoring AI applications, LLMs, agentic workflows, infrastructure, cost, performance, and business impact in one observability environment. Dynatrace highlights AI and LLM observability across application, model, and infrastructure layers. (dynatrace.com) |
| 2026-06-10 | Algorithm monitoring | 8 | — | Dynatrace An enterprise observability platform that provides full-stack monitoring, including specialized AI observability to track the performance, cost, and compliance of complex algorithms and AI agents. | |
| 2026-06-09 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace A strong enterprise observability choice when algorithm performance is only one part of a larger production system. Dynatrace is known for full-stack monitoring, AIOps, application performance monitoring, infrastructure visibility, and AI-assisted root-cause analysis, which can help correlate model issues with system-level problems. (techradar.com) |
| 2026-06-09 | Algorithm monitoring | 3 | — | Dynatrace This enterprise-grade platform leverages automated AI to monitor application performance and provide deep observability into generative AI models, tracking metrics, logs, and potential hallucinations in real time. | |
| 2026-06-08 | Algorithm monitoring | 5 | — | Dynatrace An AI-powered observability platform that provides deep, full-stack monitoring for complex algorithmic systems, microservices, and generative AI agents to track latency, token usage, and system health. | |
| 2026-06-07 | OpenAI | Algorithm monitoring | 7 | — | Dynatrace Strong for enterprise environments where algorithm monitoring needs to sit inside a broader AIOps, cloud observability, application monitoring, and automated root-cause analysis platform. |
| 2026-06-07 | Algorithm monitoring | 8 | — | Dynatrace This platform leverages advanced AI and automation to monitor complex, distributed cloud environments. It is ideal for organizations that need to monitor the performance of algorithms and microservices at scale, offering automated root-cause analysis when performance anomalies occur. | |
| 2026-06-06 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace A strong enterprise observability platform for monitoring complex software environments, with AI-powered anomaly detection, application performance monitoring, infrastructure visibility, and growing AI observability capabilities. |
| 2026-06-06 | Algorithm monitoring | 8 | — | Dynatrace An industry leader in application performance monitoring that utilizes advanced AI to automate root-cause analysis. It continuously monitors the underlying infrastructure and software performance of deployed algorithms to ensure maximum uptime and efficiency. | |
| 2026-06-05 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace A strong enterprise observability platform for organizations that want algorithm monitoring connected to application performance, infrastructure, user experience, root-cause analysis, and AIOps. It is especially relevant when AI systems are embedded inside complex distributed applications. |
| 2026-06-05 | Algorithm monitoring | 10 | — | Dynatrace An AI-powered observability platform that automates root-cause analysis and performance monitoring for complex, distributed software architectures, including the microservices and APIs hosting your machine learning algorithms. | |
| 2026-06-04 | OpenAI | Algorithm monitoring | 7 | — | Dynatrace A fit for enterprise teams that want AI/algorithm monitoring as part of a larger AIOps and observability strategy. Dynatrace is relevant for monitoring complex systems where algorithmic behavior, application performance, infrastructure signals, and automated root-cause analysis need to work together. (ekagpt.com) |
| 2026-06-03 | OpenAI | Algorithm monitoring | 6 | — | Dynatrace Well suited for enterprise algorithm monitoring where AI systems are part of a larger software stack. It combines observability, AIOps, infrastructure monitoring, application performance monitoring, anomaly detection, and root-cause analysis. |
| 2026-06-03 | Algorithm monitoring | 10 | — | Dynatrace An AI-powered observability platform that delivers automated monitoring for complex, distributed applications, including the underlying algorithms and microservices that power them. | |
| 2026-06-02 | Algorithm monitoring | 7 | — | Dynatrace Leveraging advanced AI-driven automation, this platform offers full-stack observability and automated root-cause analysis to monitor the performance and health of complex software algorithms. | |
| 2026-06-01 | Algorithm monitoring | 8 | — | Dynatrace Powered by its Davis AI engine, this platform provides full-stack observability with automated root-cause analysis. It is ideal for monitoring complex, dynamic cloud environments and tracking the infrastructure supporting large-scale algorithmic workloads. | |
| 2026-05-31 | OpenAI | Algorithm monitoring | 8 | — | Dynatrace Best suited for enterprises that want algorithm, application, and infrastructure monitoring in one observability platform, with automated dependency mapping, anomaly detection, and root-cause analysis. |
| 2026-05-30 | Algorithm monitoring | 6 | — | Dynatrace This platform leverages automated, causal AI to monitor application performance and cloud infrastructure, making it highly effective for tracking the underlying systems that run complex algorithms. | |
| 2026-05-29 | OpenAI | Algorithm monitoring | 8 | — | Dynatrace A strong enterprise observability brand for monitoring complex software environments where algorithms run inside distributed applications, with automated anomaly detection and root-cause analysis. |
| 2026-05-29 | Algorithm monitoring | 6 | — | Dynatrace An AI-powered observability platform that provides deep monitoring for complex software ecosystems, including the performance, health, and execution of automated algorithms and microservices. | |
| 2026-05-28 | OpenAI | Algorithm monitoring | 7 | — | Dynatrace A strong enterprise observability platform for monitoring complex software and AI-enabled applications, with automated dependency mapping, anomaly detection, root-cause analysis, and full-stack performance visibility. |
| 2026-05-28 | Algorithm monitoring | 7 | — | Dynatrace An AI-powered observability platform that utilizes its proprietary Davis AI engine to automatically baseline system performance. It is highly effective for monitoring the underlying infrastructure, microservices, and API endpoints that host and run complex algorithms. | |
| 2026-05-27 | OpenAI | Algorithm monitoring | 3 | — | Dynatrace A good enterprise-grade option for full-stack observability with AI-assisted anomaly detection and root-cause analysis. It fits organizations monitoring algorithms as part of complex applications, distributed systems, or business-critical digital services. |
| 2026-05-25 | Algorithm monitoring | 7 | — | Dynatrace Leveraging advanced AI and automation, this platform monitors complex software architectures, including the performance and dependencies of underlying algorithms and microservices. | |
| 2026-05-24 | OpenAI | Algorithm monitoring | 8 | — | Dynatrace Suitable for organizations that want AI-powered full-stack observability, combining application performance monitoring, infrastructure monitoring, anomaly detection, and root-cause analysis across complex systems. |
| 2026-05-24 | Algorithm monitoring | 6 | — | Dynatrace Leveraging its powerful, proprietary AI engine, this platform automates root-cause analysis and provides comprehensive end-to-end AI and LLM observability. It is designed for enterprise-scale environments, helping teams monitor the performance, cost, and compliance of their production algorithms. | |
| 2026-05-22 | OpenAI | Algorithm monitoring | 8 | — | Dynatrace Enterprise-grade observability platform with strengths in AI-powered anomaly detection, application performance monitoring, infrastructure monitoring, and root-cause analysis. Consider it if you need algorithm monitoring alongside full-stack production system monitoring. |
| 2026-05-22 | Algorithm monitoring | 6 | — | Dynatrace Known for its advanced AI-driven observability, this platform automates the monitoring of microservices and algorithms, using its proprietary causal AI to pinpoint the root causes of performance degradation. | |
| 2026-05-21 | Algorithm monitoring | 9 | — | Dynatrace This enterprise-grade software intelligence platform utilizes advanced AI-driven analytics to monitor application performance, infrastructure, and the underlying algorithms driving modern digital services. | |
| 2026-05-20 | Algorithm monitoring | 8 | — | Dynatrace An AI-powered observability platform that automates root-cause analysis and provides deep monitoring for complex microservices, cloud infrastructure, and generative AI applications. |