As mentioned earlier, we don’t promise “AI heaven” to our customers. Instead, we focus on building a robust data platform with 1Optic and creating value from there. Our approach is iterative. Step by step, we develop AI-powered capabilities that deliver measurable benefits to the domain experts using our solutions. The same philosophy applies to TripAiku. With more than 15 years of experience in rule-based monitoring and automation, we integrate AI carefully and pragmatically.
Current literature often suggests that machine learning and AI are essential for handling the vast amounts of data generated by modern mobile networks. It is frequently argued that traditional rule-based approaches do not scale. Our experience has been quite different: well-designed (in close collaboration with domain experts), rule-based triggers remain highly effective and can scale successfully to very large datasets. AI certainly enables advanced anomaly detection, but it comes at a significant cost. Large computational resources are required, inference costs can be substantial, and token consumption can quickly become (very) expensive.
In addition, network monitoring often involves company-confidential data (e.g. metrics, traffic volumes, availability scores). As a result, public AI services are typically not an option, adding further complexity to deployment and operations.
Another practical challenge is anomaly labeling. Detecting anomalies is one thing; classifying and labeling them correctly is often a labor-intensive process that requires significant expert involvement. Rule-based triggers offer a distinct advantage here: every detected anomaly is inherently labeled by the rule that generated it. Furthermore, in most cases, the cause of a rule-based trigger based alert is immediately clear. Whether the issue relates to interference, downtime, congestion, or another known condition, the trigger itself provides transparency and explainability; provided the rule logic is not too complex.
In summary, TripAiku delivers a comprehensive set of turnkey rule-based triggers for online and offline network monitoring today, while we continue to explore and evaluate where AI-driven anomaly detection can provide genuine additional value. Interested in learning more? We’d be happy to discuss your use case. We also offer Proof of Concept (PoC) projects. Just get in touch.
This text was reviewed and refined with AI assistance to improve readability and presentation.