Turning network tools into digital assets
capturing expertise, enabling automation,
and driving network competitiveness.
b.lo framework for
Strategic Network Performance
b.lo turns operational know-how
into high-value digital assets that power network excellence
and long-term differentiation.
Networks are entering a new era of agility and intelligence.
Networks are entering a new era of agility driven by the virtualization of network functions (NFV), and hybrid cloud-edge architectures, infrastructure is becoming more adaptable, responsive, and aligned with the specific needs of each service. This shift enables rapid deployment of new capabilities and fully automated network management through infrastructure as code and zero-touch orchestration.and intelligence.
b.lo, by living·objects, redefines NPM
Leveraging centralized data and increasingly open vendor interfaces, b.lo moves beyond passive monitoring. It actively interacts with systems to boost autonomy, optimize resource allocation, and enhance security-ushering in a smarter, more proactive approach to network performance.
Routine does not have to mean manual
Many network performance monitoring and fault analysis tasks follow predictable, low-variability patterns that rarely require deep investigation. This consistency makes them ideal candidates for automation. By embedding these processes into intelligent workflows, teams can streamline operations, reduce human error, and refocus their efforts on high-value, complex cases.
b.lo combines industry standards and ML to automate network performance routines
By leveraging BPMN (Business Process Model and Notation) as a recognized industry standard, b.lo structures recurring network monitoring and fault detection workflows into clear, modular processes. b.lo integrates Machine Learning agents that learn from historical data and system dynamics, enhancing workflows with intelligent, adaptive analysis patterns.
b.lo embeds an event engine based on
BPMN 2.0 standard to help Network Engineer
automate operational process or analysys.
b.lo brings ML Ops to telecom engineers
enabling use case ownership,
algorithm selection, and seamless deployment.
LLM and ML: The future pillars of network performance management
As networks grow in complexity, due a wide range of new digital service fulfilment options, traditional monitoring tools struggle to keep pace with dynamic environments. Large Language Models (LLMs) and Machine Learning (ML) are emerging as essential technologies to transform how performance is tracked, analyzed, and optimized. ML algorithms can detect patterns, predict anomalies with increasing precision. Meanwhile, LLMs bring a new layer of intelligence by interpreting logs, generating insights, and assisting operators through natural language interfaces.
Empowering telecom engineering teams with intelligent automation
By integrating LLMs and ML into its core, b.lo transforms how telecom engineering teams operate. These technologies don’t replace expertise-they amplify it. b.lo captures recurring diagnostic patterns, interprets complex data flows, and translates them into actionable insights in real time. Engineers gain a virtual assistant capable of accelerating root cause analysis, automating routine tasks, and surfacing hidden performance issues.
Combining network-centric
and service-centric approch
The network-centric approach enables reactive intervention based on equipment alarms and proactive analysis via performance counters. In parallel, the service-centric approach captures the customer’s perspective-leveraging direct feedback (complaints, satisfaction surveys) and synthetic monitoring tools that simulate user experience. When service and network performance are disconnected and difficult to correlate, the root cause analysis capability is, at best, to be a manual process.
