Brimit helpt organisaties het potentieel van data en AI te benutten door oplossingen te leveren die operaties verbeteren, kosten verlagen en resultaten verbeteren—brancheoverschrijdend en over alle bedrijfsfuncties heen.
Brimit helpt organisaties het potentieel van data en AI te benutten door oplossingen te leveren die operaties verbeteren, kosten verlagen en resultaten verbeteren—brancheoverschrijdend en over alle bedrijfsfuncties heen.
WHAT WE DO
Comparing real-time, near-real-time, and batch scenarios by business process, response window, risk level, data volume, cost, and required user action. This determines where investment in speed is justified and where it isn't—before any architecture is designed.
Designing event sources, ingestion, processing, storage, and delivery layers. Technology patterns are selected for the client's environment and latency requirements—MQTT, Kafka, Azure Event Hubs, Azure IoT Hub, Fabric Eventstream, Real-Time Intelligence, Eventhouse, KQL, and custom APIs where appropriate.
Building the dashboards, alerts, thresholds, anomaly detection, escalation paths, notifications, and workflow triggers that connect live signals to action. A production event can create a maintenance task, notify an operator, update a dashboard, and feed root-cause analysis—without manual intervention at each step.
Real-time systems need data quality checks, access rules, observability, cost monitoring, failure handling, and clear support ownership. Built in from the start so teams know when data is fresh, when a stream is delayed, and who responds when something fails.
Starting with one line, asset group, process, site, or business domain. The pilot defines source systems, latency requirements, alert logic, user actions, success metrics, and scale criteria—with a working proof before broader rollout.
