We connect events, devices, applications and screens so each operational change reaches the right people and systems with the speed and reliability the business requires.
Real time does not mean zero latency. It means changes propagate within a limit appropriate for the decision. A daily report may be enough for sales analysis, while a production incident, location or state change may require seconds or milliseconds. We define the requirement by impact, not by a technical label.
These systems provide value when people or machines must share a recent state and act in coordination.
We agree realistic response and availability objectives based on criticality. Queues, acknowledgements, retries, idempotency and event logs can prevent duplicate or lost operations. More demanding requirements need additional infrastructure, monitoring and cost.
We connect APIs, databases, message brokers, devices and existing applications. WebSockets, gRPC, MQTT or RabbitMQ may be used, but the choice depends on volume, network, source systems and required guarantees. We also define behavior when an external integration slows down or fails.
A real-time application must treat disconnection as a normal state. It shows whether data is current, preserves events where possible and resynchronizes on reconnection. Timestamps, identifiers and duplicate controls make it possible to reconstruct events without hiding gaps.
We measure simultaneous connections, message rate and size, peaks, retention and query patterns. We start with proportional architecture and load-test before expanding. The system is divided by function or flow when real volume justifies it, avoiding premature complexity.
We begin with a critical flow and a measurable latency objective. Cost and timing depend on integrations, simultaneous connections, event volume, retention, availability and recovery requirements. After the prototype, we test load and failure scenarios before planning expansion.
When delay prevents action, team coordination or incident detection: state changes, locations, alarms, production or devices. If information is only used for later analysis, periodic updates are usually simpler and less expensive.
A conventional dashboard generally polls at intervals or when refreshed. In a real-time system, the server pushes changes as they happen. Connections, event order, disconnections and resynchronization must also be handled.
Yes, when an API, database, broker, protocol or other reliable access is available. We define the authoritative source, update frequency and behavior when the external system is unavailable.
The interface indicates that data may be stale and attempts to reconnect. Depending on the case, devices or apps can store operations locally. On reconnection, versions or events are compared to rebuild a consistent state.
It depends on network, server location, volume, protocols and integrated systems. We define a measurable objective and validate it through testing. We do not promise a universal figure without knowing the complete data path.
We filter and aggregate events, prioritize actionable alerts and use queues to absorb peaks. Retention and resolution are set by use case because not every reading must reach every user or be stored at the same detail.
Yes, when designed and measured for growth. We test representative connections and events, monitor bottlenecks and scale processes, databases or brokers according to actual load.
With metrics for connections, latency, queues, errors, retries and resource use, plus correlated logs and operational alerts. Recovery procedures and accountable owners are also defined so each alert has a clear response.
Tell us what you want to improve and we will prepare a functional prototype with no obligation.
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