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Sub-second data freshness for fraud, anomaly, and real-time AI use cases.

Stream Bridge

Provisions and manages Kafka/Kinesis streaming infrastructure that delivers real-time data to online feature stores, streaming ML pipelines, and LLM context enrichment pipelines with guaranteed delivery. Critical for fraud detection, real-time network performance management, and live patient monitoring use cases requiring sub-second data freshness.

Why It Matters

Stream Bridge provides the real-time nervous system that every sub-second AI use case depends on – managed streaming infrastructure with the delivery guarantees that fraud detection, network management, and patient monitoring cannot function without.
It handles the operational reality of Kafka at enterprise scale so client teams don’t have to become streaming experts.
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Guaranteed delivery, not best-effort

For fraud and patient monitoring, a dropped event is a missed incident - managed delivery guarantees, backpressure handling, and consumer monitoring make streaming dependable enough for life-and-money use cases.

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Kafka expertise is scarce and expensive

Enterprise streaming infrastructure fails in subtle, operational ways - schema registry management and consumer group monitoring solve problems most in-house teams discover only in production.

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Supports all real-time AI workloads

Online feature stores, streaming pipelines, and LLM context enrichment all consume from the same backbone - one streaming layer powering the entire real-time AI portfolio.

The Cloudly Advantage

StreamBridge is the infrastructure floor beneath Cloudly’s real-time story — StreamPrep engineers features on it, FeatureVault serves from it, DriftShield and AnomalyRadar consume events over it.
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Cluster Services flagship workload

Kafka cluster design, tuning, and 24/7 operations is precisely what our Cluster Services consultancy exists to sell — every deployment is a substantial build-plus-operate engagement.

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The real-time foundation deal

Fraud, network, and monitoring use cases all start with "get the events flowing" — StreamBridge lands first, then StreamPrep, FeatureVault, and the platform follow on the rails it lays.

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Bundles with StreamPrep naturally

Infrastructure (StreamBridge) plus feature engineering (StreamPrep) is one real-time architecture conversation — sold together, a complete streaming ML stack.

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Kinesis and Pub/Sub pull-through

Managed AWS Kinesis and GCP Pub/Sub deployments open cloud migration and monitoring engagements across both hyperscaler footprints.

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Mission-critical operational stickiness

Once fraud decisions and patient alerts flow through our streaming layer, it's unremovable infrastructure — anchoring long-term managed-operations contracts.

The Final Takeaway

LLM context enrichment angle — Real-time data feeding RAG and agent pipelines connects streaming to the GenAI stack — a modern angle that keeps infrastructure conversations tied to board-level AI interest.

Powered By

Apache Kafka

Core to the StreamBridge technology stack.

AWS Kinesis

Core to the StreamBridge technology stack.

GCP Pub/Sub

Core to the StreamBridge technology stack.

Confluent Schema Registry

Core to the StreamBridge technology stack.

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