We build the real-time SIEM pipelines, network telemetry infrastructure, and agentic operations layers that make telecommunications networks more observable, more secure, and more autonomous. Deployed in production at T-Mobile scale.
Telecommunications networks generate operational and security telemetry at a scale that most AI vendors are not equipped to handle. The volume is orders of magnitude beyond typical enterprise SIEM. Detection latency requirements are sub-second. The consequence of false negatives is regulatory exposure or customer impact at scale. And the infrastructure is complex enough that AI solutions that work in a data center don't necessarily transfer.
The teams that get this right have invested in distributed streaming architectures, telemetry normalization across heterogeneous network equipment, and detection logic that can scale horizontally without false positive explosion.
Distributed pipelines processing high-volume security and operational events with sub-second latency. Built on Kafka and Flink/Spark Streaming. Detection logic designed for telco event volumes. Improved mean-time-to-detect, reduced false positive rates. Deployed in production at T-Mobile — see the full SIEM pipeline architecture.
Real-time ingestion from heterogeneous network equipment — routers, switches, RAN components, core network elements. Schema normalization and enrichment. Queryable telemetry layer that feeds detection, analytics, and operations tooling.
Reasoning layers that interpret network state, follow operational runbooks, execute safe remediation via tool use, and escalate to NOC teams with full context. The architecture that operations and compliance teams can trust.
DehazeLabs' team's expertise in building, deploying, and managing AI agents revolutionized our network optimization and elevated customer service efficiency.
Tell us about your network operations environment — event volume, current SIEM stack, detection latency targets, and where the pain is. We'll tell you what we'd build.