Streaming IoT Data—From Boats to Dashboards
A Databricks customer pipes telemetry from hundreds of marine sensors into LakeFlow. They needed more than raw dashboards—they wanted automated context: "Which boats show abnormal fuel flow?" "Which route has the highest vibration risk right now?" PipeIQ's agents continuously watch the streams, score anomalies, and surface human‑readable alerts in seconds.
Agentic Processing Pipeline
1. Ingest & Parse
LakeFlow ingests streaming data (JSON, Avro, Parquet). Our schema‑aware listener agent tags columns—temperature, RPM, GPS—and enriches with metadata (device ID, geo).
2. Real‑Time Agents
Supervisor Agent delegates to specialised children: anomaly detection, trend summariser, predictive maintenance. Each outputs JSON findings to a Delta stream.
3. Action & Visualise
Findings flow to Databricks SQL dashboards, Slack alerts, and webhooks for OT systems— all within seconds of data arrival.
Key Capabilities
- ⚡Millisecond‑latency anomaly scoring
- ⚡LLM summarisation every time window
- ⚡Edge‑ready webhooks & MQTT triggers
- ⚡Auto‑generated Delta Live Tables for audit
- ⚡Integration with Databricks SQL & Lakehouse Monitoring
- ⚡Row‑level security on live streams
- ⚡Pluggable models for industry‑specific KPIs
- ⚡Runs 100 % in your workspace—no data egress
Reference Architecture
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Stream Smarter with Agents
Book a 30‑minute session to see how PipeIQ turns raw LakeFlow streams into actionable insights—before dashboards even refresh.
