T7 Solution builds high-volume sensor data pipelines — MQTT/HTTP/OPC-UA ingestion, TimescaleDB/InfluxDB historian, streaming analytics and ML feature stores for IoT.
Sensor data grows fast and gets expensive faster. Naive time-series storage bankrupts IoT projects long before the ML model ships.
We build ingestion and historian pipelines tuned for cost: hot/warm/cold tiers, downsampling, retention policies and columnar storage for analytics.
Streaming analytics (Kafka, Flink, or lightweight alternatives) handle anomaly detection, aggregation and alerting — with ML feature stores for downstream models.
MQTT, HTTP, OPC-UA, Modbus, CAN — normalised into one canonical event schema.
TimescaleDB, InfluxDB or ClickHouse with per-tag retention and continuous aggregates.
1s → 10s → 1m → 1h automatic rollups with per-tag policies to keep cost sane.
Anomaly detection, thresholding, windowed aggregations and alert emission on the stream.
Reusable ML features for predictive maintenance, quality and yield models.
Gaps, spikes, stuck-at-value and clock-drift detection with quarantine flows.
Hot/warm/cold tiers, columnar storage and retention per tag — not one bucket that eats the budget.
Windowed aggregates and anomaly detection on the stream — alerts fire in seconds, not minutes.
Stuck sensors, missing gateways and clock drift caught at the pipeline — not by the ML model six months later.
Feature store, backfill and point-in-time correctness so ML models get consistent data.
Production AI modules we drop into your sensor data pipelines build.
Production ML for forecasting, churn, risk and pricing — trained on your data.
AI-native automation that reads, decides and acts across your systems.
Multi-agent architectures that plan, use tools and complete complex tasks.
Custom vision models for quality control, retail analytics, medical imaging and more.
Comfortably millions of events per second per cluster with the right broker (EMQX/Kafka) and historian (Timescale/ClickHouse) choices.
Downsampling per tag, tiered storage (hot/warm/cold), columnar analytics store and configurable retention per data class.
Yes — OPC-UA, Modbus and vendor SCADA (Wonderware, Ignition) integration is standard.
Yes — filtering, aggregation and ML inference at the edge (Linux gateway or dedicated device) with cloud sync.
Talk to a senior AI consultant from T7 about your industry, workflow, or product idea. Free, no commitment — reply within one business day.
Compare the other IoT modules or explore where IoT meets AI.
Real-time device, fleet and site dashboards with drill-down and alerts
Provisioning, health, OTA updates and remote control for connected devices at scale
PLC/SCADA integration, MES modules, machine data and control workflows
SKU-level forecasts that release working capital, not just improve MAPE.
Sub-second defect detection on the line — with a governance trail.