IOT + AI INTEGRATION
Sensor networks, edge intelligence, and cloud analytics — built on our long-standing IoT implementation experience.
Engagement
Overview
We connect devices, gateways, and cloud platforms so telemetry flows into models that detect anomalies, predict failures, and trigger actions. From factory floors to fleet operations, we deliver end-to-end IoT + AI systems.
What we build
Sensor & device integration
Edge inference
Stream processing
01 · Scope
We connect devices, gateways, and cloud platforms so telemetry flows into models that detect anomalies, predict failures, and trigger actions. From factory floors to fleet operations, we deliver end-to-end IoT + AI systems.
Sensor & device integration
Ingest data from PLCs, MQTT devices, BLE tags, and industrial protocols.
Edge inference
Run lightweight models on gateways for low-latency decisions when cloud round-trips are too slow.
Stream processing
Aggregate, window, and enrich high-volume telemetry before it hits storage or ML pipelines.
Digital twin views
Visualize asset health, thresholds, and historical trends in operator-friendly dashboards.
Typical stack
02 · System blueprint
A production path from the current process to a workflow your team can operate.
01
Define sensors, sampling rates, and connectivity for each site or fleet.
02
Secure ingestion, normalization, and time-series storage.
03
Train detection models and set alert rules aligned with operational thresholds.
04
Trigger work orders, notifications, or control signals when conditions are met.
03 · Impact
The problem
Assets are connected, but telemetry never becomes a decision — operators still find issues by walking the floor.
The solution we install
Sensors, edge inference, and cloud analytics that detect, predict, and trigger action in the systems you already run.
Movement we target
Detection
Found on walkaroundFlagged from the stream
Response
Manual ticket after the factTriggered work order
Latency
Batch export overnightOn-site or near-real-time
04 · Use cases
Monitor lines for quality drift, vibration, and energy anomalies.
05 · Methodology
Four phases from discovery to kaizen — scoped to your systems, not a generic week-count.
Map the problem and the state of your data.
A small proof-of-concept validates real value.
Integrated into your existing systems, into production.
Continuous improvement, guided by real operating data.
06 · Frequently asked
A short discovery conversation is enough to map the problem, the systems involved, and whether a pilot or a fuller build is the right first step.
Yes. We integrate into ERP, CRM, and internal apps you already operate — the point is a workflow your team keeps, not a disconnected demo.
Yes. Consulting, coordination, and handover run in Japanese and English.
The production workflow, the integration points, and the operating view your team uses day to day — with documentation and a kaizen path after go-live.