In most device programs, failures rarely come from the sensor. They arise from onboarding, updates, or telemetry gaps. Solving those foundational layers first leads to faster shipping, safer pilots, and fewer field surprises.
of field issues trace back to onboarding and update paths, not sensing.
of early truck rolls are avoidable with remote diagnostics and OTA rollback
of integration defects disappear when schemas and contracts are defined upfront.
We focus on real-world reliability first: identity, data pathways, power budgets, and a pilot-ready operational view that makes devices usable from day one.
Identity & onboarding: per-device credentials, zero-touch provisioning
Protocol adapters: Modbus / OPC UA / CAN / RS-485 → MQTT/HTTPS
OTA pipeline: signed artifacts, staged rollout, health checks, rollback
Resilient connectivity: Wi-Fi / Ethernet / LTE Cat-M / NB-IoT with store-and-forward
Device twin & telemetry: versioned schemas, alert hooks, minimal fleet dashboard
Ensure predictable, revocable access at scale with identity and zero-touch onboarding.
Reduce silent failures using retries, back-pressure handling, and offline buffering.
Use signed OTA with staged rollout and rollback to deliver fixes without risking field stability.
Accelerate integrations with clean schemas and device-twin models for consistent analytics.
Cut MTTR with actionable telemetry—logs, metrics, and events that remove operational guesswork.
Define success criteria, battery budgets, network assumptions, and key risks before build.
Stabilize drivers, establish device credentials, and set up a secure provisioning flow.
Build protocol bridges, secure ingest, define schemas, and configure baseline alerts.
Enable signed builds, validate staged rollouts, and verify rollback behavior.
Configure device twins, remote diagnostics, and store-and-forward queues for real-world conditions.
Deliver the runbook, ownership map, evidence tables, and a clear go/no-go decision framework.
A connected cohort with live views of device health, status, and alerts.
A unified schema and device twin delivering clean, consistent analytics.
A battery and cost-to-serve model based on real usage for credible budgets and SLAs.
A remote-fix and ticket-deflection model with clear stakeholder assumptions.
A go/no-go memo outlining risks, mitigations, and next scale gates.

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Commercial ventilation systems
lower energy use and 35% faster commissioning through demand-controlled airflow powered by live telemetry.
Networked smoke detection
fewer false alarms, 40% less inspection prep, and 25% lower MTTR with centralized status and test logging.
Municipal water usage & leak alerts
reduction in non-revenue water and faster leak resolution enabled by real-time consumption dashboards.
Frost protection automation
fewer spoilage incidents and reduced emergency call-outs with sensor-driven heating control.
Typically an onboarded test fleet with first telemetry in 2 weeks.
Yes—clean schemas and secure ingest that plug into AWS, Azure, or your data platform.
Both. We favor clean designs for scale, but use non-invasive adapters to accelerate pilots when it helps.
Per-device identity, signed artifacts, key rotation, and audit-ready logs from day one.
We model and measure budgets early, then co-design firmware/radio/payloads to meet life targets.
Yes—staged rollout, health checks, and rollback are proven before pilots.
You own custom code and artifacts; we retain reusable accelerators.
Brief on environment/constraints, target metrics, sample hardware/signals, and a security/IT contact.