One system. Six engineering disciplines.

We map user journeys, data sources and system boundaries first. Interfaces, APIs and background jobs are designed as parts of one observable architecture.

Testable services, legible interfaces, documented integrations and a software foundation whose behaviour can be monitored in operation.

Web and mobile applications, APIs, data pipelines, databases, integrations, operations views and deployment.

Access boundaries, data consistency, intermittent links, latency, existing-system fit and maintenance cost.

Unit and integration tests, interface contracts with real data, failure cases, measurements and rollback rehearsal.

We apply a threat model to the actual data path from device to cloud. Identity, authorization, secrets, updates and logging become part of the development process.

A prioritized risk map, verifiable controls and a secure development workflow that teams can maintain.

Threat models, identity and access, API boundaries, device communications, secrets, updates and logs.

Attack surface, key lifecycle, least privilege, physical access and legacy-system limitations.

Control reviews, unauthorized-flow and failure tests, configuration checks and traceable findings.

We evaluate sensor choice, sampling, power budget and communications together. PCB and firmware evolve iteratively between lab measurement and field constraints.

Schematics and PCB design, prototype firmware, test records and explicit decisions for the next revision.

MCU firmware, sensor interfaces, analog/digital acquisition, communications, power and PCB integration.

Sampling time, noise, energy budget, memory, temperature and field service access.

Instrumented signal checks, timing and power measurement, reproducible prototypes and fault-condition tests.

We split uncertainty into hypotheses and measurable experiments. Simulation, prototypes and test fixtures examine the same question from different angles.

A proof-of-concept prototype, experimental evidence, a risk register and a basis for deciding whether to build or investigate further.

Feasibility, test rigs, PCB prototypes, 3D-printed or machined parts where needed, and measurement software.

Testable hypotheses, material and manufacturing tolerances, cost and repeatability.

Set success criteria before the experiment; carry results, uncertainty and failed attempts into the next revision.

We interpret vibration and operating data in the context of the equipment. Sampling, frequency analysis and trend tracking rest on a trustworthy measurement chain.

Condition indicators, inspectable measurement records and technical visibility that a maintenance team can interpret.

Vibration sensors, acquisition, time/frequency analysis, balancing investigation and condition indicators.

Sensor placement, speed and load changes, sample rate, calibration and measurement uncertainty.

Reference and repeated measurements, comparing suspicious patterns with operating context. A single reading is not a diagnosis.

We treat device, connection and platform as one data path. Intermittent links, location accuracy, event timing and integrity are considered from the first architecture.

An observable telemetry flow, foundations for device management and meaningful map and event views for operations.

GNSS and field sensor → device/firmware → secure transport → ingestion → storage → application → operator.

Coverage gaps, offline queues, duplicate messages, timestamps, device identity and integrity.

End-to-end tests for dropouts, reconnects, late events, inaccurate location and higher data volumes.