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Deploint

Capability 06

Software meets the physical world.

We engineer the systems that connect machines, sensors and cameras to cloud platforms and enterprise applications: embedded software, edge computing, computer vision and digital twins, built for sites where networks drop and hardware has to keep working.
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Capability 06

07 stages

Core disciplines

  • IoT
  • Edge computing
  • Embedded systems
  • Digital twins
  • Computer vision
  • Industrial automation

Works alongside

01Services

What we engineer.

Engineering across the full path from physical signal to enterprise decision, within the constraints of real hardware and real sites.
  • 01

    IoT

    Device connectivity, provisioning, fleet management and telemetry pipelines for connected assets, with a secure identity for every device.

  • 02

    Edge computing

    Compute close to the source for low-latency decisions, local resilience and bandwidth reduction, managed centrally as a fleet.

  • 03

    Embedded systems

    Firmware and embedded software for microcontrollers and embedded Linux, with secure boot, over-the-air updates and hardware integration.

  • 04

    Computer vision

    Inspection, detection and tracking models deployed on edge devices or in the cloud, with data pipelines for labeling and retraining.

  • 05

    Digital twins

    Live digital representations of assets, lines or sites that combine telemetry, models and context for monitoring, simulation and planning.

  • 06

    Robotics

    Software for robot integration, perception, task orchestration and fleet coordination, connected to plant and enterprise systems.

  • 07

    Industrial automation

    Integration with PLCs, SCADA and MES through industrial protocols such as OPC UA and Modbus, keeping control systems isolated from IT networks.

  • 08

    Connected devices

    Software for connected products: device applications, cloud backends, companion mobile apps and secure update channels.

02Reference architecture

From physical signal to enterprise decision.

Seven stages between a physical event and an action in an enterprise system. Select a stage to see what we engineer there.

Machines, production lines, vehicles, infrastructure and environments: the assets and processes the system observes and influences.

  • Machines
  • Production lines
  • Vehicles
  • Facilities

03Edge and cloud

What runs where.

Splitting work between edge and cloud is the central design decision in connected systems. We place each function by latency, bandwidth, resilience and safety requirements.

01 / Edge

04 functions

At the edge

Where milliseconds, bandwidth or site autonomy matter.

  • 01

    Real-time inference

    Vision and anomaly models that must respond within the cycle time of a machine or line.

  • 02

    Protocol translation

    Normalizing OPC UA, Modbus and vendor protocols into one consistent data model.

  • 03

    Store-and-forward

    Buffering telemetry locally so nothing is lost when connectivity drops.

  • 04

    Local rules

    Logic that must keep running without the cloud, kept separate from safety-rated control systems.

Secure transport

  • MQTT over TLS
  • Device certificates
  • OT / IT segmentation

02 / Cloud

04 functions

In the cloud

Where scale, history and cross-site context matter.

  • 01

    Fleet management

    Device registry, configuration, health and over-the-air updates across every site.

  • 02

    Model training

    Training models on history from the whole fleet, then deploying them back to the edge.

  • 03

    Digital twins

    Asset and site models that combine telemetry, maintenance history and engineering data.

  • 04

    Enterprise integration

    Connecting insights to the ERP, MES and maintenance systems where work is planned.

04Concepts

Engineering for real hardware.

Connected systems fail differently from pure software. These practices keep devices secure, updatable and useful over long service lives.

01Devices

Secure, maintainable fleets.

  • Device identity

    Each device receives a unique, hardware-backed identity, typically an X.509 certificate issued at manufacture or first boot. It enables mutual authentication and lets a compromised device be revoked individually.

  • Over-the-air updates

    Signed firmware and software updates delivered in staged rollouts, with A/B partitions or equivalent so a failed update rolls back automatically. Without them, every vulnerability becomes a site visit.

  • Store-and-forward

    Local buffering of telemetry and events on the device or gateway during network outages, with ordered, de-duplicated delivery once connectivity returns.

02Signals

Data worth acting on.

  • Time-series data

    High-frequency telemetry indexed by time, stored in systems built for downsampling, retention tiers and fast range queries. Raw data often stays at the edge or in cold storage, while aggregates flow upward.

  • Industrial protocols

    OPC UA, Modbus, MQTT and vendor-specific protocols carry data from controllers and devices. We translate them at the edge into a consistent, documented data model.

  • Edge inference

    Running optimized models on gateways or embedded accelerators, often after quantization, so decisions land within the latency budget of the physical process.

03Operations

Context for decisions.

  • Digital twins

    A digital representation of an asset or process, kept synchronized with telemetry. Twins range from a live state view to physics-based or data-driven simulation, and the right fidelity depends on the decision they support.

  • OT / IT segmentation

    Operational technology networks are separated from IT networks through zones and conduits, with data flowing through controlled gateways. It limits how far an IT compromise can reach into physical operations.

  • Human-in-the-loop operations

    Model recommendations reach operators and planners with explanations and confidence, and their feedback improves the models. Automated actuation is introduced only where it has been validated and approved.

05Engineering approach

How we engineer connected systems.

Hardware lives for years in demanding conditions. We design for that from the first prototype.
  1. 01

    Offline is normal

    Devices and edge nodes keep working through network loss and synchronize safely when it returns.

  2. 02

    Secure from the silicon up

    Hardware-backed identity, secure boot, signed updates and encrypted transport are baseline requirements.

  3. 03

    Update everything remotely

    Every deployed component can be updated, monitored and rolled back without a site visit.

  4. 04

    Respect the control layer

    We integrate with control systems through defined interfaces and never compromise their safety functions or determinism.

  5. 05

    Prototype on real signals

    We validate early with data from the actual site or line, because lab data rarely matches the field.

  6. 06

    Fleet thinking

    We design for large fleets, with provisioning, observability and lifecycle management built in.

06Industries

Where we apply digital engineering.

Sectors where software has to work alongside physical assets, harsh environments and operational teams.
All industries

07Concept architectures

Digital engineering reference architectures.

Illustrative engineering references that show how we approach a problem. They are concept architectures, not descriptions of client engagements.
All case studies

08FAQ

Common questions.

Straight answers on how we approach Digital Engineering.
01What is the difference between IoT and digital engineering?

IoT is about connecting devices and moving their data. Digital engineering covers the whole system around them: embedded software, edge computing, computer vision, digital twins and the integration that turns physical signals into enterprise decisions.

02Do you work with existing PLCs, SCADA and MES systems?

Yes. We integrate through industrial protocols such as OPC UA and Modbus, and through MES and historian interfaces, keeping control systems isolated and unchanged wherever possible. Integration is read-only by default, and any write path is reviewed with your operations and safety teams.

03When should processing run at the edge rather than in the cloud?

When latency must be shorter than a network round trip, when bandwidth makes shipping raw data impractical, when sites must keep operating offline, or when data must stay on site. Training, fleet management and cross-site analytics usually belong in the cloud.

04How do you secure connected devices?

A unique hardware-backed identity per device, mutual TLS, secure boot, signed over-the-air updates, minimal exposed services and segmentation between operational and IT networks. A compromised device can be revoked individually.

05What does a digital twin project involve?

Defining the decisions the twin should support, then connecting the telemetry, asset data and models needed for them. Most twins start as a live operational view and add simulation or prediction where it pays off. Fidelity follows the decision, not the other way around.

Digital Engineering

Connecting physical operations to software?

Tell us about the assets, the sites and the decisions you want to improve. We'll help you architect the path from sensor to enterprise.

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