Services · Six disciplines
Six stages of one loop.
Networking, cloud, software, machine learning, robotics and the applications that close the loop. Each section below states what its stage must guarantee — something you could hold us to — and what it is built from.
The argument
The hard part is the handoffs.
Each stage is a mature discipline with its own literature and its own people. The failures we get called about live in the joins between them — a timestamp that means one thing at the sensor and another in the warehouse, a decision nobody can trace back to the reading that caused it. A handoff belongs to whoever owns both sides of it, which is the whole argument for covering all six.
S1 · Networking & IT infrastructure
Sense
Every signal your operation produces arrives intact, timestamped, and attributable.
A loop cannot correct what it cannot measure, so sensing is the first discipline rather than the last. We build the network, the endpoints and the telemetry path that turn physical activity into trustworthy data.
What this stage guarantees
- Every device on the network is inventoried and authenticated
- Telemetry is timestamped at source, not at ingest
- Network segments fail closed, never open
- Packet loss and jitter are measured continuously, not on complaint
SNMP · NetFlow · 802.1X · OpenTelemetry · Zero-trust segmentation
S2 · Cloud & platform
Transport
Data moves from where it is produced to where it is decided — without loss, and without a surprise invoice.
The substrate everything else runs on. We design the cloud topology, the delivery guarantees and the cost model together, because a pipeline that is correct but unaffordable gets switched off.
What this stage guarantees
- Infrastructure is defined in code and reproducible from an empty account
- Delivery semantics are stated explicitly per stream, not assumed
- Every environment can be rebuilt without a person remembering a step
- Cost is attributed per workload from day one
Terraform · Kubernetes · Kafka · S3 · OpenTelemetry collectors
S3 · Software engineering
Compute
The systems that turn signal into state are versioned, tested, and safe to change on a Friday.
The applications, services and data models that hold your operation together. We optimise for the second year of a system rather than the first month of it.
What this stage guarantees
- Every change ships behind a test that would have caught its absence
- Rollback is a single command, not an incident
- Schema changes are backward-compatible by default
- No production access depends on one individual
TypeScript · Go · Python · PostgreSQL · Trunk-based CI
S4 · AI & machine learning
Decide
Every automated decision can be traced back to the inputs that produced it.
Models are the part of the loop most often bolted on without a way to audit them. We treat a decision system as accountable infrastructure: evaluated before deployment, monitored after it, and explainable when challenged.
What this stage guarantees
- Model behaviour is measured against a held-out set before release
- Inputs and outputs are logged for every automated decision
- A human override path exists and is tested
- Drift is alerted on, not discovered in a quarterly review
PyTorch · ONNX · Vector retrieval · Eval harness · Drift monitors
S5 · Robotics & automation
Act
Actuation is bounded: the system has a defined safe state and can always be commanded into it.
Where software stops being an argument and starts moving mass. Robotics is the most vivid expression of the loop, and the least forgiving — a wrong decision here has momentum.
What this stage guarantees
- A defined safe state exists and is reachable from every operating mode
- Emergency stop is hardware-backed, never software-only
- Fleet behaviour is simulated before it is deployed
- Every actuation is logged against the decision that requested it
ROS 2 · MoveIt · CAN bus · Safety PLC · Fleet orchestration
S6 · Mobile & applications
Verify
A human can see what the system did, and disagree with it, from wherever they are.
The stage that closes the loop. An autonomous system without a human-legible surface is not autonomous — it is merely unattended.
What this stage guarantees
- Operational state is visible on a phone, not only on a wall display
- The interface works with intermittent connectivity
- Any automated action can be inspected and reversed by an operator
- Alerts carry enough context to act on without opening a laptop
Swift · Kotlin · React Native · Offline-first sync
How we work
The same table on every stage.
These commitments do not change with the discipline. They apply to a network rollout and a robot fleet in the same words, and every row names the evidence that would settle an argument about it.
| Parameter | Standard | Method | Evidence |
|---|---|---|---|
| Handover | Reproducible from an empty account | Infrastructure as code + written runbook | Repository |
| Response | First technical reply within 24 hours | Named engineer on rota, not a shared inbox | Ticket log |
| Rollback | Single command, no incident call | Blue/green deploys, backward-compatible schemas | Runbook, deploy history |
| Access | No system depends on one person | Paired operations, documented credentials handover | Access register |
| Change | Nothing merges without a test that would catch its absence | CI gate on every branch | Pipeline history |
Start with the stage you cannot see. The measurement problem comes first, and the automation is a great deal cheaper once the loop is closed.