ARTEMISIntelligence, Trust, and Control for the Systems That Move the World.

In applied AI the model is rarely the hard part. We start from the decision — what is predicted, who acts on it, and what it costs when the answer is wrong — then build backwards into the data. Models are evaluated against operational reality rather than a leaderboard, shipped behind interfaces your teams already use, and watched in production so drift is caught before anyone downstream feels it.

Typical engagements

• Discovery sprint
• Proof of concept to production
• Embedded AI team
• Model audit and remediation

What we deliver

• Data and feature pipelines

  Ingestion, labelling workflows and feature definitions that keep training inputs and production inputs identical.

• Evaluated, production-ready models

  A baseline, candidate models and an evaluation harness scored on operational cost — not accuracy alone.

• Decision interfaces

  APIs, dashboards and in-workflow surfaces that place a prediction exactly where the decision is made.

• Monitoring and retraining

  Drift detection, shadow deployments and scheduled retraining with a documented path back to a known-good version.

A language model earns its place when it is grounded, constrained and measurable. We design retrieval and tool-use architectures over your documents, tickets and telemetry, tune against evaluation sets built from real tasks, and put guardrails wherever a wrong answer would be expensive. Deployment runs from managed APIs through to models serving entirely inside your own network.

Typical engagements

• Assistant build
• Evaluation and guardrail review
• Private model deployment
• Team enablement

What we deliver

• Retrieval-grounded assistants

  Retrieval architecture over your corpus, with tool use, permissions and citations back to the source document.

• Evaluation harness

  Task-level test sets, regression runs and scoring so that changing a prompt or a model is a measured change.

• Guardrails and safety layer

  Input and output filtering, tool permissioning, sensitive-data handling and human-in-the-loop escalation.

• Fine-tuning and private inference

  Adapter training and self-hosted serving for data and workloads that cannot leave your estate.

Digital-asset systems are judged on what happens on their worst day. We design custody, settlement and on-chain integrations around an explicit threat model: where key material lives, which signing paths exist, who has to approve what, and what evidence survives the incident. Contracts are specified before they are written and independently reviewed before they ever hold value.

Typical engagements

• Security architecture review
• Contract audit and hardening
• Custody platform build
• Monitoring retainer

What we deliver

• Threat model and key architecture

  Custody design, hardware or multi-party signing paths, approval quorums and a rehearsed recovery procedure.

• Smart contract design and review

  Specification, implementation, property-based test suites and independent review ahead of deployment.

• Settlement and reconciliation

  On-chain and off-chain reconciliation, ledgering and exception handling built for the people who close the books.

• Audit and control evidence

  Tamper-evident logging, reporting and controls documentation your auditors and regulators can actually use.

The same workload behaves differently in a data centre, a regional cloud and a box bolted to a machine on a factory floor. We place compute deliberately — latency, bandwidth and failure domain decide where code runs — and then make the whole estate deployable from one pipeline, with one honest view of its health whether a node is in a region or in a truck.

Typical engagements

• Platform build
• Cloud and edge migration
• Cost and performance review
• Managed platform operation

What we deliver

• Reference architecture

  Cloud, regional and on-device tiers with explicit data flows, latency budgets and failure boundaries.

• Infrastructure as code and delivery

  Reproducible environments, progressive rollout and rollback that treat a device fleet like any other target.

• Edge runtime and fleet management

  Constrained-hardware runtimes, over-the-air updates and offline-first sync that survives a lost link.

• Observability and SLOs

  Metrics, traces, logs and service objectives that cover the edge as thoroughly as the core.

Moving people, goods and data is an optimisation problem wrapped in an operational one. We build the telemetry backbone first so the network has a truthful real-time state, then the planning and routing on top of it, then the tooling dispatchers and drivers hold in their hands — because a plan nobody on the ground can execute is not a plan.

Typical engagements

• Network modelling study
• Routing platform build
• Fleet telemetry rollout
• Continuous optimisation partnership

What we deliver

• Telemetry and tracking backbone

  Vehicle, asset and sensor ingestion producing one real-time state of the network across every partner system.

• Routing and scheduling engines

  Constraint-aware planning for routes, loads, shifts and depots, with what-if simulation before anything moves.

• Dispatch and driver tooling

  Operations consoles, exception queues and mobile apps built to keep working on poor connectivity.

• Integration layer

  Transport, warehouse, ERP and partner APIs joined into a single operational picture rather than six tabs.

Control systems are where software meets consequences. We build the supervisory, automation and safety layers for operations that cannot simply be turned off and on again: defined operating states, deterministic transitions, tested failure paths, and an operator who is never left guessing what the system is doing or why it did it.

Typical engagements

• Controls design review
• Automation build and commissioning
• Legacy system modernisation
• Round-the-clock operational support

What we deliver

• Control architecture and state model

  Operating states, interlocks and transitions specified and reviewed before a line of control logic is written.

• Supervisory and plant integration

  Controller, sensor and historian integration over segmented, monitored networks with least-privilege access.

• Operator interfaces and alarm design

  Interfaces built around alarm rationalisation, situational awareness and unambiguous escalation paths.

• Simulation, testing and commissioning

  Hardware-in-the-loop and digital-twin testing, plus factory and site acceptance support through go-live.