Everything we do, named.
Five practices, thirty-three services. Most engagements draw on more than one, because platform, data, models and architecture are one problem wearing four job titles.
Cloud & platform engineering
We build the Kubernetes estate underneath everything else — on your own hardware, in your cloud accounts, or across both as one operational surface. You get a platform with ingress, storage, policy, secrets and observability already decided, documented and handed over.
Kubernetes platform foundation
A production cluster estate with ingress, storage, secrets, policy and observability installed, documented and handed over.
Hybrid landing zone
The account, network, identity and policy structure that makes an on-premises and a cloud estate one operational surface.
GitOps delivery pipeline
Declarative delivery where the repository is the source of truth and a rollback is a revert.
Bare-metal GPU cluster build
Accelerated hardware turned into a scheduled, shared, measured resource rather than a machine somebody logs into.
Zero-trust network & remote access
A network where reaching a service requires an identity rather than a location, with the corporate tunnel as a component rather than a perimeter.
Platform reliability & SRE enablement
Service level objectives, error budgets, on-call and runbooks, installed and then handed over.
Cloud cost & FinOps
Unit economics per workload, and the placement changes that follow from them.
Data engineering
We build open-table-format estates and the streaming spines that feed them, with the layout, the compaction, the retention and the failure semantics decided rather than defaulted. Every migration we run is proven equal, not assumed equal.
Lakehouse foundation
An open-table-format estate with the catalogue, the layout, the compaction and the retention decided rather than defaulted.
Streaming backbone
A Kafka and structured-streaming spine with exactly-once semantics, checkpointing and replay, built so a late record has a defined fate.
Batch-to-streaming conversion
An existing nightly estate turned incremental without a rewrite, one pipeline at a time.
Data contracts & schema governance
A schema registry and an enforcement point, so a producer cannot break a consumer silently.
Warehouse modernisation
A migration off a legacy warehouse with the semantics preserved and proven equal rather than assumed equal.
Pipeline reliability audit
An independent read of an existing estate, returning the ranked list of what will fail and what it will cost.
Data quality & equivalence harness
An automated comparison lane that proves two paths produce the same data, which is the only honest way to migrate anything.
Data science & machine learning
We build models against the decision they inform rather than against a leaderboard metric, and we ship them with the registry, the serving and the monitoring that make them a system instead of a notebook.
Decision modelling & forecasting
Demand, risk or capacity models built against the decision they inform rather than against a leaderboard metric.
MLOps platform
Feature store, model registry, serving and monitoring, so a model is deployable by the team that built it.
Experimentation & causal inference
The design of experiments and the analysis that separates a real effect from a seasonal one.
Model risk & validation
Independent validation, documentation and challenge, in the form a regulator or an audit committee expects.
Analytics engineering
The semantic layer and the metric definitions, so two dashboards stop disagreeing about revenue.
Applied AI
We put language, voice and video models into production on hardware you control or on burst capacity you rent, with routing, quotas, evaluation and guardrails built in from the first day rather than bolted on after the first incident.
Private LLM platform
Model serving on your own accelerated hardware, with routing, quotas, caching and observability, so the data never leaves.
Retrieval-augmented knowledge systems
A retrieval layer over your corpus, with ingestion, chunking and evaluation treated as engineering rather than as configuration.
Agentic workflow engineering
Multi-step agents with tools, bounded autonomy, human checkpoints and a full audit trail of what the agent did and why.
Voice agents
Speech recognition, a reasoning layer and speech synthesis assembled into an assistant that answers inside a human conversational turn.
Synthetic presenter & video systems
Generated video with a consistent brand identity, rendered on burst capacity and published through a pipeline rather than by hand.
Evaluation harness & guardrails
The test suite for a probabilistic system, covering correctness, safety, regression and drift.
Inference placement & cost optimisation
Deciding per workload whether it belongs on owned hardware, on cloud accelerators or on a serverless provider — and making the switch a configuration change.
Architecture & software engineering
We review, design and modernise systems, and we leave the decision-record practice behind so the same argument does not recur every quarter. Where you need the judgement before you need the headcount, we hold the architect's chair.
Architecture review & decision-record programme
An independent review returning the risks in priority order, plus the decision-record practice that stops the same argument recurring.
Domain-driven service design
Bounded contexts, service boundaries and contracts derived from the business rather than from the current database.
Legacy modernisation
Incremental strangler migration with the old and the new running side by side and proven equivalent before the switch.
Platform engineering for product teams
The internal developer platform, the golden paths and the templates that make the right thing the easy thing.
Engineering due diligence
A technical assessment of a target company for an investor, delivered as a written verdict with the remediation cost estimated.
Fractional CTO
Senior technical leadership at a fraction of a full-time appointment, for a company that needs the judgement before it needs the headcount.
Team enablement & technical mentoring
The transfer of the practice to your own engineers, because an engagement that leaves no capability behind has failed.