Global logistics operatorEnterprise
A processing pipeline that fell behind under peak load. We rearchitected it onto a streaming platform and transitioned operations to their team.
Platform, cloud, AI and data engineering for organisations where downtime is not an option and change has to be controlled.
Modernising core systems without interrupting the business that depends on them.
Migration, governance and cost control across the major cloud platforms.
Production systems with the oversight and controls regulated environments require.
Pipelines, warehousing and reporting that leadership can act on with confidence.
Each begins with a short paid assessment and a written view of what we found.
A defined outcome, owned end to end.
Senior engineers inside your existing teams.
Direction for decisions that are expensive to reverse.
Delivered, documented, and handed to your team.
Ledgers, reconciliation and reporting built to withstand scrutiny.
Telemetry, routing and pipelines that hold at volume.
Regulated data and systems that must be traceable.
Subscription and content platforms under load.
Catalogue, inventory and analytics the business trusts.
Long-lived systems with procurement and audit obligations.
Clients are not named. We can discuss detail under NDA.
A processing pipeline that fell behind under peak load. We rearchitected it onto a streaming platform and transitioned operations to their team.
Cloud costs growing faster than revenue. We reviewed the estate service by service and rearchitected only where it was justified.
A language model over years of unstructured records. We built the evaluation framework first, so quality was measured rather than assumed.
A production interface carrying real traffic without operational discipline behind it. We put versioning, monitoring and incident process in place.
A short paid review of the estate. You keep the findings either way.
Decision records for anything expensive to reverse, held in your repository.
Working software throughout, with testing and documentation in the same change.
Runbooks, monitoring and a walkthrough with your engineers.
Which parts of the work a model touches, which parts it does not, and how it is checked.
Evaluation is built before the pipeline, so quality is a number. Outputs cite sources your people can open, and cost is monitored rather than discovered.
Automation on migrations, scaffolding and first-pass review. A named engineer reads and owns every change before it reaches your estate.
No model in a path where error is costly and there is no fallback, no human check, and no way to detect it afterwards. We raise that early.
We operate as part of your engineering function rather than beside it, working within your governance, your delivery process and your security requirements.
Every engagement is led by engineers who have built and run systems at scale, in environments where change is controlled and continuity matters more than speed.
The work is designed to be handed over. Documentation, runbooks and knowledge transfer are part of the schedule, not something arranged at the end.
Replacing a system in place, without a rewrite and without a cutover weekend.
Applied AIHow the pieces fit together, and where the quality is actually decided.
OperationsWhat to instrument first, and what a useful alert looks like.
The system, the timeline, and what it affects. We respond within one business day.
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