// strategy · compliance · engineering
AI strategy, compliance and engineering that works in production.
Organisations have a board mandate for AI, a compliance team that is risk averse, and a technology team already swamped with support tickets. We help bridge that gap from business case, SOP, EU AI Act compliance to private workflow deployment & inference infrastructure running in your environment.
Business case, roadmap and governance before any build begins.
EU AI Act ready - evals, governance and audit built in from day one.
Model inference inside your cloud, VPC, or on-prem boundary.
Every input, decision, and approval recorded in a structured record.
// The organisational gap we bridge
3 layers with competing priorities
Strategy wants speed. Compliance wants risk control. Engineering wants clarity. Without an integrated plan, some AI programmes struggle to achieve ROI.
AI models are now capable enough to add value, but the people who define scope, manage risk, and the people who build systems need to be on the same page or the gap becomes clear in production.
Leadership getsA structured AI strategy, readiness assessment, and roadmap that engineering can actually build and compliance can sign off.
Compliance getsEU AI Act governance, risk classification, and audit architecture written by engineers who understand what they're auditing.
Engineering getsWorkflow contracts, inference infrastructure, and private agent deployment with defined scope, audit trails, and escalation paths that don't change after launch.
// How we help
Two engagement tracks. One team that can do both.
Most firms either advise on AI or build it. We provide the end to end view.
Strategy to Governance
We work with leadership, data, and compliance teams on the decisions that have to be agreed before anything is built, the ones that are hard to reverse once you're in production.
AI Strategy, Readiness & Roadmap
Business case development, AI maturity assessment, phased build roadmap with defined success criteria, tailored to your actual operating environment.
AI Governance, Risk & EU AI Act
High-risk system classification, transparency obligations, human oversight requirements, and audit architecture embedded from the outset.
AI Platform Architecture
Open source versus proprietary model selection, hosting strategy, total cost of ownership modelling, and boundary requirements for regulated data environments.
Production Workflow & SOP Design
Mapping regulated procedures to AI-ready workflow contracts identifying what the model can do, where humans must remain in the loop, and what evidence each step must capture.
Architecture to Deployment
We design, build and deploy the systems that get AI running safely in production. Private, auditable, and engineered for regulatory scrutiny and durability from day one.
AI Agent Design, Development & Deployment
Production-grade agents written in Rust and Python with workflow contracts, defined escalation paths, and structured audit trails per run.
Inference Infrastructure
Private model serving inside your environment using vLLM, SGLang, TensorRT-LLM, or NVIDIA Dynamo configured for your latency and compliance needs.
Deployment Architecture & PII Redaction
24/7 runtime inside your cloud, VPC, or on-prem with authorised connectors, IAM controls, and runtime PII detection with reversible tokenisation upstream of the model.
Model Fine-tuning, Quantisation & Optimisation
Domain-specific fine-tuning with structured benchmarking for accuracy, latency, and cost measured against your task, your data, and your operating constraints.
// How an engagement works
From first conversation to production deployment.
Most engagements start with either a strategic assessment or a defined production challenge. We scope the opportunity, design the solution, build it, and either transition ownership to internal teams or continue as an embedded engineering partner.
AI Readiness & Scoping
We map people, process, data, technology, and governance. We define what a safe production deployment looks like for your specific operating environment and regulatory context.
Blueprint & Governance
Roadmap, workflow contract design, EU AI Act classification, risk register, platform architecture decision, and a phased implementation plan that is compliance ready.
Build & Deploy
Private inference infrastructure, workflow engineering with audit trails, agent development in Rust/Python, PII redaction, escalation paths, and deployment inside your boundary.
Optimise & Harden
Fine-tuning, quantisation, benchmarking evals for your specific tasks, performance profiling, and ongoing monitoring & support for your operating environment.
// Where to start
Not sure where to start?
We'll give you an honest, impartial view on what your best path to a production AI solution is.