Principal-led systems & AI practice
Systems engineering that enables your team to take AI
from PoC to production
AI keeps getting more powerful. Accountability stays human.
Getting AI to work in a demo is the easy part. The hard part is everything after: making it trustworthy, keeping the final levers in human hands, and surviving contact with production.
That is the systems-engineering work where we bring three decades of experience, so your team can build the system and the capability to own it.
From software architecture to AI-assisted engineering and agentic products: real problems, real systems, senior judgement.
Three ways to work with us
Different problems need different kinds of help. You may need to resolve an architectural problem blocking production, occasional help with difficult technical decisions, or a way to build capability inside your team. We’ll start with the smallest useful engagement.
Production-Ready AI
When a live system needs senior intervention.
A stalled PoC, a difficult architecture or security decision, or a system that needs to cross the gap between convincing demo and dependable production. We diagnose, architect, build where needed, and hand the capability back to your team.
Architecture Advisory
When the hard decisions keep coming.
Regular senior support for architects, engineering leads and technical leaders carrying decisions that are expensive to get wrong. Bring the live decision; leave with the reasoning, design and decision record.
Workshops
When the capability needs to live inside your people.
Practice-based programs built around your real systems, code and decisions — from software architecture, through AI-assisted delivery, to trustworthy agentic products.
Practice-based workshops
Participants learn by working on real systems, code and decisions. Build capability in the individual, the team and the product.
The person
Software Architecture
For senior engineers stepping into architectural responsibility. Bring a live architectural decision; learn to reason it through and record it defensibly.
Senior engineer → architect
The team
AI in the SDLC
For engineering teams adopting AI across delivery without giving away understanding, quality or control.
Faster team → accountable team
The product
Agentic AI
For experienced technical leaders building an agentic product while deciding whether, where and how agents genuinely belong.
Agent demo → trustworthy product
Example judgement calls that rescue production systems
- Don’t automate the human who still owns the decision. In legal document review, the architecture was designed around the lawyer’s review workflow rather than pretending autonomous review was the goal.
- Don’t build the feature if the reusable capability is the real asset. A sales assistant became a shared knowledge engine supporting multiple products rather than another isolated chatbot.
- Don’t vectorise the warehouse because everyone else is doing RAG and SQL Generation fails anyway for complex queries. For an enterprise analytics assistant, we rejected a proposal to embed the entire warehouse and instead used schema-aware SQL generation, splitting exploratory questions from must-be-right ones.
Recent work includes production systems for Fortune 500 and FTSE-100 companies.
See the case studies →Our approach
Tools change quickly. The hard questions don’t. Across consulting, advisory and workshops, we use the same five-step discipline:
Frame → Options → Size → Decide → Record
The detail changes with the problem. The principle does not: match the depth of reasoning and verification to what is at stake. See details of our approach →
Facing a hard architectural decision?
Bring the messy version. We'll help you work out what to do next.
Talk it through