Software Consultancy
Better Technology Decisions, Made Earlier.
Systems rarely fail at the code level. They fail at decisions made two years earlier — a boundary drawn in the wrong place, a database chosen for load that never arrived, a service split nobody could afford to staff. We work at that level.
The Problem
The cost of a decision is paid long after it is made.
Systems rarely fail at the code level. They fail at decisions made two years earlier — a boundary drawn in the wrong place, a database chosen for load that never arrived, a service split nobody could afford to staff. We work at that level.
Teams rarely ask for architecture help while things are calm. They ask when a release takes three weeks, when one table locks under load, when onboarding an engineer takes a month, or when an acquisition puts someone else’s stack inside theirs.
By then the problem is not a single bad component. It is a set of couplings that each made sense on their own and now hold one another in place: a database three teams write to, a deployment only one person can run, a queue that started as a workaround and became load-bearing.
Untangling that takes judgement about sequence more than it takes new technology. Which constraint do you remove first so that the next one becomes removable at all? That is the question we answer, and we answer it with evidence from your system rather than from a reference architecture.
Our Approach
How we work on this.
The same order every time. Understanding before design, design before build, evidence before scale.
- 01
Read the system as it is
We go through the code, the schema, the deployment path and the incident history before proposing anything. The documented architecture and the running architecture are usually two different systems; we work from the second one.
- 02
Locate the binding constraint
Not everything that is wrong is worth fixing. We identify the small number of couplings that block everything else — the shared write path, the untestable module, the manual release — and rank the rest below them.
- 03
Design the target and the route to it
A target architecture nobody can reach is a diagram. We write down the end state and the intermediate states, each one shippable, each one leaving the system working and the team able to stop.
- 04
Prove it on a real slice
One service, one workflow, one migration, executed end to end with your engineers. It settles arguments that documents cannot, and it calibrates the estimate for everything that follows.
- 05
Hand over the judgement, not just the plan
We write down the rules the decisions came from — what belongs inside which boundary, when to split, when to leave it alone — so your team can extend the design without us in the room.
Capabilities
What this covers.
Named plainly, so you can tell whether we are the right people for the piece of work you have.
- Software Architecture
- Technical Strategy
- Legacy Modernization
- Cloud Architecture
- Technical Due Diligence
- Performance Optimization
- Engineering Consulting
Technical Architecture
Where the work sits.
Stabilise
Make the system observable and releasable before changing its shape. Without a reliable deploy and a signal for regression, every later step is a guess dressed as a plan.
Decouple
Break the couplings that force unrelated changes to ship together: shared write paths, shared schemas, shared release trains, shared on-call.
Modernise
Replace the components whose cost has become structural — the framework nobody upgrades, the batch job that defines the business day — one at a time, behind a boundary that already holds.
Scale
Only once the shape is right. Scaling a bad boundary buys a few months and multiplies the eventual migration.
Institutionalise
Encode the decisions as defaults: service templates, review rules, architecture tests, budgets. Otherwise the system drifts back to where it started.
Use Cases
Where this applies.
If one of these reads like a description of your week, it is the right conversation to start with.
A monolith that can no longer be released weekly
One deployable with a two-week regression cycle. We find the seams that already exist in the data model, extract the highest-churn area first, and recover the release cadence before touching the rest.
Post-acquisition stack consolidation
Two products, two identity systems, two billing models. We decide what merges, what stays separate behind an interface and what gets retired, in a sequence that keeps both customer bases live throughout.
Technical due diligence before a commitment
An independent read on architecture, delivery capability, key-person risk and the real cost of the stated roadmap — written for people who have to act on it, not filed as a deliverable.
A database under load it was never designed for
Query paths, index strategy, write amplification and contention. We measure before recommending, because the answer is often a read model or a changed access pattern rather than a different engine.
A platform choice with a decade of consequence
Cloud, runtime, data platform, build versus buy. We compare on the constraints that will actually bind — hiring, egress, latency, compliance, operational load — rather than on feature matrices.
A team that ships slowly for structural reasons
Long-lived branches, unclear ownership, environments that drift, review queues nobody owns. We change the structure that produces the delay instead of adding process on top of it.
Business Impact
What changes.
Stated as outcomes rather than percentages. We publish numbers for work we measured, on the page for that work.
Releases become routine rather than events, because the path to production is exercised as often as the code changes.
The cost of change stops rising with system age, because boundaries hold instead of leaking.
Failures are diagnosed from telemetry rather than reconstructed from memory.
Capacity and platform decisions are made against measured behaviour instead of vendor guidance.
New engineers become productive without a named guide, because the design is legible from the code.
Technology choices survive contact with the roadmap, because the roadmap was an input to the evaluation.
Related Work
Worked examples.
Realistic problems taken through architecture, implementation and the trade-offs we would argue for in a real engagement.
- DemonstrationIndustrial manufacturing
Intelligent Operations Platform
A reference architecture for unifying plant telemetry, work orders and quality records behind one operational data model, with model-assisted triage layered on top.
- DemonstrationLogistics
Legacy Modernization
A strangler-pattern reference for moving a business-critical monolith to a service boundary set, without a migration weekend and without a feature freeze.
FAQ
Questions we are usually asked.
Software consultancy
Bring us the decision you keep deferring.
An architecture review, a modernisation sequence, or a second opinion before a large commitment. Tell us the constraint and we will tell you what we would do first, and why.