We build automation and AI systems that survive contact with reality.
Production systems. Clear ownership. Automation first — AI only where it earns its keep.
If your problem is clear, your constraints are known, and the system matters — we build. Not demos. Not experiments. Not "let's try AI and see". We design and ship systems that people actually rely on.
AI optional · Human accountable
This path works best when:
If most of this feels true, building is likely the right next step.
If not — starting with a short system review usually saves months.
What you actually build
Automation & Workflow Systems
Replacing manual steps with deterministic, reliable workflows. APIs, internal tools, data pipelines, back-office logic.
Example: Order handling, onboarding flows, internal approvals
AI-Assisted Capabilities
Language, classification, search, summarisation — only where judgment or scale demands it. AI supports decisions. It does not quietly make them.
Example: Email triage, document analysis, internal knowledge search
System Integrations
Connecting tools that were never meant to talk to each other — safely. CRMs, inboxes, databases, legacy software, internal services.
Example: CRM sync, data warehouse pipelines, API bridges
Internal Software & Operational Tools
Custom systems built for how your company actually works — not how SaaS demos assume you work.
Example: Admin dashboards, workflow tools, reporting systems
How you build
Automation before AI
Rules are cheaper, faster, and safer. AI is added only when rules stop working.
Human-in-the-loop where risk exists
If a mistake can cost money, trust, or compliance — a human stays accountable.
Production thinking from day one
Logging, error handling, ownership, monitoring. No 'we'll harden it later'.
Clear scope and stopping points
We define what success looks like — and when to stop building.
Bias toward simplification
Sometimes the best improvement is deleting half the system.
AI is not at the base. Humans are not optional.
What you deliberately do not build
We don't build:
If this sounds restrictive — it is.
That's how systems remain usable six months later.
Engagement shapes
Direct build engagement
For teams with clear goals and stable processes.
Audit → build
When assumptions need validation or risk is high. Often faster in the long run.
Improve & refactor
For existing automation or AI that feels fragile, expensive, or opaque.
We'll tell you which path fits — and why.
If you're confident in what needs to be built, we can discuss execution.
If there's uncertainty — validating first is usually the smarter move.
Short diagnostic. Paid. No obligation to build.