Practical technology work for teams with real constraints, old systems, and serious decisions to make.
Voodoo AI helps with the hard middle of change: deciding what matters, designing a route that can survive implementation, and then helping ship it.
Who we work best with
CTOs, founders, COOs, and transformation leads who need a senior technical view without turning the work into a months-long consulting exercise.
Typical triggers
AI pilots stuck after a demo, delivery slowed by old architecture, cloud spend nobody quite owns, or manual workflows that quietly eat margin.
How engagements start
Most work starts with a short review, readiness sprint, or targeted delivery intervention so the first step is useful even if the wider plan changes.
Web & Application Development
Node.js architecture, API design, and platform repair for teams whose software is becoming harder to change, operate, or explain.
View detailsNode.js Systems Architecture
Backends that need clearer boundaries, better observability, safer releases, or fewer mysterious slowdowns.
API Design & Microservices
Service boundaries, contracts, and integration patterns chosen for the team that has to maintain them.
Progressive Web Applications
Fast internal and customer-facing web apps, with reliability and accessibility treated as product requirements.
Full-Stack Product Development
Full-stack delivery when you need a product, dashboard, workflow, or portal built properly rather than patched together.
Performance Engineering
Find the bottlenecks, remove the guesswork, and leave behind measurements the team can keep using.
IT Strategy & Consulting
Technology due diligence, architecture reviews, AI readiness work, and delivery planning for leaders who need decisions they can act on.
View detailsDigital Transformation Strategy
Roadmaps that separate business-critical change from fashionable but low-value activity.
Technology Due Diligence
Plain-English technical assessment for investment, acquisition, board reporting, or recovery planning.
Architecture Review & Remediation
Architecture review with the tradeoffs, risks, and first fixes made explicit.
AI Readiness Assessment
A practical check of data, systems, workflow ownership, governance, and implementation readiness.
Cloud & Infrastructure
Cloud migration, resilience work, cost governance, and infrastructure clean-up for systems that need less drama.
View detailsCloud Strategy & Migration
Migration plans that account for dependencies, cutover risk, ownership, and the reality of existing systems.
Cloud Cost Optimisation
Cost visibility, usage patterns, right-sizing, and governance that stops spend drifting unnoticed.
Multi-Cloud Architecture
Hybrid and multi-cloud decisions made for resilience, compliance, and operational practicality — not novelty.
Infrastructure as Code
Infrastructure that can be reviewed, repeated, and changed without relying on tribal memory.
Data Engineering & AI Systems
Data engineering, LLM integration, AI workflow design, and production ML support for businesses that need usefulness over demos.
View detailsData Platform Engineering
Data foundations that make reporting, automation, and AI less brittle.
ML Pipeline Architecture
Repeatable paths from experiment to deployment, with monitoring and ownership included.
AI System Design & Deployment
AI system design that covers inputs, outputs, review, escalation, failure handling, and measurement.
LLM Integration & Fine-Tuning
RAG, workflow integration, evaluation, and model selection based on the task rather than the trend.
Real-Time Data Systems
Event and streaming systems where teams need timely information without creating an operations burden.
A simple model, used carefully
The shape changes by project, but the principle stays the same: understand enough to avoid bad work, then move in small steps that reduce risk.
Orient
Map the system, constraints, people, risks, and business pressure before prescribing a solution.
Decide
Choose the route, make tradeoffs visible, and define what needs to be true for the work to succeed.
Ship
Deliver in small enough pieces to learn quickly without leaving fragile half-solutions behind.
Stabilise
Leave owners, measurements, documentation, and follow-up decisions in place after launch.
Technology is selected, not worshipped
We are comfortable across modern stacks, but the work starts with the problem, the team, and the operating constraints.
Not sure which service fits?
We can usually identify the right engagement shape quickly once we understand the systems, constraints, and business pressure around the work.