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These are representative engagement patterns: the kind of messy technical situations Voodoo AI is useful for, and the practical shape the work usually takes. Client names are anonymised; the outcomes are real.
Representative AI & data pattern
Planning teams had useful data, but forecasts, exceptions, and procurement decisions lived across disconnected tools and manual judgement calls.
Start with data readiness, workflow ownership, and exception handling. Then connect forecasting outputs into the operational systems where decisions are already made.
“The forecasting workflow now connects directly into daily procurement decisions. We went from spreadsheets and guesswork to a system the planning team actually trusts.”
Representative cloud modernisation pattern
A critical estate needed modernising, but downtime, compliance, dependency risk, and unclear ownership made a simple migration plan unrealistic.
Design the target environment, map dependencies, move services in bounded batches, validate rollback paths, and introduce cost governance before spend becomes invisible.
“We'd been told a migration would take 18 months and cost a fortune. Voodoo AI showed us how to do it incrementally — services moved in batches, with rollback paths at every step. The business never noticed.”
Representative platform architecture pattern
A growing platform had become difficult to reason about: slow paths were unclear, releases felt risky, and new features touched too much of the system.
Identify the worst bottlenecks, make boundaries explicit, improve observability, and change the architecture in steps small enough for the team to absorb.
“Every release felt like a gamble. After the recovery work, we shipped three features in the time it used to take to ship one — and the team stopped dreading deployments.”
If the details are different but the pattern feels familiar, we can help work out the first sensible move.
Last updated: July 2026