Real-time fraud engine
A streaming risk layer that scores every transaction inline, before it settles — replacing a batch process that flagged fraud hours too late.
Six of the systems we’ve shipped and still stand behind. Client names are withheld under NDA — the work speaks for itself.
A streaming risk layer that scores every transaction inline, before it settles — replacing a batch process that flagged fraud hours too late.
A ground-up mobile bank — accounts, cards, payments, and support in one app — engineered to stay responsive past two million users.
An event pipeline and ML layer that forecasts equipment failure across an industrial fleet — turning unplanned outages into scheduled service windows.
We consolidated fourteen disconnected data sources into one modeled warehouse — cutting the time-to-answer for the whole company from days to seconds.
A retrieval-grounded assistant for a support team of three hundred agents — deflecting routine tickets and drafting the rest, with every answer traceable to a source.
We moved a monolith to a container platform on infrastructure-as-code — halving the cloud bill and dropping deploy times from an afternoon to minutes.
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