I lead Data, BI & AI at Spark Maxx, and there's only one bar here: systems in production. 15+ so far: dashboards, autonomous agents, analysis and local AI, each one documented on my portfolio with the problem, the decision, the architecture and what the choice cost.
Beyond that, I work as a fractional CAIO (Chief AI Officer) for selected companies: the executive function that owns AI strategy, governance and implementation, without the full-time seat. Open to B2B remote contracts (BR/US/Global).
Context before model. A powerful model without context is wasted potential, so I treat context as infrastructure: every project carries living documentation that AI reads before acting. It's how 15+ simultaneous systems fit one person.
Production is the bar. Every case is written as problem → decision → architecture → what the choice cost. A write-up is only done when the trade-off is stated.
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Has your data problem outgrown the spreadsheet? → victordataengineerds@gmail.com