Why teams call.
No one wakes up needing a fractional architect. They wake up with a specific, nameable problem. Below are the situations that most often prompt the first conversation — each one bounded enough for a single senior practitioner to take on directly.
The bill
The data layer costs more than it should, and the number is hard to defend.
The data platform bill climbs every quarter, and no one can say which workloads are driving it.
Typically→Data Layer Health AssessmentA multi-year Snowflake or Databricks renewal is coming, and there is no evidence base for whether the commitment is sized right.
Typically→Data Layer Health AssessmentData costs cannot be allocated back to the teams and products that generate them.
Typically→Data Layer Health AssessmentThe decision
A specific call has to be made, and it needs a defensible, independent answer.
A vendor has proposed an architecture, and the organization wants an independent read before it signs.
Typically→Architecture ReviewTwo internal teams are advocating different approaches, and leadership needs a defensible tiebreaker.
Typically→Architecture ReviewA data platform was inherited, and no one can say with confidence what is load-bearing and what is safe to change.
Typically→Architecture ReviewThe platform that pages you
It works, mostly — until it doesn't, and the failure modes have become routine.
Upstream schema changes keep breaking pipelines, and the patches have accumulated into a structure no one fully understands.
Typically→Fractional AI Data ArchitectEvery new data source takes weeks to onboard when it should take days.
Typically→Fractional AI Data ArchitectQueries have slowed to a crawl, and the cause is somewhere in a million small files no one has had time to compact.
Typically→Fractional AI Data ArchitectThe AI that won't survive production
The demos land. Production is another matter — and the data layer underneath is the reason.
The agent and retrieval demos work, but the data layer underneath them will not hold up in production.
Typically→Fractional AI Data ArchitectAn LLM is being wired into an operational workflow, and the patterns are being set without a designer in the room.
Typically→Fractional AI Data ArchitectThe board has asked for an AI roadmap, and there is no internal author for it.
Typically→Fractional AI Data ArchitectThe missing architect
The team is capable, but no one is holding the architecture — and it shows.
The engineers are strong, but there is no architect, and decisions are accumulating faster than the team can absorb them.
Typically→Fractional Solution ArchitectThe organization is between architecture hires and needs a steady hand for six to twelve months.
Typically→Fractional Solution ArchitectTechnical posture is invisible to the executive team — the board hears nothing it can act on.
Typically→Fractional Solution ArchitectIf your problem isn't here —
The list above is the common ground, not the boundary. If the problem in front of you is adjacent to this work — a data, cloud, or AI architecture question that needs senior judgment and a bounded engagement — the first conversation will tell us both quickly whether it's a fit. If it isn't, you'll get a straight answer and, where possible, a name worth calling.
When the right first move is evidence.
Several of the problems above are hard to act on because they are hard to quantify. The productized two-week Data Layer Health Assessment exists for exactly that — a defensible, written answer before any larger commitment.