Fractional AI Architecture · Richmond, VA
I'm Will Cassell — a former SVP of data science & analytics who now builds AI systems hands-on. I find the business problem first, then assemble the AI, data, and automation stack that actually solves it.
Fixed engagement length
No open-ended billing
One process, end to end
Clients at a time
Fig. 00 — The terms, at a glance
01 — The Gap
Companies keep getting caught between the two: advice with no implementation, or implementation with no business judgment. The work that moves a P&L needs both halves in one head.
| Provider | Advice | Implementation | Owns the outcome |
|---|---|---|---|
| Strategy firmsDeck, no build | Yes | No | No |
| Dev shopsCode, no judgment | No | Yes | No |
| This practiceBoth halves, one head | Yes | Yes | Yes |
Years running data science and analytics organizations at the SVP level — budgets, org change, vendor selection, and the politics of getting new systems adopted rather than shelved.
Daily, hands-on work with LLM agents, voice systems, data pipelines, and workflow automation. When I recommend something, it's because I've already built a version of it.
02 — The Engagement
A fixed-fee, three-week engagement on one department or process. You leave with a ranked roadmap and a working pilot of the top opportunity — not a recommendation to go build one.
Interviews with your team and a workflow map of the target process: where time, money, and errors actually accumulate.
Every opportunity scored on ROI against feasibility — then I build a working pilot of the one at the top of the list.
A 90-day roadmap, the live pilot demo, and a decision-ready business case your leadership can act on immediately.
03 — Recent Builds
AI agents that place real phone calls and run structured interviews end-to-end — transcripts, scoring, and follow-ups landing in a database, no human dialing.
Conversational assistants that sit on top of an organization's live job and operations data, so frontline staff get answers without hunting through systems.
Data pipelines that turn messy public records into ranked, decision-ready intelligence — the kind of signal a sales or underwriting team can act on weekly.
Agent-driven automation across machines and services, with dashboards that make usage, cost, and reliability visible at a glance.
Live demos of each shown on intro calls.
04 — After the Audit
When the audit surfaces more than one thing worth building, I stay on as your fractional AI lead — owning the roadmap, building the pilots, selecting the vendors, and upskilling your team on a monthly retainer.
I hold two retainer seats at a time. That constraint is the point: you get a senior operator's attention, not a bench of juniors.
2 seats, total. Senior attention by design — never a bench of juniors.
05 — About
For 25+ years I led data science and analytics at scale — most recently as SVP of Data Science & Engineering at RDSolutions, and for fourteen-plus years a Director at Capital One, where I ran its bank-fraud innovation team. Those are the years where you learn that technology fails for organizational reasons more often than technical ones.
Now I work as an independent architect because I like the craft: finding the business problem, then personally assembling the AI, analytics, and automation blocks that solve it. CR Tech Lab is the practice that work lives under.
06 — Contact
Tell me what's slow, manual, or opaque in your operation. If there's a fit, we'll scope an audit in one call — and if there isn't, I'll tell you that too.
Book a callor email directly: wcassell@gmail.com