Sitting on AI pilots that never shipped? I'm the operator-engineer who finds the one system worth building, puts it into production, and proves it moved the P&L.
Available now for fractional AI leadership · or a permanent Head-of role
“He can ship the engineering and own the number it moves.”
I build the production AI a business runs on, and I run the business it's built for. Most engineers optimise the system in front of them. I get to choose which system is worth building, because I'm also the one reading the P&L it feeds.
Every other hire is a handoff. Strategy passes to a PM, who passes to an engineer, who passes back something nobody measured against the P&L. I'm all of those people. One head decides which system is worth building, builds it, and owns whether the number moved. Nothing gets lost in translation, because there's no translation.
The things founders actually say to me, and how I fix each one. Hover or tap a card.
Two sides of the same job. I build it, then I run it.
Production AI, not demos. And I prove it works.
I carry the number, not just the code.
I run the business and build the AI it depends on, from the same desk.
I think in the numbers that run a business, and build the AI that moves each one. Leads → conversion → value → margin → profit.
I connect the systems a business already runs on, and put one AI layer across them.
Depth isn't ten projects named. It's one, shown completely.
The retrieval engine behind day-to-day operations was nearly blind: about 0.05 recall. It didn't need a bigger model. It needed someone to measure it and admit it was failing.
So I rebuilt retrieval as a hybrid system (vector plus keyword, with reranking) and engineered it to trustworthy, not just plausible. The model was the easy part; the measurement was the job.
Recall@5 went from ~0.05 to ~0.85 on a hand-labelled golden set, now regression-gated in CI, with a human-in-the-loop critic that refuses to auto-trust new facts. Under board review and external audit, that's not optional; it's the build.
I run production AI where wrong outputs carry real financial and legal weight, under board review and external audit. Governance isn't a slide; it's how I already work.
Every prompt or model change runs against a golden set; CI aborts on a regression before it reaches anyone.
Responses cite the source records they came from, not the model's memory, so they're checkable.
The system flags; a person approves anything consequential. Every automated decision is logged and traceable after the fact.
Production systems in daily use. Figures banded for confidentiality.
An organisation-wide retrieval system that turns scattered business knowledge into grounded, cited answers: Postgres + pgvector, hybrid retrieval and reranking, an automated eval harness and a human-in-the-loop critic gating what's trusted.
Co-pilots in daily use by leadership: cashflow forecasting, an operations risk co-pilot, and marketing-attribution dashboards.
A central pricing engine as a single source of truth, powering AI-assisted instant quoting and self-service booking.
An idempotent, rate-limit-aware layer connecting CRM, field-service, finance and e-sign, replacing a fragmented manual process with automated, gate-based tracking and one live control panel.
Built the unit-economics model and board-level monthly management reporting; restructured incentives and helped take the business from owner-dependent to system-led.
What hiring me actually buys: a diagnosis, a shipped system, and a number that moved.
I read the numbers before I touch the stack. Where's the money leaking, and which single lever moves profit most? You get a diagnosis of the binding constraint, not a tool wishlist.
One production system, built at that lever and measured against a baseline: the first automation live and real hours handed back to the team.
Evals, guardrails and a repeatable cadence, so it keeps working after I stop watching it: a measurable quality number on every change, not a demo that quietly rots.
I audit your stack and your P&L and hand you the one system worth building first, fully spec'd and costed. Fixed fee. You keep the roadmap whether or not we work together after.
One loop, owned end to end: decision to P&L.
Golden-set evals, regression checks and grounding gates: reliability is measured, not assumed.
Every build starts from the business outcome and has a number it's meant to move, and I own whether it moved.
Owner-dependent → system-led: documented processes, governance and automation so nothing depends on one person.
Hands-on from model to production.
The cost isn't the AI. It's standing still while your competitors compound.
Every quarter, the businesses that adopt this get a little faster, a little cheaper, a little harder to beat. The real risk isn't a failed AI project. It's the efficiency gap that opens when they move and you don't. I close that gap, and keep it closed.
“Charlie built and runs the AI and systems our business depends on: instant quoting, forecasting, and the board reporting they feed. He's the rare person who can ship the engineering and own the number it moves. Genuinely transformative for how we operate.”
Available for fractional AI leadership and a fixed-fee diagnostic, and open to permanent Head of AI & Operations / AI & Automation Lead roles for the right team.