Services

Four ways to get your AI spend under control.

Each engagement is independent and model-agnostic — I have no incentive to push any provider. Start with a diagnostic, or go straight to implementation.

01
Most popular

AI Cost Audit

2–3 weeksFixed scopeDiagnostic

A clear picture of where every token dollar goes — and a costed, prioritized plan to cut it.

  • Per-workload token mapping across your real production traffic
  • Model, architecture & pricing-tier review against current 2026 rates
  • Quantified savings roadmap, ranked by effort vs. impact
  • Self-host vs. API breakeven analysis where relevant
02

Optimization Sprint

4–6 weeksHands-onImplementation

We don't just recommend — we ship the cuts and prove them.

  • Model routing & cascading wired into your stack
  • Prompt caching and async batch tiers implemented
  • Prompt & output token reduction without quality loss
  • Before/after measurement so the savings are verifiable
03

AI-FinOps Advisory

Monthly retainerOngoingOn call

Keep efficiency from eroding as models, prices, and your usage change.

  • Model-selection guidance as new releases land
  • Price-change monitoring & quarterly re-benchmarking
  • Build-vs-buy and self-hosting decision support
  • A standing line to an expert for your engineering team
04

Team Workshop

½–1 dayEnablementRemote or on-site

Upskill your team on the seven levers — against your own workloads, not toy examples.

  • The full cost-optimization framework, hands-on
  • Live teardown of one of your production workloads
  • A reusable cost-modeling spreadsheet your team keeps
  • Practical playbooks for caching, batching & routing

Not sure which fits?

Tell me your monthly token spend and the workloads you're running. I'll point you to the right starting point — no pitch required.

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