Agent Readiness Audit

A diagnostic engagement. I work through your actual workflows, rank the AI-workflow opportunities, and deliver a concrete recommendation for the top candidate(s) — which may be a custom-built agent, an off-the-shelf vendor product configured into your stack, a hybrid, or don’t build this. The recommendation is detailed enough to scope a real engagement, and the readout includes a go/no-go. The output answers where should we start with AI workflows, and is it worth it? — grounded in what you actually run.

What you get

• Written report (PDF + Markdown) — your workflows ranked, the top candidate(s) recommended, and the reasoning behind both. Page depth scales with the engagement.
• Workflow opportunity ranking — every workflow we surface, scored on automation potential × business impact, in one table you can take to a budget conversation.
• Recommendation(s) on the top candidate(s) — each one of: an architecture sketch for a custom build, a vendor evaluation (which vendor, why, integration approach, cost), a hybrid, or an explicit don’t-build with reasoning.
• Tooling recommendation memo — which LLM, which orchestration approach, which vendor products belong in the stack.
• Go/no-go recommendation with the reasoning written out, so you can defend the decision to a board or a budget owner without me in the room.
• 60-minute live readout plus a recorded video walkthrough (~15 min) you can share internally with stakeholders who missed it.
• Source artifacts — workflow map, scoring sheet, intake survey responses, every diagram. Delivered as a zipped folder.

How it works

Four phases over one to two weeks, sized to the engagement. Updates land async (shared doc + short recorded walkthroughs) between phases so your team can react without meeting overhead.

Who it’s for

• You run an ops-heavy company (20–500 people) and you’ve watched at least one workflow eat hours every week.
• You have a budget owner who can sign off on $5k–$12k for a diagnostic without a procurement cycle — typically a director, VP, or CTO at a series A–C company.
• You want a defensible decision — build, buy, configure, hire, wait, or skip — not another generic AI strategy deck.
• You’d rather pay for a concrete recommendation (custom architecture, vendor evaluation, or hybrid) than spend six weeks evaluating options on your own.

Not the right fit if

• You want a one-day workshop deliverable — not enough surface area for real work.
• You’re not ready to commit budget to a follow-on engagement (custom Build or vendor configuration) if the audit recommends it.
• You’re looking for a multi-vendor comparison matrix across every LLM on the market — the audit names a single stack with reasons.

What it costs

Starting at $4,800. Scoped per engagement.

Typical engagements run 1–2 weeks at $4,800–$12,000, depending on the breadth of your workflow surface and the depth of recommendation needed for a defensible go/no-go. The exact price and duration are confirmed in writing before kickoff, once the scope is clear from the intake survey and discovery conversation.

There are no pre-defined tiers to choose from — what you get is shaped by what you run.

Payment: full fee due at kickoff via Stripe. Work starts when payment clears.

What’s not included: LLM API costs and vendor subscriptions (none expected during the audit; any pilot calls land on reflecttech), infrastructure costs (none expected), post-report changes outside the agreed scope (additional workflows scored, additional recommendations) — billed at $300/hour or rolled into a Build.

What happens next