crail

Agent-era go-to-market services

We built Crail's agent-readiness methodology by scoring 100+ real vendors. We use the same lens to help software companies model what changes when agents — not just humans — evaluate, buy, and pay for their product.

Agent-driven marketing & AEO

Where you currently stand across ChatGPT, Claude, Gemini, and Perplexity for your category's buyer-intent queries, what's earning citations against you, and a prioritized content/structured-data roadmap. See our guide on getting cited by AI answer engines.

Agent-native pricing & access

Whether your pricing, self-serve signup, and API surface are actually usable by an autonomous agent doing the evaluating and buying — and what's blocking it if not. See our guide onpreparing for agent-driven payments.

Usage & buy-vs-build modeling

For teams deciding whether to build internal agent tooling instead of buying, or vice versa — a structured framework, not a sales pitch either way. See ourbuy vs. build guide.

How it works

  1. A short intake call to scope which of the three areas above (or all three) matters most right now.
  2. We run your product through the same agent-readiness methodology used across Crail's catalog, plus a cross-engine AEO check specific to your category's buyer-intent queries.
  3. A written findings report with a prioritized action list — not a generic audit template.

This is a new practice — we don't have published case studies yet. What we do have is the same public, versioned methodology (/methodology) we apply to every vendor on Crail, so you can see exactly how we'd score your own product before engaging us.