Bespoke
Agent Readiness

Where it sits

This is not answer engine optimization under a different name, and the two are bought for different reasons.

• SEO decides where you rank in a list of links.
• Answer engine optimization decides whether a model names you when someone asks a question.
• Agent readiness decides whether an agent can act on what it found once you are named.

Being named in an answer is worth little if the agent then cannot resolve your pricing, cannot tell what you integrate with, and moves on to the vendor whose documentation was cleaner. The two services are usually bought together, and each is useful without the other.

What you get

• Twenty to fifty buyer-intent prompts run across the major AI engines, and a written record of what they say about your business today — including where they get your pricing, positioning or comparisons wrong
• A protocol-layer scan interpreted rather than handed over, separating what applies to your business from what does not
• Crawler access reviewed at both the robots and the edge layer, including the multi-purpose crawler trap that can cost you traditional search
• A machine-readable source of truth: llms.txt, content signals, agent-aware link headers, and structured data that agrees with your visible copy
• Pricing, comparison and use-case pages rewritten so an agent can extract a fact rather than infer one
• Customer proof organised by segment, and FAQs written as buyers actually phrase them
• Optional monthly re-run of the same prompts and the same scan, tracked over time

How it works

1. AuditRun the prompts. Run the scanners. Read the crawler logs. Two questions get answered: what do AI engines say about you today, and what can an agent actually fetch when it arrives.
2. InterpretA scanner returns red for things that do not apply to you. It cannot tell the difference between missing and deliberately not implemented. Separating those is the work, and shipping the entire checklist is not the goal.
3. ImplementThe base build: crawler access, machine-readable source of truth, structured pages, extractable answers. Anything requiring a genuine tool surface gets scoped separately.
4. MonitorOptional and ongoing. Model behaviour drifts, and platform defaults change without notice — as Cloudflare demonstrated in September by blocking agent traffic on sites whose owners never touched a setting.

What we never claim

Shipping this stack does not guarantee citations, referrals or ranking, and we will not tell you otherwise. Google’s own search documentation states you do not need machine-readable files to appear in generative AI search. The most rigorous causal study on structured data and AI citations, across 1,885 pages, found no significant uplift.

What the work demonstrably does is narrower and still worth buying. It reduces the cost of reading you for the agents already arriving — Cloudflare measured 31% fewer tokens and 66% faster agent responses across its own documentation after this work. It removes the failure modes that make an agent give up and recommend someone else. And it puts the infrastructure in place before the systems that will use it arrive.

There is no forcing function here yet. HTTPS had browser warnings; agent readiness has nothing equivalent. We think the schema.org precedent applies — niche in 2012, table stakes by 2017, foundational by 2025 — but a precedent is not a guarantee, and anyone selling you certainty on this is selling a product.

Who this is for

Businesses whose buyers already run AI tools against the web: B2B software, professional services, technical products with documentation, and anyone selling into a procurement process that has started using assistants.

If your audience is offline, or your site is five pages that never change, we will tell you to wait. That conversation costs you thirty minutes and saves you an engagement.

In practice: a procurement agent asked to shortlist vendors in your category quotes your pricing correctly, resolves your integrations, and represents your terms accurately — instead of stalling on a PDF and recommending the competitor whose documentation was easier to read.

Questions