A free Full Audit for our founding cohort

We're onboarding a small founding cohort in observability / monitoring and API / dev-infrastructure SaaS. Qualify, and we run your complete Full Audit (normally $2,500) at no charge — in exchange for an honest review and permission to publish the results as a case study.

Apply for a founding spot ↓ Get a free teardown first

Not ready to apply? See your AI-visibility gap first — no commitment.

Only 10 founding spots — a selected cohort of qualified DevOps / observability / API-infra SaaS (we pick where we can show a real result, not the first to click). Once it's filled the free Full Audit (a $2,500 value) closes — the short application below is how we check fit.

What you get

The complete Full Audit (AEO + SEO) — AI share-of-model + the full SEO foundation + a 30/60/90 roadmap — at no charge.
If you continue on a retainer, a locked founding rate — 40% off the then-current list price at the time of renewal — for 12 months from signup, then it steps to the then-current standard list. The discount is always measured against the list price in force at renewal, never against a price frozen at signing. Only 5 founding retainer rates — a separate, smaller pool than the free audits above.

What we ask in return

A short, honest written review once you've seen the work.
Permission to publish the outcome — anonymized by default. We publish an outcome for every founding client, including “no measurable change against the pre-registered metric”; that commitment is made in advance and is what makes the published wins mean anything. Being named is a separate opt-in you can withdraw at any time, and there is no perpetual or irrevocable licence over your name, logo or results.

Who qualifies

Early-stage B2B SaaS in DevOps / observability / monitoring or API / developer-infrastructure, with a real product and a website we can measure.

Apply to the founding cohort

A human reviews every application. Tell us who you are and why you're a fit — no call required.

Not ready to apply? Get a free teardown and see your AI-visibility gap first.

The transparency wedge

A method you can reproduce

pre-registered prompt sets with published hashes, run counts and a confidence interval on every figure, and null results published on the same terms as positive ones - as standing practice, not a one-off study

at least 10 runs per engine (12 by default), spent adaptively — more on high-variance engines, fewer on stable ones, never below a 5-run floor Every presence figure carries a Wilson 95% confidence interval. Share of model carries a percentile bootstrap 95% confidence interval in the paid audit, and a Wilson 95% confidence interval in the public AI Visibility Index — the method matched to the metric and named per product, both computed from the actual runs.

Confidence intervals are reported honestly wide and named per product: presence uses a Wilson interval in both products; share-of-model uses a percentile bootstrap in the paid audit and a Wilson interval in the public Index, whose pooled denominator is clustered - so those Index intervals are narrower than a cluster-corrected estimate would give, and we say so. We never narrow a CI to look more certain than the data is.

We publish our run counts, our uncertainty and our pre-registered prompt sets. Across the 8 providers we checked on 2026-08-02: run counts 4 of 8 verified; 4 not verified; uncertainty on published figures 2 of 8 verified; 6 not verified; the prompt set published with the results 0 of 8 verified; 8 not verified. The full comparison, with each vendor’s own wording →

That is the wedge: a number you can re-run and get back. See the full method →

Hold us to it, and hold the others to it too — the 12 questions to ask anyone selling AI visibility, each one answered here with a link.