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UX Audit + AI Readiness

A UX audit plus AI readiness review finds usability and IA gaps and whether your product can introduce AI features without breaking trust.

Part of Creation. This is the entry offer: high clarity, bounded scope, clear next step into redesign, MVP, or AI feature work.

Growth job: convert "we should fix UX / add AI someday" into a prioritised plan you can buy. Productized audits are how studios like Clearleft and regional peers (ReloadUX-style UX review SKUs) de-risk larger SOWs. We match that structure with Phoenux's product-studio lens.

Guessing is expensive

Stakeholders argue from screenshots. Product ships another feature on top of broken IA. Support tickets climb while churn reasons stay vague. Then someone mandates "add AI". On a product that already hides errors, skips empty states, and confuses permissions.

An audit does not fix everything. It tells you what to fix first and what Creation SKU to buy next. With evidence stakeholders can disagree productively about.

Who it's for

  • Product leads on a mature product with rising support load, stalled activation, or churn signals they cannot map to UX
  • Teams about to bolt on AI copilots, generators, or assistants and unsure what will break trust
  • Stakeholders who need evidence before funding a rebuild, modernization, or design system investment
  • Founders who want a second opinion before committing to a six-figure redesign SOW

Objections we clear

  • "Everyone has a different opinion about what is broken"
  • "We know UX is bad but not where to start"
  • "Leadership wants AI next quarter and the base product is already confusing"
  • "We cannot afford a full redesign, we need a ranked plan"
  • "Last agency audit was slides, not a roadmap"

What we tackle

Task friction and IA

Where do users stall, backtrack, or abandon? We trace critical journeys. Especially the ones that pay the bills: and name structural confusion, not vague "make it modern" feedback.

Missing states

Empty, loading, error, permission denied, partial success. Gaps that make products feel unfinished and make AI outputs harder to trust. We flag what eng has been inventing under pressure.

AI readiness (when in scope)

Can your product surface AI outputs with disclosure, recovery, and oversight? We score data surfaces, UX patterns, and governance gaps. Without promising ChatGPT rankings or citation hacks.

Buying path recommendation

The audit ends with a sequenced roadmap: what to buy next, in what order, and what to defer.

What you get

- Ranked findings with severity and user/business impact - AI readiness scorecard when relevant (data, UX surfaces, oversight, trust patterns) - Remediation roadmap sequenced for impact and eng capacity - Recommended buying path: sprint, redesign, modernization, system work, or AI feature UX - Playback session where findings can be challenged with evidence

Typical audit engagements are time-boxed (often on the order of a focused sprint). See Rates.

How it works

1. Access & goals: journeys that pay the bills, stakeholders, constraints, AI plans if any. *Deliverable: audit charter.* 2. Review: expert heuristic audit, product walkthrough, analytics/support signals where available, competitive patterns when useful. *Deliverable: raw findings inventory.* 3. Playback: ranked findings stakeholders can argue with. Not a performance. *Deliverable: findings deck or doc.* 4. Roadmap: quick wins, structural work, recommended Creation SKU and phasing. *Deliverable: remediation roadmap + buying recommendation.*

Engagement shapes

  • UX audit: usability and IA focus; AI readiness optional
  • AI readiness add-on: when AI rollout is the forcing function
  • Audit → sprint: fix quick wins immediately, then phase larger work
  • Audit → redesign / modernization: when structural debt is the blocker

Proof

Audits often precede work like Sendoso and Unlayer growth phases. Complex products where "what is broken" was contested before design started. Governata is the kind of dense data product where IA diagnosis pays before UI polish.

Where it leads

Fit / not for

For teams ready to act on findings. Not decorate a board deck. Not for audits commissioned only to justify a decision already made. Not for "guarantee #1 in ChatGPT" SEO theater.

Frequently asked questions

What is a UX audit?

A structured review of usability, information architecture, and critical journeys that produces ranked findings and a remediation plan, not vague opinions or screenshot nitpicks.

What does AI readiness mean here?

Whether your product's UX, data surfaces, and oversight patterns can support AI features without confusing users or eroding trust. We assess disclosure, recovery, permissions, and where AI should not be exposed yet. We do not promise AI search rankings or ChatGPT citations.

How long does an audit take?

Most audits are time-boxed like a focused sprint once access and goals are clear. Scope tracks journey count, AI depth, and how much evidence we can access. We confirm duration in the estimate.

Is an audit required before redesign?

No: but it is the fastest way to de-risk a large SOW when stakeholders disagree about what is broken. Skip it when the problem and journey scope are already aligned.

Do you need user research access?

Helpful, not always required. We use expert review, your analytics and support data, and product walkthroughs. And name gaps when user evidence is missing.

What deliverable format do we get?

Ranked findings, severity, roadmap, and a recommended buying path. Written so product and eng can plan sprints. Format fits your toolchain; the content is what matters.

Can you audit only AI readiness?

Yes, when the base product is relatively sound and the question is specifically "can we ship AI safely?" We still flag UX blockers that would break trust.

How is this different from a free heuristic review?

Depth, evidence, sequencing, and a buying recommendation tied to Phoenux Creation SKUs. Or an honest "you do not need us for this" when that is true.

Start with an audit

Tell us the journeys that matter, what is going wrong, and whether AI is in scope. We will propose a bounded audit with a clear deliverable list.

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