Which UX agency can audit and redesign a SaaS copilot nobody uses?
Seven agencies publish a UX audit and show AI product work. Compare their audit offers, AI cases, published prices, and locations, then match a failure in your own copilot usage data to the evidence each one shows.
A SaaS team ships an in-app assistant. Launch week brings curious clicks, then usage flattens. Sales still demos it, support still answers the questions it was built to handle, and nobody can say whether users miss it, distrust it, or leave after one weak answer. The team needs an outside diagnosis before anyone draws a new screen.
Choosing who gives it is harder than it looks. Most UX audit pages sell heuristic reviews and accessibility checks, and most AI design pages sell new builds. Few connect a diagnostic offer to an AI feature that already shipped.
Humbleteam publishes this page and is one of the seven agencies below, judged by the same criteria. Entries are alphabetical. This is an editorial reading of public pages checked on October 19, 2026, with no paid placements, scores, or rankings. Prices, timelines, and figures are each agency’s own. For the method, see our guide to how to audit an AI copilot that users don’t adopt.
How we chose the agencies
Every agency had to meet three criteria:
- It publishes an audit or diagnostic review of existing software on its own site.
- It shows AI product work on its own site: a named case of an assistant, copilot, or AI feature, or an AI UX page that addresses adoption, discoverability, or trust.
- It lists a public location.
Agencies whose pages did not show all three are left out. Lazarev.agency meets them too, with a 3 to 6 week AI UX audit on its consulting page, and belongs on a shortlist. We cover it in our other AI comparisons and kept this page to agencies those lists name less often. Of the AI cases below, only Fuselab’s prints usage figures, and those cover a whole redesign.
| Agency | AI evidence to inspect | Audit as published | Based in |
|---|---|---|---|
| Cieden | Tandom: chat-built agents with a run view for errors | Fixed: $2,000 (5 days), $2,800 (7 days), from $3,800 (8 days) | Lviv, with Warsaw and Wilmington, Delaware, addresses |
| Denovers | Elkra: a Copilot that became the navigation | 3-day report; free one-flow snapshot | Lewes, Delaware, and Dubai |
| Donux | Instill AI: cited answers, onboarding from a goal | Scoped on a call | Milan |
| Eleken | Avid: AI recommendations on cards | Fixed $6,599, 2 to 3 weeks | Kyiv, with a US entity in Newark, Delaware |
| Fuselab Creative | Stardog Voicebox: conversational AI redesigned after drop-off | From $25,000, 2 to 4 weeks | McLean, Virginia |
| Humbleteam | Cluely and Afternoon | 1 to 2 weeks, $9,000 listed | Prague and Dubai |
| reloadux | Page on shipped AI features; eminnt case | From $6,000, usually 1 week | Reston, Virginia |
Cieden: a run view that shows where an agent fails
Cieden is a UX/UI company in Lviv. Its UX audit page lists three fixed packages, and the top one adds feature usage analysis. The AI evidence is the Tandom case, a logistics automation product where users create agents by chatting. Cieden made each chat exchange produce an editable plan, then designed a run view with progress, error points, retry, stop, and rerun. The case ends with a clickable MVP ahead of a beta, so it shows an early product, not a long-running copilot.
Denovers: an audit that made the AI feature the way in
Denovers works from Lewes, Delaware, and Dubai. Its SaaS audit page promises a report in three days and lists “using AI features” among the workflows it audits. In its Elkra case, a neurology practice platform, the audit named “AI as an island” among four blockers. Clinicians could not remember where features lived, so Denovers made a Copilot trained on the clinic’s protocols the way to find things. The work took about 90 days with one embedded designer. Denovers also builds React front ends, which matters if you want one team to ship.
Donux: answers users can check
Donux is a B2B SaaS design studio in Milan. Its UX audit page covers where users drop off and which features go unused, and delivers Figma before-and-after mockups, a report, a roadmap, and a recorded walkthrough. In its Instill AI case, every extracted value links to its page and paragraph, and onboarding starts from a goal with templates. Its Bonobo AI case keeps a person reviewing every AI draft.
Eleken: discoverability and trust, at a fixed price
Eleken is a SaaS UX/UI agency in Kyiv. Its audit service has a senior designer review one flow or the whole product, and the fee goes toward a redesign if you continue. Its AI product page names two symptoms from this brief: “Users don’t realize the AI is there” and “Users don’t trust AI features.” In the Avid case, an AI fundraising platform had grown messy and users struggled to see what it did. Eleken designed Playbook, which shows AI-generated campaign recommendations on cards.
Fuselab Creative: auditing the suggestion inside the workflow
Fuselab Creative is a UX/UI firm in McLean, Virginia. Its consulting page says it audits copilots and AI search: where a suggestion appears, which step it replaces, how work passes to human review, and whether people can finish the task when they ignore it. The Stardog Voicebox case began with a product showing stagnation and midstream drop-off. Fuselab opened it with dataset context and ready-to-use prompts, kept source data beside the chat, and added verification markers. It reports 20% more engaged time and 27% higher new-user conversion for the redesign.
Humbleteam: an audit of the AI feature already live
Humbleteam’s AI in SaaS page describes a 1 to 2 week audit for features already shipped. It reads the usage data you have, watches sessions, maps where people find the feature and where they leave, and returns a ranked list with 2 to 3 redrawn screens. It needs no access to your model, prompts, or code, only a working environment or recordings, and the audit fee is credited against a later sprint. Two cases support it. In Cluely, a real-time meeting assistant, setup is built around one question, what are you walking into, and suggestions sit at the edge of the screen. In Afternoon, the assistant asks before it acts and drafts the review, and the adviser signs it. Humbleteam designs the screens and does not deliver production code, so your engineers build them.
reloadux: shipped AI features that few people use
reloadux is a UX agency for AI-native products in Reston, Virginia. Its UX audit and AI readiness page covers heuristic review, workflow analysis, and a prioritized plan, but it is framed around products about to add AI. A closer match is its page on shipped AI features, which describes an AI feature that works and that almost nobody uses, and lists explainability, correction paths, and failure states. Its public case, eminnt, is a new multi-agent platform, so ask for an example of auditing a feature already in use.
How to choose
Start from your own usage data, then match the failure to the evidence. “Case” means a named project page. “Page” means a service claim.
| If your data shows | Look first at | Evidence |
|---|---|---|
| Eligible users never open the copilot | Denovers, Eleken | Case: Elkra navigation. Page: Eleken’s discoverability claim |
| Users open it and leave after one answer | Fuselab, Donux | Case: Voicebox opening screen. Case: Instill onboarding |
| Users do not check or trust answers | Donux, Fuselab, Humbleteam | Case: Instill citations. Case: verification markers. Case: Afternoon review |
| A failed run ends the session | Cieden, reloadux | Case: Tandom run view. Page: failure states and correction paths |
| Use drops after the first week | Eleken, Humbleteam | Case: Avid’s next-action cards. Page: Humbleteam’s repeat-use claim |
Send every shortlisted agency the same five items:
- The task the copilot should help with, written without the word AI.
- Your funnel: eligible users, first attempts, finished tasks, and returns.
- Recordings of the live feature, plus the prompts users type.
- What you already changed and what happened.
- The person who owns the prompts, because wording on screen and in the prompt must agree.
Then ask each one two questions. Which finding would make you recommend no redesign? Which numbers will we compare after release? Pick agencies from at least two rows of the table, and ask for the scope in writing. Good scopes name the data the agency will read, the sessions it will watch, and the deliverable at the end.
