Superflow turns an agency's pre-launch QA checklist into AI agents that scan every page of a site for broken links, typos, and brand drift before a human signs off.
Every agency that ships client websites has the same expensive last mile. Before a site goes live, someone, usually a senior designer or a project manager, spends a day clicking through every page on every device, checking that links resolve, spelling is clean, brand colors match the client's guide, and images have alt text. Superflow's own on-site calculator puts that at 20 minutes of QA per asset, and for a studio pushing 300 assets a month at a $125-an-hour billing rate, that pencils out to over $105,000 a year spent looking for typos and broken links, work that either gets billed to the client or quietly eaten by the agency.
Superflow takes the checklist your team already uses for that pass, the Excel file or the Notion doc with a hundred-plus line items, and turns it into a set of AI agents that run those same checks against every page of a live or staged site. Point it at a site and it hunts for what a human reviewer would: broken links, spelling and grammar errors, missing alt text, brand color and font drift, accessibility basics, and SEO fundamentals. When an agent finds something, it doesn't drop a line in a spreadsheet. It pins a comment to the exact element on the live page, with a screenshot attached, so the note survives the next redeploy.
Findings then route through an approval chain: the internal team reviews first, and a link goes to the client, who can approve it from a phone with no account, no login, and no app, even behind SSO. Every review also feeds a memory layer, so the next project for the same client starts already knowing their brand rules and past corrections. Superflow's own FAQ is direct about what this replaces and what it doesn't: "AI does the first pass and catches the obvious stuff. Your team and your client still review the work and sign off." This is not a tool that ships sites unattended, it's one that shrinks what a human has to look at.
Pricing runs on a flat credit system rather than a headcount fee: one agent checking one page costs 10 credits, so three agents (broken links, spelling, accessibility, say) across a 50-page site burns 1,500 credits in a single pass. The Starter plan is free forever after a 10-day full-feature trial, with 60 credits a month, about six agent-page reviews. Growth runs $24 a seat per month billed yearly, or $29 month to month, with 300 credits (roughly 30 reviews) and unlimited projects. Scale is $28 a seat with 600 credits. Running low mid-month costs $20 for a 500-credit top-up, another 50 reviews, and packs roll over. Set that against the $105,000-a-year manual QA math above, or against Superflow's own named case study with the agency Wonderist, which reports 47 hours back a month and three fewer rounds of client feedback per project since adopting it. A five-seat Growth team runs about $145 a month. One avoided round of client revisions on a single project probably covers that.
The free Starter plan is a hook, not a workaround. Sixty credits a month is about six agent-page checks, fine for spot-checking a landing page, nowhere near enough for a real pre-launch audit of a multi-page site, so any agency doing this seriously ends up paying for Growth or Scale. The compliance pitch is also ahead of where the company actually is: the marketing page lists "SOC 2 Type II" under its compliance section, but the pricing FAQ says plainly that Superflow is "currently going through SOC2 certification," not finished with it. A healthcare or financial-services buyer who needs a signed SOC 2 report for procurement should ask for the actual document rather than take the landing page's word. And this isn't built for teams chasing fully unattended publishing. The whole design keeps a person in the loop on every asset, by intention, so if the goal is zero human review, look elsewhere.
Superflow's own FAQ says the quiet part out loud: the AI does not replace your reviewers, it replaces the version of your reviewers that used to spend a full day clicking through every page looking for problems that usually were not there.