Agencies
AI Agency Operations OS
Connects agency onboarding, delivery, reporting and knowledge into one system with shared client data and approval rules (no sales or proposal agents).
Agencies
AI Agency QA
Every deliverable is checked against the client brief and brand guidelines before it leaves your team.
One off-brand color or missing legal line can undo weeks of good work in a client's eyes. AI Agency QA checks each finished deliverable against the client's brief and brand guidelines before it leaves your team, lists specific issues for fixing and clears the rest to move on. Borderline calls go to your named reviewer, who keeps the final say.
- Every deliverable checked against the client brief and brand rules
- Specific issues listed for fixing before delivery
- Borderline calls routed to your named reviewer
$2,900
20–30 working days
Optional maintenance $249/mo
What it is
AI Agency QA checks each finished deliverable against the client's brief and brand guidelines before it goes out, flags anything that misses the mark, brand colors, tone, required elements, and clears the rest to move forward. Issues are listed for fixing, and failed checks go to your named contact.
Why businesses buy it
Clients notice small mistakes more than big ideas: the wrong logo version, a missing disclaimer, copy that drifts from their tone. Each one costs a revision round and a little trust. Senior reviewers can catch them, but checking every color and required element by hand wastes their judgment on routine work. AI Agency QA does the repeatable check consistently, so reviewers focus on the calls that matter. The Scope Card sets the workflow, the connected systems and the test runs before you buy, so the commitment is clear.
Problems this solves
Off-brand colors or the wrong tone slip through to the client
Each finished deliverable is checked against the client's brand guidelines before it goes out. Mismatched colors, tone or missing elements are flagged as issues, so your team can fix them first.
Required elements from the brief get missed under deadline pressure
The workflow compares the deliverable with the brief's required elements, such as logos, disclaimers or calls to action. Anything missing is listed for fixing, and failed checks go to your named contact.
Senior staff spend hours proofing work that is already fine
Deliverables that pass the checks are cleared to move forward without waiting in a manual review queue. Senior reviewers can then give their attention to the pieces the workflow has flagged.
Internal review feedback is vague and hard to act on
Issues are listed one by one against the brief or guideline they break. Designers and writers get a clear fix list rather than a general note that something feels off.
A good fit if
Deliverables currently get a final look from a senior team member before they go out, and that review is starting to bottleneck around one or two people.
You have a written brief and brand guidelines for each client that a deliverable can actually be checked against, not just a gut-feel review.
You want a background check, no client-facing channel, that runs automatically once a deliverable is marked ready, flagging misses rather than approving everything by default.
You're comfortable with one workflow of up to twelve steps, including one AI decision step on whether a deliverable passes or needs a second look.
Not the right fit if
You need the content or creative itself produced, not a check on finished work. See AI Agency Content Engine.
You need the checked deliverable packaged and routed for client approval, not just the brief check itself. See AI Agency Delivery Agent, which can pick up right after QA.
You need new-client details and brand assets collected, not deliverables reviewed. See AI Agency Client Onboarding.
Your check needs more than three connected systems or a workflow longer than twelve steps. Add a note at checkout for a written Change Quote, or start from our Custom AI enquiry form.
How it works
- A deliverable is marked ready for review. Once your team flags a piece as finished, the QA workflow picks it up from your project tool or drive without anyone submitting it separately.
- It's checked against the client's brief and brand guidelines. Required elements, brand colors, tone of voice and anything specifically called out in the brief are checked against the actual file, not a generic style guide.
- Misses are flagged with specifics. Rather than a pass or fail, it names what's off, a missing required element, an off-brand color, wording that drifts from the approved tone, so the fix is clear.
- Clean deliverables move forward automatically. If nothing is flagged, the deliverable is marked cleared to proceed to whatever step comes next in your process, without waiting on a person to say so.
- Anything borderline routes to a person. The one AI decision step in the workflow is where it's confident enough to clear or flag outright, and where it isn't, it hands off rather than guessing.
- 20 test runs on your sample data confirm it catches the misses your team actually cares about before it runs on live client deliverables.
What you provide within 72 hours
Your portal lists these the moment you order. Delivery starts the working day after everything is in and your access is checked.
- The systems this check should touch, such as your project tool and client-facing drive, with admin or API access for each.
- A written description or short screen recording of how your team currently reviews deliverables before they go out.
- Five to ten real deliverables, with the brief they were checked against, so it learns what a real miss looks like.
- The person or team who should be alerted when a deliverable is flagged.
- Admin access and API keys for every connected system, shared by adding our team as a user or creating a key you control, never by email.
- Your business information (company basics, hours and brand voice), shared during intake.
- One decision-maker who can approve the check criteria and sign off at launch.
- An API key for your own AI model account (for example OpenAI or Google Gemini), created for this build with a spending limit.
The 72-hour rule. Send everything on your checklist, including access, within 72 hours of ordering so your build starts on time.
Timeline
Start
Intake verified, brief-check criteria and connected systems confirmed.
Weeks 1–2
The QA workflow is built around your brand guidelines and brief format.
Week 3
Project tool and drive connected with the right access.
Weeks 3–4
20 test runs on your sample deliverables, with results sent to you.
Week 4
Your review and two rounds of changes.
Go-live
Live, recorded handoff session, support starts.
| Option | Delivery time | Price |
|---|---|---|
| Standard | 20–30 working days | $2,900 |
| Express | 15–25 working days | $3,400 |
| Rush | 10–20 working days | $3,900 |
What you receive at handover
- AI Agency QA configured and running in the background in your environment
- One workflow of up to 12 steps, with its prompt and guardrail configuration
- Connections to up to three of your agreed systems
- A test report from 20 test runs on your sample data
- An admin guide and a recorded 45-minute handoff session
- 30 days of post-launch support
Expected benefits and how to measure them
- Can catch brand and brief mismatches before a client sees them.
- Helps senior staff spend review time where it matters most.
- Makes internal feedback more specific and quicker to act on.
- Client-returned errors
- Count deliverables sent back for brand or brief mistakes, from your project tool, for two months before launch and two months after.
- Proofing hours
- Compare hours logged to QA or proofing in your timesheets for four weeks before and after launch.
- First-pass check rate
- From the QA workflow's log, track how many deliverables pass on the first check each month and watch the trend.
Before you start: Note how many deliverables clients returned for brand or brief errors last quarter. Record roughly how many hours each week go into internal proofing.
These are things to track, not promised results. Outcomes depend on your data, your team and your market.
Running costs
The build price is one-time. Running AI Agency QA afterwards costs roughly $20 to $100 a month, covering the automation platform and AI model usage, billed directly in your own accounts as the number of deliverables you check changes.
AI usage during the build and testing is also billed to your accounts, so you keep ownership of every provider relationship. Nothing runs through us.
Ask about running costsCustom requirements
If you need something outside the Scope Card, add a note at checkout. You get a written Change Quote, and that work only starts once you accept it. Your original order runs on its normal timeline either way. Larger or bespoke projects go through the Custom AI request form instead.
Request a custom versionKeep it running
For this build we recommend monthly maintenance: monitoring, fixes, and a monthly allowance of change hours, enough for an updated brand guideline or a new check rule. It starts after the 30 days of support, bills monthly, and can be cancelled any month.
$249/mo (the minimum fee, includes 2 change hours)
Optional. Starts after the post-launch support period. Cancel any month.
How maintenance worksHow this compares
| Do it yourself with a SaaS tool | Hire a custom agency | Upmark Labs | |
|---|---|---|---|
| Price | A proofing tool bills per seat whether a deliverable ships that month or not | A senior reviewer's time checking every piece is billed as overhead | Ours is one fixed price, shown on this page before you buy |
| Scope | A proofing tool gives you generic checklists to configure yourself | The check depends on which senior person has time that day | Ours is written on the Scope Card before purchase |
| Consistency | A proofing tool checks format, not whether the brief was actually followed | Consistency depends on who reviewed it and how rushed they were | Ours checks every deliverable against the same brief and guidelines |
| Delivery | Sign-up is instant, teaching it your real brand rules is not | Training a reviewer to catch what matters takes months | Ours has a fixed delivery time shown before you buy, with faster options |
Questions about this product
How much does AI Agency QA cost?
The one-time build price is shown in the price and delivery panel on this page, next to each delivery speed. It covers everything on the Scope Card: the check workflow of up to twelve steps, up to three connected systems and 20 test runs completed before launch. That price holds once your Scope Card is confirmed.
How is AI Agency QA different from AI Agency Delivery Agent?
QA checks a deliverable against the client's brief and brand guidelines before it is marked ready. AI Agency Delivery Agent picks up after that, packaging the approved asset, routing it to the client and tracking revisions through sign-off. QA sits earlier in the process, and Delivery Agent handles the handoff that follows.
Does AI Agency QA replace our senior reviewer?
No. It handles the repeatable part of the check, comparing a deliverable against the written brief and brand guidelines, flagging specific misses rather than a vague pass or fail. Anything borderline routes to a person, so your senior reviewer spends their time on judgment calls instead of checking every color and font by hand.
How much does AI Agency QA cost to run each month?
Roughly $20 to $100 a month in your own accounts, covering the automation platform and AI model usage. The figure moves with how many deliverables you check each month. You pay providers directly. The one-time build price is separate and shown in the price and delivery panel on this page.
How long does AI Agency QA take to launch?
The price and delivery panel on this page shows the time for each speed, counted from the day your intake is complete and access is verified. Most of the build goes into teaching it what your team actually flags as a miss, using five to ten real deliverables and the briefs they were checked against.
What does AI Agency QA need from us to check deliverables properly?
It needs admin or API access to the systems your deliverables move through, such as your project tool and drive, plus five to ten real examples with the brief they were checked against. Admin access and API keys are shared by adding our team as a user or creating a key you control, never by email.
Can I add a new check rule later?
Small changes, such as an updated brand guideline or a new required element, fit inside the monthly change hours that come with maintenance. A workflow beyond the twelve steps in scope, or a fourth connected system, gets a written Change Quote first.
What happens when AI Agency QA finds a problem?
It flags the specific miss, a missing required element, an off-brand color, wording that drifts from the approved tone, and routes the deliverable to the person you named instead of quietly holding it back. Clean deliverables move forward automatically, so your team's attention goes to the ones that actually need it.
Stop letting off-brief work slip through to clients.
Order AI Agency QA and every deliverable is checked against the client's brief and guidelines on a fixed delivery date. The scope above is what you get, in writing, before you pay.
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