Grammar QA for content agencies running AI workflows

A content agency delivers 200 AI-assisted articles a month to clients. Before delivery, someone has to check every piece for grammar errors. Right now that person is a human editor running each article through a generic grammar checker that wasn't built for AI output — and still missing errors, because the complaint pattern is consistent: 'the writing might not use the best grammar' and 'it can occasionally fail to find grammar and is prone to grammatical errors.' The editor catches some. The client catches others. The agency looks sloppy.

This gap persists because grammar checking and AI content generation have been built by entirely separate product teams with no shared context. The grammar tool doesn't know that the text was AI-generated, doesn't know what style guide the agency promised the client, and doesn't know that the client is in Australia and finds American spellings unprofessional. Each piece of context lives in a different system — the project brief, the style guide doc, the AI tool — and no one has connected them.

Generic grammar checkers surface the same low-confidence suggestions a human editor already knows to ignore, adding noise instead of reducing it. What agencies actually need is a final-pass QA step that validates AI output against a client-specific style rule set — catching not just grammatical errors but register violations, Americanisms in British-English accounts, and vocabulary inconsistencies that make bulk AI content feel obviously machine-made.

This is a business because agencies run this QA step on every deliverable, forever. The volume is high, the cost of errors is client churn, and no editor wants to manually catch AI-specific failure patterns across hundreds of articles a month. The agency owner will pay to systematize it.

What to build

Build a batch QA workflow where content agencies upload AI-generated articles in bulk, attach a per-client style ruleset (English variant, banned words, tone flags, grammar strictness), and receive a structured error report with confidence scores — exportable as a CSV for editor review before client delivery.

Where to start

Start with agencies delivering content to clients who have explicitly specified British or Australian English, where the Americanism problem is concrete and documentable — you can show a client a list of flagged Americanisms in their last delivery, which makes the pain undeniable and the value immediate.

The hard part

Selling to agencies requires integrating into wildly varied delivery workflows — some use Google Docs, some use CMS direct uploads, some use Notion — so the first painful trade-off is deciding how narrow to keep the initial input format without losing too many early prospects.

How it makes money

Monthly subscription based on article volume processed per month, with a per-seat add-on for editor accounts who need to review and action the QA reports.