AI Content

The challenge

Before

A digital marketing agency managing content for 12 clients was producing articles, social posts, and email campaigns manually. Writers were at capacity. Client content requests were backlogged 2–3 weeks. The agency was turning down new business because it couldn't scale production without hiring — a process that took months and added fixed overhead. Content quality was inconsistent across writers, and briefing writers for each client's brand voice took as long as writing the content itself.

• All content written manually — writers at 100% capacity with a 2-3 week backlog
• Turning down new client business due to production capacity constraints
• Brand voice briefing required per client per writer — significant overhead
• Content quality inconsistent across writers and content types
• No content performance feedback loop — writers didn't know what was working
• Social media content produced in one-off sessions — no batching or scheduling
• SEO briefs compiled manually from keyword tools — time-consuming for every piece

The solution

What we built

We built an AI content suite trained on each client's brand voice, content archives, tone guidelines, and target audience profiles. The suite handles long-form blog drafts, social media post batches, email campaign copy, and meta descriptions — producing first drafts that editors refine rather than writers create from scratch. An SEO brief generator pulls keyword data automatically. A content calendar with batch scheduling integrates with each client's social channels. Performance data feeds back into the system to weight future content toward formats and topics that drive engagement.

How the system flows

1. Client Brand Profile Setup→Tone Training→Sample Archive Import→Voice Calibration
2. Content Brief→AI Draft Generation→Editor Review→Client Approval→Publish
3. SEO Keyword Input→AI Brief Generation→Long-form Draft→Internal Link Suggestions
4. Social Post Batch→Platform Formatting→Scheduling Calendar→Auto-publish
5. Content Performance Data→Engagement Scoring→Topic/Format Weighting→Future Brief Optimization