How a PR agency scaled SEO and content with 30+ AI agents

AI agents in production

30+AI agents in production

articles produced

1,000+articles produced

niche directory sites

3niche directory sites

to build, then ongoing

7 moto build, then ongoing

The agency had a problem every growing PR firm eventually hits: the work that wins clients — original research, technical SEO, and a steady stream of well-sourced content — is exactly the work that doesn't scale with headcount. This is how we turned that manual grind into a fleet of more than 30 production AI agents, running reliably enough to put in front of paying clients.

The client

A mid-size PR agency running content, SEO, and digital-PR programs for a roster of clients. Their differentiator was credibility: articles backed by real research, not filler — the kind of pieces that earn coverage and citations from major outlets like CNN and The Times. The problem was that this quality was entirely manual, and manual doesn't scale.

The challenge

Every deliverable competed for the same scarce analyst hours:

• Technical SEO across many client sites — audits, fixes, and monitoring — done by hand in spreadsheets.
• Research for every PR article, chasing primary sources and data to make each piece genuinely citable.
• Content production at a volume the team could never realistically staff for.
• Directory sites the agency wanted to launch in specific niches, each needing hundreds of quality listings.
• Competitor analysis that went stale the moment it was finished.

They didn't want a chatbot. They wanted the busywork to run itself — reliably, on-brand, and visible enough to trust with client work.

Our approach: a fleet, not a feature

Instead of one "AI writer," we built a fleet of specialised agents — more than 30 in production — each scoped to a single job and wired into the tools the agency already used. The design principle was boring on purpose: every agent does one thing, is observable, and hands its output to a human to approve rather than publishing blindly.

The whole fleet runs on the Stacx24 Runtime, self-hosted in the agency's environment, which gives every agent monitoring, cost control, memory, and governance out of the box.

Inside the fleet

Technical SEO agents

These pull live data from Google Search Console and Ahrefs, then surface and prioritise issues — crawl errors, thin or cannibalising pages, broken internal links, decaying rankings. They draft the fix — a rewritten title, a redirect, an internal-link plan — and route it to an editor. What used to be a monthly manual audit became a continuous, always-on process.

Research and content agents

The agency's edge is research-backed writing, so these agents lead with sources. Each grounds itself in authoritative references before drafting, so claims are backed rather than invented — the foundation for pieces that stand up to editorial scrutiny and earn citations from major publications. Editors review and approve; the agents handle the grind of sourcing, structuring, and drafting. Over the engagement the fleet has produced 1,000+ articles.

Directory-building agents

For three niche directory sites, agents research, structure, and populate listings at a volume that would be uneconomical by hand — turning a "someday" idea into three live properties.

Competitor-analysis agents

Instead of a one-off deck that's outdated on delivery, these agents monitor competitors continuously — content, keywords, backlinks, positioning — and keep a living picture the strategy team can actually act on.

The stack

The system is deliberately built on tools the team already trusted, with LLMs chosen per task:

• Claude and OpenAI models — stronger reasoning models for research and analysis, faster models for high-volume drafting.
• Google Search Console and Ahrefs for live SEO signals.
• The agency's headless CMS for publishing, Google Sheets as a familiar control surface, and Amazon S3 for assets and artifacts.
• The Stacx24 Runtime tying it together — the control plane that makes 30+ agents observable and affordable.

Keeping 30+ agents trustworthy

Running one agent is a demo. Running thirty in production is an operations problem — and it's where most "AI automation" quietly falls apart. Three things made it viable:

• Observability. Every agent run is traced end to end, so when something drifts it's visible, not a mystery.
• Cost control. The runtime meters spend per agent and per workflow, with budgets and alerts, so continuous operation stays economical.
• Human-in-the-loop and governance. Agents draft; people approve. Guardrails check tone, facts, and PII before anything ships.

That combination is the difference between a clever prototype and a system a PR agency will put in front of paying clients.

The results

Over roughly seven months — and continuing with ongoing support — the fleet has:

• Put 30+ agents into production across technical SEO, research, content, directories, and competitive intelligence.
• Produced 1,000+ articles, grounded in research rather than filler.
• Stood up three niche directory sites the agency couldn't have staffed manually.
• Turned technical SEO and competitor analysis from periodic projects into continuous, always-on processes.

Most importantly, it did this visibly: the agency can see what every agent did and what it cost — the trust that lets them scale AI into real client work instead of keeping it in a sandbox.

What's next

The engagement continues. New workflows get added to the fleet the same way the first ones did — scoped tightly, instrumented from day one, and expanded once they've earned it. If you're running a content, SEO, or digital-PR operation that's bottlenecked on manual work, that's exactly the kind of system we build.