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Case study · AI SEO agents
A multi-agent AI SEO system that compounds organic growth
We built a team of AI agents — discovery, keyword scoring, drafting, and verification — that write and optimize content across a large catalog, wrapped in deterministic guardrails so nothing unverified ever ships. AI does the volume; engineering keeps it honest.
The challenge
Hundreds of pages, one team, zero room for AI hallucinations
A B2B e-commerce catalog with hundreds of SKUs needs unique, accurate, well-optimized copy on every page — product descriptions, category text, metadata — kept fresh as the catalog changes. Doing that by hand doesn't scale. But letting a language model write freely across a commercial catalog is worse: a single invented spec, wrong compatibility claim, or fabricated certification is a real liability, not a typo.
So the brief wasn't "use AI to write SEO content." It was: get the volume and speed of AI, with the accuracy and safety of engineering — a system that writes at catalog scale but is structurally incapable of shipping an unverified claim.
How it works · AI agents
A pipeline of specialized agents, not one big prompt
Instead of a single model doing everything, the work is split across focused agents — each with one job, its own checks, and a hand-off to the next. A human owns approval where it matters.
Discovery & research agent Reads your data
Parses the live product database and current site, pulls Google Search Console performance, and maps what already exists against what's ranking. It builds a working picture of the catalog — every SKU, its attributes, its current SEO state — so nothing downstream is guessing about the product.
Keyword & opportunity scoring agent Rules + AI
Combines a rule-based keyword engine with model reasoning to score every page 0–100 on opportunity — search demand, intent match, current rank, and effort. High-value gaps rise to the top, so the system works the pages that actually move traffic first instead of rewriting everything blindly.
Drafting agent Grounded generation
Writes product and category copy, titles, and metadata — but only from verified product data. It's grounded to the database, not free to improvise: it can phrase, structure, and optimize, but it can't introduce a spec, compatibility, or claim that isn't in the source of truth. Multilingual-safe, so translated catalogs stay consistent.
Guardrail & validation agent Deterministic
The safety layer — and the reason this is engineering, not a demo. Deterministic rules validate every draft before it can ship: unverified claims are blocked, values are checked against the verified-data boundary, translation integrity is enforced, and anything ambiguous is held. Not "the model usually behaves" — code that says no.
Verification & publish agent Human-in-the-loop
Runs an audit-mode diff of exactly what will change, so a human approves with full visibility, then handles import/export with export verification — confirming what actually landed on the site matches what was approved. Nothing ships silently; every change is accounted for.
Monitoring loop Search Console
After publishing, the loop watches Search Console — impressions, clicks, positions — and feeds movement back into the scoring agent. The system compounds: this month's wins reveal next month's opportunities, and the pipeline keeps working the catalog instead of running once and stopping.
Why it's safe
AI writes. Engineering verifies.
The difference between a content-spam generator and a production SEO system is the guardrails. Ours are deterministic — rules, not vibes.
What the system guarantees
Every claim traces back to verified product data — no invented specs or compatibility.
A human approves changes with a clear before/after diff (audit mode).
Export verification confirms the live site matches what was approved.
Multilingual integrity — translated pages stay consistent and safe.
What it will never do
Publish an unverified or fabricated claim to a live product page.
Ship changes no one reviewed or can trace.
Mass-generate thin, duplicate copy just to fill pages.
Drift silently — every run is scoped, logged, and reversible.
The outcome
Compounding organic growth over 12 months
Figures below are from the anonymized case dashboard — representative of a 12-month organic-growth engagement.
+112%YoY
Organic clicks
2.41M+58%
Impressions / mo
428+214
Keywords in top 3
612
Pages optimized
74
Featured snippets won
Interactive — try the segments and charts above
Growth trend, keyword-rank distribution before vs after, market segments, winning queries, and optimization coverage — the same view the client sees. Open it full-screen for the full experience.
We run this on ourselves
The same approach, applied in parallel to our own SEO
This isn't a one-off deliverable we walked away from — it's a live practice. We run the same agent-driven, guardrailed SEO approach on our own site and content in parallel: entity-first, answer-first pages built to win both classic search and AI answers, with the same discovery → score → draft → verify loop. When we recommend it, it's because we're doing it ourselves.
Tuned to your catalog
The rules engine and scoring adapt to your products, data model, and market — it's not a generic content mill.
Fits your stack
Connects to your CMS or store and Search Console, with import/export verification so publishing stays safe.
Get started
Want AI-driven SEO you can actually trust?
Tell us about your catalog and goals — we'll scope how an agent pipeline would work for you, with the guardrails baked in.
Book a discovery callAnonymized case study. Client details are confidential; figures are representative of a 12-month organic-growth engagement.