Case Studies — All client work under NDA

Systems in production, and the numbers they actually produced.

Aigeniy publishes case studies in two forms: full write-ups where the material can be shown, and short anonymised outcomes where only the result can be disclosed. Client names and logos are withheld under NDA; first-party projects are named. Numbers are reported as measured, with dates, and are not rounded up.

full write-ups: 2 — 1 first-party, 1 client under NDA
anonymised outcomes: 3 — result disclosed, client withheld
disclosure: NDA by default · first-party projects named
numbers: as measured, with dates · not rounded up

Full write-ups

Two projects, shown from the inside.

One is our own site, so the forensics are published in full. The other is client work under NDA: the names are withheld, the architecture is the story.

Real Estate · Thailand · First-party project

Google Suppression Recovery

Recovering

after algorithmic suppression

Our own programmatic real estate platform, thailandproperty.org, was hit by a Google scaled-content suppression in April 2026 — indexed but invisible, no manual action. We ran a full forensic audit, traced every content symptom to a pipeline root cause, and rebuilt the publishing system with hard source-validation gates. Impressions have been climbing since late June. Published while recovery is in progress — no inflated numbers.

stack · n8n · Next.js · GSC Forensics

Performance Media · LATAM

Multi-Brand Publishing Platform

production sites, one codebase

A LATAM performance media operator needed dozens of branded sites — with an ambition of hundreds — without maintaining a fleet of codebases. We built a platform where a new brand is configuration, not code: one monorepo, environment-driven branding, a five-stage automated content pipeline with es-419 localization, and full infrastructure handover to the client's own team.

stack · Next.js Monorepo · n8n · Supabase

Anonymised outcomes

Results that can be disclosed without the client.

Production systems delivered under NDA. What each one changed is public; who it was built for is not.

20x

publishing speed

AI Content Pipeline

The client operated a high-traffic Fintech blog requiring constant content output to maintain search visibility. Manual production created a bottleneck — publishing cycles took days and legacy articles degraded in performance after each Google core update. We designed and deployed a fully automated content pipeline built on n8n and enterprise LLMs, covering ideation, drafting, structured formatting, and publishing. A parallel workflow continuously audited and re-optimized existing articles against updated search structure standards.

400+

listings/day

Real Estate Data Intelligence

A real estate operator needed reliable, up-to-date availability data across multiple developer projects — manually checking listings was slow, error-prone, and unscalable. We built an ingestion and normalization pipeline: incoming listing data passes through an LLM normalization stage and lands in Supabase as structured, queryable records — 400+ listings a day, available in real time instead of after a manual check.

Real-time

monitoring

Competitor Link Intelligence

The client lacked visibility into competitor backlink strategies, making it difficult to prioritize link-building efforts and respond to market shifts. We built an automated monitoring system on n8n that continuously tracked competitor domains, extracted link authority signals, and delivered structured reports on a scheduled basis.

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