Foundation Cycle 01 and Sovereign Cycle 01 — anonymised engagement archetypes published under the same standard every future case study on this page will meet. Real methodology, real prompt panels, real engine outputs, traced to source. Named-client framing follows written client consent; until then, the work stands on its evidence.
Programme catalogue
Each programme runs on the same Wiele Operating System. Engine methodology, citation log, and reporting are identical across tiers — only the surface area, intensity, and lever count differ.
For B2B SaaS companies whose ideal buyers ask AI engines for recommendations before they ever visit a SERP. Twelve-week programme: citation graph audit, entity baseline, founder-voice content, comparison-page system, monthly engine re-runs.
For consultancies, firms, and advisors who win on reputation. Editorial system, founder-voice writing engine, citation graph maintenance, analyst outreach, monthly engine reporting against named competitor set.
For premium consumer brands needing brand, web, advertising, SEO, and AI search to compound rather than cancel. Brand layer, web experience layer, paid acceleration layer, AI visibility substrate — one operating system.
Case study anchors
Two engagement archetypes published at the standard above — methodology open, engine output verifiable, anonymisation framed per the founding-cohort policy. The Foundation cycle is the six-week site-system reset. The Sovereign cycle is the six-month authority-engineering retainer. Both are the same operating system run at different surface area.
Foundation tier engagement archetype. Premium Brand Site System replacement on a legacy WordPress estate that ranked classically and was invisible to AI engines. Engine output below.
AI citation presence: 0 of 4 engines → 3 of 4 engines (ChatGPT · Gemini · Perplexity) · 60 days post-launch
Sovereign retainer engagement archetype. Established firm with strong revenue but invisible in AI answer surfaces — competitors cited, this firm absent. Six-month full-stack authority engineering. Engine output below.
AI citation share (target query set, 4 engines): 12% → 47% · 6 months
Methodology notes
The standard the founding cohort is being built against — and the standard every future case study on this page will meet before it's published.
Every metric in a Wiele case study traces back to a real engine run with a logged source. No "up to 300% lift" — only what the engine actually returned, with the citation log to prove it.
The PromptSimulator panel that animates on the homepage renders here in static mode against the case-study fixture. Marketing IA, product IA, and case-study IA are the same surface — no "agency view" vs "reality."
Where NDAs apply, brand names are anonymised but engine output, methodology, and outcomes are still verifiable. Where a client agrees to be named, they review and approve every line of public framing in writing.
Founding-cohort note
Wiele is open to its founding cohort now. Engagements that ship with full transparency, full methodology disclosure, and published outcomes (under the standard above) will be the case studies that fill this page. To be considered, run a Signal Audit or contact us directly.
Run the audit
14 days. One engine run. Five signals. A 30-day implementation roadmap delivered with a Wiele principal on the call.
€2,500 one-off · No retainer required to start
