AI Leverage.
No Hype.
No Slop.
Practical AI implementation for marketing, content and SEO teams. Internal knowledge bases, RAG pipelines, content ops automation, prompt systems. The work that makes AI useful, not embarrassing.
We help marketing teams use AI — without becoming the reason AI gets a bad name.
The AI implementation market is split cleanly in two. One side sells agent-generated content at scale — the reason half the internet now reads like it was written by the same tired intern. The other side sells strategy decks about "AI transformation" that never ship a working system.
We do neither. We build small, specific, measurable systems that remove boring work from marketing teams so humans can spend time on the parts AI still does badly: voice, point of view, primary research, strategic judgment. Our clients ship fewer AI-generated articles — and more of the good ones get cited.
Concrete systems. Shipped. Owned by your team.
Internal RAG Knowledge Bases
A single LLM-searchable source of truth over your brand guidelines, past briefs, research, campaign archives and SEO history. New hires onboard in days, not months.
Automated Content Briefs
Turn a target query into a brief that contains the real buyer prompt, the current AI answer, the gap, the entity requirements and the schema spec — in under 60 seconds.
Editor Assistant Pipelines
LLM pipelines that handle the boring parts of editing — entity consistency, schema generation, internal link suggestions, fact-check flagging — and hand a clean draft to a human.
Market & Competitive Research Bots
Automated weekly analysis of how your brand, products and competitors are being cited across Perplexity, ChatGPT, Gemini, and Copilot. Deltas delivered to Slack.
Prompt & Policy Systems
Reusable, versioned prompt libraries with a tested evaluation harness — so your team stops copy-pasting prompts and starts running them like software.
EU-Hosted & On-Prem Deployments
DSGVO-compliant data flows, EU model endpoints, self-hosted open-weight models for sensitive workloads. Required for DACH and Swiss enterprise.
Pragmatic stack. No vendor religion.
We work with Claude, GPT-4/5 class models, Gemini, and open-weight models (Llama, Mistral, Qwen) where self-hosting makes sense. Orchestration in LangChain or LlamaIndex or plain Python depending on what the system actually needs. Vector storage in Pinecone, Weaviate, or pgvector. Automation glue in n8n, Make or custom workers.
Tool choice is driven by the problem, not the logo on the sales deck. If your team already lives inside Notion, Airtable, HubSpot or Contentful, we meet the system where it is.
AI Implementation — common questions.
Is this an AI content farm?
No. The opposite. We use AI for research, briefing, structured data, tagging and editing — so humans can spend time on voice, point of view, and primary research. Our clients ship fewer articles. More of them get cited.
What tools and models do you work with?
Claude, GPT-4/5 class, Gemini, open-weight models where appropriate, LangChain, LlamaIndex, Pinecone, Weaviate, pgvector, n8n, Make, Python. Tool choice is problem-driven, not vendor-driven.
Can we keep our data private?
Yes. EU-hosted endpoints, zero-retention settings, self-hosted open-weight models for sensitive data, DSGVO-compliant flows. Required for most DACH and Swiss engagements.
How long does an engagement take?
First working system usually in 3–6 weeks. We ship small and iterate. No 9-month "transformation programs."
Complete the picture.
Stop talking about AI. Ship something.
Free 45-minute scoping call. We'll tell you honestly whether a project is worth doing.