Work.
What we've built for enterprises.
And for ourselves.
Selected case studies
3,000 SKUs narrowed to one recommendation.
Agents need this logic — it's currently locked behind a JavaScript UI. We built an AI-powered product finder that guides users through complex filtration requirements to the exact right product.
3,000 SKUs with complex compatibility rules. Customers can't self-serve, sales reps need deep product knowledge.
Conversational AI product finder that understands filtration requirements, vehicle specs, and application context.
Self-service product selection. Reduced support load. Foundation for agent-accessible product logic.
AI Product Finder
Ski selection based on rider profile.
Complex compatibility logic made conversational. From body measurements, skill level, and terrain preference to the perfect ski — without a 40-page catalogue.
Ski selection requires matching rider weight, height, skill level, terrain, and snow conditions against product lines.
Conversational product finder that translates rider profile into precise ski recommendations with reasoning.
Higher conversion in online shop. Reduced returns. Better match quality than manual selection.
AI Product Finder
Context that persists across sessions.
An AI companion that remembers where the user left off. Not a chatbot — a persistent working partner that builds understanding over time.
Every AI session starts from zero. Users re-explain context, lose thread, waste time re-establishing where they were.
Session-persistent AI companion with memory architecture. Picks up where the user left off, builds cumulative understanding.
Dramatic reduction in context-setting time. Users treat the AI as a working partner, not a tool.
AI Companion
AI companion for complex consumer decisions.
Guiding users through high-consideration purchases with contextual intelligence and personalised recommendations.
High-consideration consumer decisions require deep product understanding and personal context.
AI companion that learns user preferences and guides through complex decision trees conversationally.
Improved conversion rates and customer satisfaction through personalised guidance.
AI Companion
Full buyer context before the first call.
Sales team sees the complete journey. Every touchpoint, every document downloaded, every question asked — surfaced before the conversation starts.
Sales reps enter calls blind. Buyer history scattered across CRM, website analytics, and email threads.
AI-powered sales enablement that aggregates buyer journey into a pre-call briefing with context and talking points.
Sales team enters every call prepared. Shorter sales cycles. Higher win rates on complex deals.
Sales Enablement
Our own hybrid organisation. Agents alongside experts, autonomous 24/7.
Our own organisation as proof. We run what we sell — a hybrid organisation where AI agents handle structured work so humans focus on judgment and relationships.
A small expert team with enterprise-grade workload. Expert time consumed by reporting, inbox, pipeline management.
A named AI agent fleet (Lola, Cody, SM3CB, Martin, Giorgio, Vera, Joerg) operating 24/7 across sales, product, strategy, and operations.
~40% of expert time is structured routine — agents now handle 60%+ of it. Morning briefings, pipeline intelligence, overnight deliverables, all autonomous.
Hybrid Organisation
520 queries. 10 brands. 4 AI platforms.
Hyperize — our venture for agent visibility. Understanding how AI platforms recommend — or ignore — brands when users ask for products and services.
Brands have zero visibility into how AI agents recommend products. Even brands cited 86% of the time when named get zero citations the moment the query goes generic.
Platform that tracks brand visibility across ChatGPT, Gemini, Perplexity, and Claude for real purchase queries.
Brands see exactly where they're invisible to AI agents — and get a roadmap to fix it.
Agent Experience
Your use case is next.
We start with a workshop — half a day, three roles, one concept paper. No pitch decks.
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