Eight agents where we prove our approaches
This is a showcase of the studio's competence, not a separate consumer product. Each agent here is a complete working system: dialogue, memory, external data sources, answer control. An approach is proven here first, with live users and real requests, and only then moves into a corporate environment where the cost of a mistake is different.
Agents for personal tasks
They open from a link, with no installation and no sign-up. If you want to see what the same loop looks like on a corporate task, that is the Catalog section and Phase 0.
TravelMate AI
Trip planning: route, accommodation, events and weather in a single conversation.
Open the agentFitCoach AI
A personal fitness coach: a programme matched to your goal, fitness level and available equipment.
Open the agentDayPlan AI
Day planning: priorities, a realistic schedule and protected time for what matters.
Open the agentGiftGenius AI
Gift selection: the agent works through the occasion, the relationship and the budget instead of listing a top ten.
Open the agentNutriChef AI
A personal nutritionist: a diet built around your goal and restrictions, with calculations and a shopping list.
Open the agentHobbyFinder AI
Hobby selection based on temperament, budget and how much free time you actually have.
Open the agentAI tutor
English: speaking practice, error analysis and explanations pitched at your level.
Open the agentAI stylist
Outfit and clothing selection based on your wardrobe, the occasion and what actually suits you.
Open the agentThe enterprise side
If you are after a rollout into a process with a measurable effect rather than a demonstration of what is possible, this is where to start.
Enterprise agents and MCP services
Seven agents in a working loop and eight MCP libraries — everything already deployed and reachable by link.
Prove the value in four weeks
One painful process, a prototype on production data, an effect assessment and a rollout plan in board-ready form.