AI Buddy
Agentic Workforce Learning
Problem: Enterprise knowledge is fragmented across documentation, learning systems, and operational know-how, which slows onboarding and weakens execution consistency.
Approach: Use an agentic learning assistant that combines role-aware retrieval, guided learning paths, and feedback loops tied to internal sources of truth.
Architecture: RAG pipeline, identity-aware policy layer, enterprise content connectors, usage telemetry, and orchestration services for guided learning workflows.
Impact: Faster capability ramp-up, better reuse of internal knowledge assets, and clearer governance over how AI is used in workforce enablement.
Grüetzi
Local Service Orchestration
Problem: People looking for local services often face fragmented directories, low trust, and poor matching between intent and provider capability.
Approach: Model local discovery as an orchestration problem: capture need, context, geography, and quality signals, then route users toward relevant providers.
Architecture: Intent parsing, multilingual retrieval, provider data enrichment, geo-aware matching, and a conversational delivery layer for guided service discovery.
Impact: Higher signal in discovery, better conversion into qualified leads, and a cleaner experience for both users and local providers.
0 Salary
Financial Independence Navigation
Problem: Most financial tools show isolated metrics rather than a navigable path toward long-term independence and cash-flow resilience.
Approach: Translate financial planning into route planning with milestones, scenarios, and decision checkpoints that users can understand visually.
Architecture: Scenario engine, portfolio and savings models, visual roadmap layer, educational recommendation engine, and progress tracking components.
Impact: More understandable planning, stronger habit formation, and better visibility into how decisions affect long-range financial outcomes.
SwissMCP
Enterprise MCP Integration
Problem: AI agents need secure access to enterprise systems, but most organizations lack a controlled integration layer for tools, APIs, and context exchange.
Approach: Introduce an MCP-based integration layer with explicit governance, access controls, and reusable connector patterns for enterprise environments.
Architecture: MCP server platform, tool registry, identity and approval controls, observability, and adapters for APIs, data sources, and workflow systems.
Impact: Safer enterprise adoption of agents, faster connector reuse, and a more defensible path from experimentation to production integration.