We build AI systems
that actually work.

ETH engineers bringing applied AI into production: practical systems, measurable results.

ETH Zurich Start-up
3 founders with deep AI knowledge
Zurich, Switzerland
01

How We Help

We support you from the first analysis to the production rollout of your AI solution.

Opportunity Discovery & Roadmap

Systematic identification and prioritization of AI use cases aligned with your business KPIs and technical feasibility.

AI Agent Automation

Automate complex workflows with AI agents that coordinate tools, decisions, and handoffs.

RAG Knowledge Systems

Accurate, context-aware answers based on your internal company knowledge.

Data & MLOps Foundations

Pipelines, monitoring, and infrastructure that turn proof-of-concepts into reliable production systems.

Document Intake Automation

AI agents that handle document intake, validate data, and automate downstream workflows.

Change Management & Enablement

Documentation, training, and runbooks that ensure your team can operate and improve AI systems.

02

What We Build

Data Intake & Processing Pipelines

Structuring, quality gates, plausibility checks, query logic, and handoff to downstream systems.

Agentic Workflows & Automation

Copilots and automations with guardrails, logging, approval processes, and traceable process logic.

Training & Cloud Deployment

Scalable training, data processing, MLOps, and production operation on AWS, Azure, and GCP.

03

From Idea to Production

In months, not years.

01

Online Meeting

45 min to 1 hour

We discuss your goals, challenges, and first ideas for using AI. Together, we identify where AI can create real value.

02

Scoping Workshop

2 to 3 hours

We sharpen the use case, show relevant demos where helpful, and define what will be built, how the implementation will work, and what costs to expect.

03

Build Phase

3 to 6 months

We develop the solution step by step, show regular progress, and integrate it cleanly into your existing systems.

Meet the Team

Three ETH Zurich engineers bringing AI from the lab into production.

Andre Emmenegger

Andre Emmenegger

Agentic Systems & Platforms

  • MSc CS, ETH Zurich
  • Time Series & LLMs Research
  • Ex-BSI Engineer
  • Published at Disney Research
Darius Doongaji

Darius Doongaji

Innovation & Intelligence

  • MSc CS, ETH Zurich
  • Full-stack Engineer at SF Startup
  • Lesion Detection Research
  • Built Robust AI at Medical Startup
Tobias Leuthold

Tobias Leuthold

Automation & Acceleration

  • MSc Mech. Eng., ETH Zurich
  • Automation Pipelines at Swiss AI Startup
  • Classification Models on Timeseries Data
  • Improved Google's SOTA Pose Estimation Model
“We connect current AI research with business practice and turn applied research into systems with measurable results.”

Common Questions

We implement least-privilege access, auditable data flows, and human-in-the-loop validation where it matters. All systems can be deployed on-premise or in your own cloud environment with full data sovereignty.

Discovery phase: 1-2 weeks. MVP development: 2-6 weeks with weekly demos. Full production deployment typically completes in 8-12 weeks total, depending on complexity and integration requirements.

We work on project-based or retained engagement models. After the initial scoping workshop, you'll have a clear roadmap with effort estimates. We focus on value delivery, not billable hours.

Yes. We build cloud-agnostic solutions that can run in AWS, Azure, GCP, or on-premise infrastructure. You maintain full control of your deployment environment.

Every project starts with defining measurable KPIs tied to business outcomes (e.g., time saved, error reduction, margin improvement). We track these metrics throughout development and production.

Ready to put AI into practice?

Book a 20-minute call. Together, we explore where AI can create meaningful value for your business.

Least-privilege access · Auditable data flows · Human-in-the-loop where it matters