About
shenas is a local-first quantified-self platform. It gathers health, finance, and lifestyle data from the services you already use, normalizes it across your own home mesh — laptop, phone, tablet, server — and helps you find patterns. Your raw data never leaves the mesh.
How the company is run
Founded and run by Alexander Funcke. Solo-founder, bootstrapped, no outside investment. Day-to-day operations are agent-led: roles like Head of Product, CTO, CISO, Legal Counsel, QA, and engineering run as configured agents under founder oversight, working against versioned values and per-role briefs.
The company runs on top of the same data and analytics pipeline the product offers users. Agent operations, decision quality, and work-product reactions all flow through it. If the architecture cannot run a company, it cannot run a person — and we want to find out which it is, on ourselves, first.
How the company makes money
shenas is open-core. The community version is free and open source, and it always will be. A commercial layer with hosted services and team-shaped features funds the work. Anything that touches your data — the local pipeline, the on-device models, the privacy primitives — stays in the community version.
What we believe
Privacy first, then wisdom, then science, then fun — in that order. Don't lie. Don't cheat. Don't moralize; be moral. Respect differences in goals. Say what we mean. Don't be loved; be lovely.
Engineering posture follows from these values: privacy by default, raw data stays local, and no telemetry. We don't roll our own crypto, we don't move records off-device, and we only share "wisdom, not records" via differential privacy and secure aggregation.
Where we are
Stage 0 of the roadmap: agent-first operations live; desktop alpha in daily founder use; a minimum viable agentic feedback system being dogfooded against our own operations; LLMMixNet research and Swiss + US dual-jurisdiction structure in active research. The first public release will be a free, open-source community version targeted at the quantified-self cohort, distributed via package repositories and word of mouth.