TameChaos
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How it works

An edge-first experimental control platform

Design and run sensor-driven systems on the authoritative edge, and let a fleet of edges get smarter from its own operation. Here's what that means.
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Edge-first

The edge is the authoritative runtime

Sensor-driven systems are built, run, and refined on the edge server — it owns execution. The cloud observes and aggregates; it is never the real-time control plane.
  • Build on the edge
    Compose real and virtual sensor arrays, physics and inference models, and the experiments that exercise them — on the edge server that owns your hardware.
  • Run on the authoritative edge
    The edge server executes experiments and simulations — in real, simulated, or hybrid mode. It is the authoritative runtime, not the cloud.
  • Refine locally, then aggregate
    Analyze and document runs locally first. The cloud is a non-authoritative layer that aggregates across edges — it is never the real-time control plane.
The fleet-learning loop

Oversee → Aggregate → Improve → Distribute

The cloud is the non-authoritative aggregation, coordination, and intelligence layer for your fleet. Steps 1–2 ship today; steps 3–4 are the deferred model-loop phase.
Available now (v1)
1 · Oversee
A fleet registry: which edges exist, online / last-seen, software version, and their active runs.
Available now (v1)
2 · Aggregate like-processes
Group runs that instantiate the same process-class template, across edges, into comparable sets — the join key for everything downstream.
Model-loop phase — on the roadmap
3 · Improve models
Refine physics models (calibration / system identification) and inference models from aggregated like-process data.
Model-loop phase — on the roadmap
4 · Distribute
Publish improved templates and models back to the fleet for edges to pull and adopt — publish-and-pull, never command.
Edge authority

Cloud suggests. The edge decides.

The cloud is authoritative for definitions and identity; the edge is authoritative for adoption and execution. A template is an inert definition until an edge instantiates a run from it.
The cloud is authoritative for definitions
Template and model definitions, and their identity — the registry. Cloud issues template identity and observes, aggregates, compares, and suggests.
The edge is authoritative for execution
Which definitions it adopts and runs, and the live runs themselves. Cloud never starts, stops, or mutates a run — distribution is publish-and-pull, never command.
Per-fleet tenancy

A fleet gets smarter from its own operation

Aggregation and model improvement are scoped to a single owner's fleet. There is no cross-tenant data or model sharing — your fleet learns only from its own operation.
Honest about phasing

What's available now, and what's next

v1 is aggregation-only. The model-improvement loop and pull-based distribution are the next phase — we'd rather be clear than over-claim.
Available now (v1)
Aggregation across your fleet, plus the registry it builds on.
  • Fleet registry & oversight
  • Run / measurement ingestion
  • Process-class template registry + identity
  • Time-series query + cross-run comparison
On the roadmap
The model-loop phase — improving and redistributing models back to the fleet.
  • Physics + inference model registry and lineage
  • Model / template distribution & adoption back to the fleet
  • Cloud-side composition of refined templates
  • Cloud-run training / physics calibration

See it in the app

The platform lives in the cloud app. This is the marketing front door — when you're ready, open the app.
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