Signal Loom
Observe, evaluate, and ship reliable agent workflows from one Python-native surface.
Northstar
Relay
Forge
VectorLake
Compose
Model agent work as explicit steps
Shape tools, review points, and retry policy without hiding the workflow behind a client-side framework.
Plan -> retrieve -> call tools -> review -> respond
Observe
Trace every run as stateful product UI
Expose timeline, artifacts, source provenance, and recovery actions as first-class screen objects.
Run timeline with source bundle, retry, and reviewer handoff
Improve
Turn production traces into evals
Keep quality loops close to real user behavior and make regression evidence visible.
Trace -> eval case -> reviewer score -> release gate
Proof before integration code
4
golden screens
320px
phone proof
0
utility classes added
Choose an entry point
Teams use it for durable agent surfaces
Northstar
Operational state stayed visible
A command center replaced disconnected queue cards with a single inspected work surface.
Relay
Review work moved faster
Filters, records, and selected details shared one low-glare review rhythm.
Forge
Run recovery became obvious
Agent traces, artifacts, and retry controls stopped feeling like raw logs.
Build the next mock from a screen, not a blank grid
Start with a catalog archetype, choose a profile, then let primitives and components carry the details.