Who needs it first
Requests show which shopify, Etsy, Amazon, and DTC sellers need the first working loop.
Improves: A tighter request path for E-Commerce Profit Optimizer, with the next owner and outcome visible.
Loading
Loading
Loading
Founder OS
Tracks margins, inventory, shipping, returns, ad spend, and product profitability.
In build
App status
In build
Access
Founder OS
App field
What makes it useful
The app is useful when the people, evidence, action, and follow-up are clear enough for someone to move without a private explanation from the Rhiz team.
Useful inputs
The people this should help first
The outcome that would make the app worth using
Current blockers, manual work, or missed follow-through
Records, datasets, pledge notes, or payment context you control
App flow
The app starts with a concrete need, turns it into a usable next move, and keeps the useful result close enough to reuse.
Import finance state
Model runway
Flag risk
Route cleanup
Record decision
What gets better
Who needs it first
Requests show which shopify, Etsy, Amazon, and DTC sellers need the first working loop.
Improves: A tighter request path for E-Commerce Profit Optimizer, with the next owner and outcome visible.
Where people get stuck
Completed and blocked actions show which step is confusing, slow, or missing proof.
Improves: One clearer checklist item, prompt, handoff, or follow-up reminder inside the app.
What becomes reusable
Sales motion patterns strengthen Data access layer.
Improves: A marketplace primitive that can improve related apps instead of staying trapped in one request.
How Rhiz helps
Package queryable datasets, permissions, subscriptions, provenance, usage, support, and review trails.
Track cash, runway, receivables, payables, taxes, credit readiness, margins, and funding scenarios.
Turn customer segments, offers, pricing, campaigns, retention, referrals, and growth experiments into next actions.
Build faster
Rhiz starts from proven open-source patterns where they fit, then wires the trust, access, and follow-through layer around the people using the app.
Data access layer
Embedded analytics, dashboards, alerts, and data browser surfaces.
integrateRevenue growth engine
Product analytics, funnels, experiments, and conversion measurement.
integrateFinance control loop
Budgeting, accounts, cash tracking, and transaction-led finance UI patterns.
studyData access layer
Data exploration, visualization, and BI dashboard patterns.
studyData access layer
Single-cell data exploration and domain-specific scientific UI.
studyData access layer
Dataset catalogs, data portals, APIs, and provenance metadata.
studyCompounds with
Related apps share primitives, outcomes, or operating lanes, so useful signal from one request can strengthen the next surface instead of disappearing into a separate backlog.
Finance control loop + Revenue growth engine
Shares Finance control loop and Revenue growth engine.
AlphaFinance control loop + Data access layer
Shares Finance control loop and Data access layer.
In buildRevenue growth engine + Finance control loop
Shares Revenue growth engine and Finance control loop.
In buildRevenue growth engine + Finance control loop
Shares Revenue growth engine and Finance control loop.
In build