Marketplace brand operating system

The control layer
Amazon never built
for brands.

AdSwarm turns scattered Amazon signals — inventory, ads, finance and forecasting — into governed decisions, execution memory, and operator-approved automation.

By invitationFor USA Amazon brandsAmazon-first
The problem

Amazon exposes the signals. Brands still run the operating system by hand.

Inventory, ads, finance, forecasting, creative and operations get reconciled across reports, APIs, spreadsheets and operator memory. The work isn’t collecting insight — it’s reconciling decisions.

Inventorystock cover · inbound velocity
Adsbids · budgets · negatives
Financefees · settlements · cash
Forecastdemand · replenishment
Creativeassets · tests · publish
Operationsapproval · reorder · issues
Manual reconciliationspreadsheets · exports · dashboards · operator memory
Slow decisionsoperators wait on reports
Leaking marginads, stock & cash disconnected
Weak memorylessons live in people & Slack
Unsafe automationactions without proof or rollback
The system

One governed control loop.

Every domain becomes a stage in a single loop — constrained by capital, executed through governed mutations, and verified against the outcome it promised.

01Inventory

Stock cover & inbound velocity as live constraints.

02Forecast

Demand & replenishment, projected per ASIN.

03Capital

Fees, settlements & cash bound the spend.

04Ads

Bids, budgets & negatives vs real margin.

05Execute

Governed, idempotent mutation batches.

06Verify

Checked against the outcome it promised.

07Learn

Outcomes train the next decision.

Machine learning layer

Machine learning with guardrails, not black-box automation.

AdSwarm converts marketplace outcomes into training signals, calibrates recommendation confidence, detects drift, and rolls back weak model behavior before it compounds into operator risk.

00.510.51Predicted probabilityObserved rateperfectly calibrated
Posterior confidence

Bayesian inference draws confidence from sparse marketplace data.

Isotonic calibration

Recommendation probabilities calibrated against historical outcomes.

Hyperparameter fitting

Per-strategy model tuning — not one global black box.

Drift detection

Decaying signal quality is detected before it compounds into risk.

Auto-rollback

Weak model behavior is reverted automatically — a safety action, not a hope.

The system doesn’t just recommend actions — it learns which recommendations survive marketplace reality.

Built depth

A built control plane, not a dashboard mockup.

AdSwarm already contains the surfaces, APIs, data models, workers, migrations and tests required to run marketplace operations as governed software.

897Klines of TypeScript1.08M lines of source including schema, SQL & styles
823API routesDecision + execution layer
336Data modelsAcross three Postgres databases
317MigrationsEvery schema change versioned
818ComponentsCommand surfaces
428Test filesVerification layer
163App pagesOperator console
01 Command Surfaces163 pages · 818 components
02 API + Decision Layer823 governed routes
03 Operating Memory336 models · 317 migrations
04 Worker System115 job types · 4 services
05 Verification Layer428 test files

Measured from the production checkout, June 2026. Generated outputs and dependencies excluded.

Access

By invitation.

AdSwarm is built for a small number of USA Amazon brands running real volume. Request access and we’ll review your brand by hand — or enter an invite code if you already have one.

  • Amazon-first, governed marketplace execution
  • Operator-approved automation with full rollback
  • Built and run by brand owners, not a dashboard vendor

Request access

By invitation · For brands selling on Amazon in the USA

Request access