Intelligence for the physical world

Every shipment.
One connected
workflow.

Connect orders, cargo and fleet operations. Move from fragmented handoffs to coordinated decisions, from the warehouse to the final receipt.

Early-stage concept · Interactive demo with synthetic data
OPERATIONS / NETWORKCONCEPT VIEW
Connected shipment workflowOrder data and cargo scans meet in a coordination layer, which proposes consolidation and dispatch. Operators approve actions before delivery and reconciliation.INPUT / 01INPUT / 02OPERATOR REVIEWOrder dataCargo scansCoordination layerApprove dispatchFleet executionDelivery + ledgerPLAN · VERIFY · PROPOSE
Order data
Cargo scans
Coordination layerConsolidate · Verify · Propose
Operator reviewApprove dispatch
Fleet execution
Delivery + ledger
Physical events. Traceable decisions. Human control.
ONE OPERATION, CONNECTED
Cargo identityLoad planningFleet coordinationDelivery evidence
01 / The connected workflow

From the first order
to the final receipt.

A shared shipment record is the proposed foundation. Every scan, load check, assignment and delivery event stays connected to the same order.

01

Receive

Bring orders and delivery requirements into a common format.

02

Identify

Match RFID or barcode events to a known shipment.

03

Consolidate

Group compatible cargo by destination, capacity and time window.

04

Verify loading

Check each shipment against the assigned vehicle manifest.

05

Dispatch

Propose assignments using traffic and operational constraints.

06

Close the loop

Link delivery evidence to reconciliation and settlement review.

Planned product scope. The demo simulates this workflow; hardware, AI and business-system integrations are not connected.

02 / Designed around operations

Less re-entry.
More coordination.

Starting with regional delivery teams, where cargo handling and dispatch need to work together.

A

A shipment identity
that survives every handoff.

The planned event layer connects label reads, vehicle assignments and proof of delivery. Missing scans and mismatches become explicit exceptions, rather than another spreadsheet.

Barcode-first MVPRFID pilot plannedEvent history
B

Constraints first.
Intelligence where it helps.

Capacity and delivery rules define what is feasible. A proposed Claude layer interprets documents, explains exceptions and drafts next steps. Operators approve consequential changes.

Rules + optimizationPlanned Claude integrationOperator approval
C

Delivery is an event.
Settlement is a workflow.

Connect a signed delivery record to the original order and agreed charges. Surface missing evidence before a billing review. Payment execution remains a separate, approved step.

Proof of deliveryCharge reconciliationApproval trail
Explore a complete handoff

A shipment's journey.
A decision you can inspect.

Import sample orders, verify cargo, consolidate loads and respond to a traffic exception. See what changes at each step.

Run the interactive demo
03 / Product roadmap

Start focused.
Learn from the field.

The first proposed pilot pairs one warehouse with a regional fleet. Scope and milestones will be validated with operators.

NOW / CONCEPT

Explain the workflow

Interactive prototype, proposed architecture and discovery with warehouse and dispatch teams.

NEXT / MVP

Connect the essentials

Order import, barcode scan events, load manifests, approval-based dispatch and delivery evidence.

LATER / FIELD VALIDATION

Measure, then expand

Validate RFID reads, traffic feeds and system integrations. Measure manual touches, loading exceptions and on-time delivery.

Before you explore

Clear answers.
Realistic boundaries.

Is the product available today?

AI Logistics OS is a working name for an early-stage product concept. This website is a prototype. The interactive demo uses synthetic data and predefined logic, with no live AI, vehicles or connected devices.

Why connect software with cargo identification?

A plan is only useful when it matches what happened on the floor. Barcode and RFID events are intended to connect a shipment record to physical handling. Reader reliability, installation and scan coverage still need field validation.

Where would Claude fit in the product?

The proposed integration would use Claude to extract order requirements, explain exceptions and draft actions through controlled tools. A rules and optimization service would check feasibility. Claude is not connected to this demo, and no Anthropic partnership or program acceptance is claimed.

What would a pilot need to prove?

That operators spend less time re-entering data, catch more loading mismatches and can inspect dispatch recommendations. Pilot targets and commercial pricing will be set after discovery; no measured performance gains are claimed.

Design partners wanted

Run a warehouse
or a regional fleet?

Walk us through one real handoff, from order to proof of delivery. We are looking for a small number of operators to shape the first pilot.