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Agentic control tower for logistics

One control tower
for your logistics operations.

marnieAI learns your team's systems, data, and SOPs, along with every investigation your team has already run. From that, it builds a set of expert agents customized to your operation, one for each system in play. Those agents find root causes on demand, and catch anomalies before customers feel them. The whole system gets sharper with every investigation it runs.

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How marnieAI works
BRAIN

Knowledge Brain

Holds your systems, data, SOPs, and every past investigation. From this, marnieAI builds the agent team below, customized to your operation.

The agent team marnieAI built for this operation
OMS
Order agent

Triages the promise

Isolates which orders missed their promise, and when.

WMS
Warehouse agent

Checks the floor

Investigates that same cohort: pick, pack, staffing.

TMS
Transportation agent

Checks the road

Investigates that same cohort in transit: carrier, routing.

SYN
Synthesis agent

Joins the findings

Combines every agent's finding into one root cause, with evidence.

Every agent draws on the Brain before it starts, then hands off what it found to the next. What Synthesis learns feeds back into the Brain for next time. You stay in the loop throughout: continue, redirect, ask, or synthesize early.

The problem

Manual coordination is expensive

Escalations get solved by hand, one disconnected system at a time.

4+

disconnected systems checked one at a time: order, inventory, warehouse, and transportation

~6 hrs

lost per customer escalation, reconstructed by hand across systems

Reactive

today's tooling catches problems only after a customer feels them

Every quarter

escalation firefighting drains the team that should be building product

Example

A real investigation, at real scale

Case: 5% late deliveries, last week

An ops lead asks why 5% of last week's orders arrived after their promised date. Order release and carrier transit both look normal for the week. The actual cause is one Tuesday when warehouse pick time rose from about an hour to about four, pushing that day's orders past the ship cutoff. No team catches this alone, because each one only watches its own system. A team doing this by hand takes roughly six hours across three systems. marnieAI finds it in minutes.

  1. 01Order Management: isolates exactly which orders missed their promise, and by how long.
  2. 02Warehouse: checks that same cohort for pick, pack, and staffing anomalies.
  3. 03Transportation: checks the same cohort in transit for carrier and routing issues, finds nothing.
  4. 04Synthesis: narrows to the one Tuesday when pick time rose from about an hour to nearly four, pushing that day's orders past the ship cutoff.
Why marnieAI reasons the way it does

Built from the instinct of running this by hand

We've run these operations ourselves, at companies moving some of the largest volumes in the industry: Amazon, Chewy, Procter & Gamble, and Flipkart. Fifteen-plus years of escalations taught us when a problem needs a root-cause trace, a live experiment, or a full flow simulation. marnieAI's judgment layer runs on that same instinct.

Three tools. One judgment layer decides which an investigation needs:

When the question is "why"

Root-cause trace

A metric moved and the systems behind it are already connected. marnieAI chains through each one in sequence until the cause has evidence behind it.

When the fix isn't proven yet

Live experiment

The hypothesis needs real traffic before it's trusted. marnieAI designs the test and reads the results.

When it's too risky to test live

Flow simulation

Rolling a change out live isn't worth the risk. marnieAI stress-tests it against the full network first.

Capabilities

Five pillars, built in the open

The core capabilities built into marnieAI's control tower, with recommendations today and direct action next.

sample investigations marnieAI is designed to answer
>How did the recent snowstorm impact my delivery speed?
>Did our cost-per-order spike because of the fuel surcharge increase?
>Why are the distribution centers nearest most of our customers out of stock this week?
>Did product demand decline because of the recent delivery-delay escalations?
>What happened to cost and delivery speed after we launched the new last-mile partner?

Team knowledge brain

Learns each team's own schema and SOPs, then unifies them into a single source of truth. Gets sharper with every investigation it runs.

Multi-lens BI investigations

Runs analytics through every stakeholder lens: business, product, operations, and science, in one agentic workflow. Queries every team's database on command, in plain conversation.

Data science toolkit

The same root-cause trace, live experiment, and flow simulation tools from above, available for any metric that moves.

Anomaly detection & alarms

Catches a metric moving before a customer feels it, and flags it the moment it moves, no prompt required.

Recommendation & insight generation

Closes the loop from diagnosis to action: chat alerts, ticket assignment, and eventually the fix itself.

Next phase

Autonomous action

marnieAI will trigger changes directly in your connected systems next, once trust and human-in-the-loop validation are in place.

Who it's for

Built for the platform, felt by the merchant

Paying customer

Logistics & fulfillment platforms

3PL and fulfillment software operators. Run your own operations end to end, or switch marnieAI on for the merchants you serve. Each merchant runs different systems, so each gets its own customized agent team. One license, many tenants.

Downstream beneficiary

The merchants they serve

Small and mid-sized e-commerce and DTC sellers who don't have an in-house supply-chain engineering team. Root-cause investigation gets switched on for their account through the platform they already use.

Positioned as an alternative to enterprise incumbents like Aera, Kinaxis, o9, and Blue Yonder, sized for platforms and merchants below their budget and team size. What sets the reasoning apart is the judgment layer, built from actually running these operations by hand.

Private beta

Get early access.

marnieAI is in private beta today. Early access goes to platform and merchant teams first. Request a walkthrough, or join the list for updates as the pilot program takes shape.

Running a logistics or fulfillment platform and want to talk pilot? Get in touch →