What kinds of logistics workflows can Levity automate?

Levity targets high-volume, email-driven logistics communication — the kind of work where thousands of repetitive requests flow through shared inboxes every day. Based on its own product materials, the platform is built around a set of named email categories: Track and Trace, Booking, Pricing & Quoting, Damage Claims, Customs, and General Inquiry, with shipment-specific scenarios including Shipment Status, ETA Updates, POD Requests, and Exceptions. If your operation handles these request types at scale, Levity is designed for that shape of work. If your workflows are low-volume or not email-centric, the fit is weaker.

The workflow categories Levity names

Levity's dashboard groups incoming email into categories, which gives a concrete picture of what it expects to process:

A second layer of categories covers shipment-level events: Shipment Status, ETA Updates, POD Requests, and Exceptions. These are the recurring touchpoints where a customer, carrier, or partner needs a status answer or a document.

Why these categories are the automation target

The common thread is repetition with variation. A Track and Trace email and an ETA update request look similar but differ in shipment reference, language, and urgency. Levity's stated approach is to find "repetitive requests, handoffs, and bottlenecks at scale" — meaning it first measures which categories dominate your inbox, then turns the highest-impact ones into automations.

The scale in Levity's own example is large: a dashboard showing 8,240,312 emails processed in 30 days, with daily incoming volume charted in the hundreds of thousands. That's the regime the product is built for — global supply chain operations where manual triage doesn't scale.

How the workflow actually runs

Levity describes three stages, and each maps to a different kind of work:

1. Analyze — Connect inboxes and let the system categorize incoming email. The Control Tower dashboard shows volume by category, internal vs. external split, and trends over time. You can also "chat with your data" in natural language to explore operational patterns.
2. Build — Turn the high-impact categories into production automations. This is where a Track and Trace or POD Request workflow becomes something the system handles rather than a person.
3. Scale — Govern and improve automations through visibility, human oversight, and continuous feedback. The point is that humans stay in the loop for exceptions and quality control.

Where Levity fits — and where it doesn't

Levity is a reasonable fit when:

• Your logistics communication runs primarily through email at high volume
• Requests fall into recurring categories rather than one-off projects
• You have shared inboxes with handoffs between teams or regions
• You need visibility into what's actually arriving before automating it

It's a weaker fit when:

• Volume is low enough that manual handling isn't a bottleneck
• Workflows aren't email-driven (e.g., pure API or EDI integration without a communication layer)
• Requests are highly bespoke with little repetition

A practical way to decide

Before committing, the useful test is whether you can name your top three email categories and roughly how many arrive per day. Levity's own framing — "don't bolt AI onto chaos" — suggests the first value is measurement: seeing which categories dominate and where handoffs stall. If you can't yet describe your inbox in those terms, the Analyze stage is where you'd start. If you already know your Track and Trace or POD Request volume is in the thousands per day, that's the workflow to automate first.