Envio 360 is a logistics platform used by BCOs and the trucking community to manage equipment and create drayage orchestrations, and by terminal operators to manage drayage capacity and vessel schedules.Designed as a more focused and automated evolution of traditional terminal systems, Envio shifts the burden of scheduling away from users and onto the system itself—allowing users to express intent while the platform works continuously to secure valid appointments.

Role

Senior UX Designer

My focus was on:

Designing workflows across key modules
Establishing clear relationships between screens
Translating complex logistics rules into usable experiences
Validating ideas through end-to-end prototypes

The work was highly collaborative and iterative.

Users & Context

Envio supports two interdependent user groups

BCOs & Truckers

Manage equipment
Create drayage orchestrations
Track system-driven outcomes

Terminal Operators

Manage drayage capacity
Configure vessel schedules
Control availability that determines booking success

A core challenge was ensuring actions by one group were clearly reflected for the other.

Problem 1

Booking required users to micromanage availability

Traditional systems required users to:

Pick exact dates and time slots
Submit and wait for success or failure
Retry manually when capacity was unavailable

This made booking error-prone, time-consuming, and stressful—especially under operational pressure.

Users had to pick a slot, submit, fail, and try again

Solution 1

Shift booking responsibility to the system

Envio allows users to:

Provide date ranges and preferred time windows
Submit intent once

The system then:

Continuously monitors capacity
Responds to capacity changes over time
Automatically secures a valid slot when available

This reframes scheduling as a system responsibility, not a user burden.

Add drayage orchestration

Problem 2

Screens existed, but system behaviour felt fragmented

Users struggled to understand:

Why bookings succeeded or failed
How capacity changes affected outcomes
Where the current source of truth lived

The lack of visible relationships reduced trust.

Solution 2

Design around clear cause-and-effect

We focused on how modules influenced one another:

Capacity shapes orchestration outcomes
Orchestration intent drives system behaviour
Dashboard surfaces outcomes
Equipment reflects real-world state

The goal was to make cause → effect → outcome easy to follow.

Relationship between modules

Problem 3

Users lacked visibility into what the system was doing

Without clear feedback, users were unsure:

If the system was still working on their request
What required attention vs what was automated

Solution 3

Use the dashboard as the system’s voice

The dashboard was designed to:

Surface booking states at a glance
Reflect terminal status and utilisation
Highlight operational opportunities (e.g. dual moves)

It prioritises clarity over raw data.

Dashboard screenshot

Problem 4

Automation needed a real-world anchor

Scheduling logic alone felt abstract. Users needed confidence that system decisions aligned with actual containers and yard reality.

Solution 4

Ground automation in equipment visibility

Manage Equipment provides:

Container-level status
Clear state transitions (Available, In Yard, Gate Out, Completed)
Direct links between assets and orchestration outcomes

This made automation feel tangible and trustworthy.

Manage Equipment list + detail view

Problem 5

Capacity control required precision without complexity

Terminal operators needed fine-grained control without overwhelming interfaces.

Solution 5

Make capacity scannable and predictable

Manage Drayage Capacity uses:

Visual indicators for utilised vs available slots
Hour-level control
Clear pickup, drop, and dual breakdowns

Operators can quickly reason about impact without digging through data.

Drayage Capacity — Day view

The Outcome

Reduced manual effort and retries
Fewer failed bookings
Clearer system feedback
Greater trust in automation

The experience shifted from reactive problem-solving to proactive system support.

Krunchbox evolved from a report-heavy system into an insight-led platform designed for faster, more confident decisions.