Automate analyses for data-backed optimizations

Learn from the past

FlexOps Diagnostics uses machine learning and historical data to map your processes, re-create your delivery operations, and identify opportunities for improvement across costs, routes, delivery capacity, and fleet management.

FlexOps Diagnostics diagrams and flowcharts
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Works with any data format

Every organization’s data is unique and imperfect. FlexOps algorithms account for imperfect and incomplete data, and include tools to detect and fix common issues such as redundancies and bad geocodes.

Automatically identify

  • Inefficient manual or semi-automated scheduling, booking, or routing practices

  • Utilization variations across fleets causing instability

  • Handling steps (sorting, packing, scanning) that are causing delays and bottlenecks

  • Underperforming prioritizations, FIFO, or vehicle packing processes

  • Over or under-utilized assets

  • High-cost reverse logistics processes

  • Last-mile delays due to parking, traffic, weather, human error, or other.

Adiona FlexOps Command user interface

Here's an example

The scenario

A logistics director is tasked with identifying bottlenecks and other areas for improvement in their operations and processes. Very quickly, the logistics director finds that they have data issues, such as data redundancies and bad geocodes, that are leading to missed opportunities.

The logistics director identifies the data quality as the first step to unblocking bottlenecks and creating efficiencies, and needs to be completed first so they can make informed decisions later on.

How it works

  • Upload Historical Data

    Data that is uploaded to the FlexOps proprietary labeling and normalization engine is transformed into standardized and consistent formats.

  • Map Processes

    Once the data is standardized, FlexOps creates a baseline model of existing operations.

  • Identify Metrics

    Now that the data is reliable, accurate, and in one place, benchmarks can be established across end-to-end processes for the logistics director to monitor, evaluate, and measure improvements.

The results


After normalizing the data, they reduce time spent manually checking and correcting information, and automatically identify opportunities in delivery operations such as reducing delays.


Once benchmarks are set, they use the data to identify the first opportunity for improvement, based on size and impact. Opportunities include resource allocation, delivery times, fleet efficiency, and more.


As each bottleneck is systematically addressed, the end-to-end operations improve as a whole. They are now capable of continuous and accurate benchmark measurement, allowing the logistics manager to holistically prioritize the next bottleneck to tackle.

Explore our technologies

FlexOps Command icon

FlexOps Command

Combines our Diagnostics and API systems on a customizable map-based user interface.

For fleets and logistics operators
FlexOp Diagnostics

FlexOps API

A suite of automation and optimization tools that can be integrated into almost any IT stack.

Built for developers
2D graphic illustration of moving trucks

FlexOps Fleet Simulator

Quantify and optimize your vehicle purchase and deployment decisions, infrastructure plans based on real operational requirements.

For next-gen low-emission fleets

Get started today

Access 14 Days of Adiona for free and upload your own data to see how much efficiency you can gain.

Developers, get instant access to our API.

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