Beneath AnalyticsIndustry
Logistics
Late deliveries usually show up in a weekly report, after the customer has already called. We pull telemetry, orders and fleet data into one place, forecast demand and capacity, and flag exceptions during the shift: late loads, cost per lane, and routes that quietly lose money.
Where this sector loses ground.
For carriers, 3PLs and shippers. We build the data layer that makes on-time rate, cost per lane and capacity visible, with alerts that reach your team before they reach the customer.
Performance visible only after the fact
On-time and cost figures are compiled weekly, so problems on the network are found once the service has already failed.
Capacity planned on instinct
Demand and capacity forecasts are built by hand, so teams react to peaks instead of staffing and positioning ahead of them.
Unprofitable lanes hidden in averages
Network profit is reviewed as one number, which hides the routes and customers that consistently lose money.
Telemetry and orders that do not match
Vehicle, warehouse and order systems do not reconcile, so finding why a delivery was late takes hours of digging.
How we work in this sector.
Sequence matters: govern the data first, make every reported number traceable, then build the models and automation that act on it.
Bring telemetry, order, warehouse and fleet data into one warehouse with agreed definitions.
Build demand and capacity forecasts that reflect seasonality, lanes and service commitments.
Calculate cost and margin by lane and customer, so exceptions surface without manual analysis.
Automate exception alerts and recurring reports, so action happens during the shift and not after it.
Where this usually starts.
The solutions we most often deploy in this sector. Each page sets out the capabilities, platforms, and outcomes you can expect.
- AI Consulting & Development
AI-Ready Data Platforms
AI-ready data platforms means Beneath Analytics builds the warehouses, pipelines, and governance that AI and analytics depend on: BigQuery and Snowflake warehouses with dbt transformation, data quality checks, and documented lineage you can defend. Pipelines scale with your data volume, so models and dashboards run on data your team trusts.
View solution - Tracking & Analytics
Analytics & Business Intelligence
Analytics and business intelligence means Beneath Analytics turns your tracked data into decisions: attribution modelling, predictive models, and dashboards built around the questions your team actually asks and adopted by the people who use them.
View solution - AI Consulting & Development
AI Workflow Automation
AI workflow automation removes the manual work between your systems: compliance reports, risk summaries, inventory updates, and weekly reporting compiled by hand. Beneath Analytics maps the process, builds pipelines with n8n, Python, or dbt, then monitors them, so reports arrive on time without someone spending days assembling them.
View solution
Common questions.
Yes. We connect through available APIs, database extracts or flat files, depending on the system, then standardise the data so it can be modelled consistently.
We start by agreeing the definition across operations, finance and customers, then build it into the reporting layer so everyone reports the same number.
Yes. Forecasts cover demand, lane volumes and required capacity, and are checked against actuals so accuracy improves instead of drifting.
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A 30-minute session, no pitch: you get a one-page opportunity map showing where AI can make a real difference in your business.