Six good places to start

Six problems we're set up to solve: illustrations, not client stories.

DEMAND FORECAST · OPERATIONS LEADEXAMPLE

Production, stock or staffing decisions rely on a spreadsheet and experience.

OUTCOME
A four-week estimate for each product group, in the planning tool.
TEST
Backtest against the current forecast over the same historical periods.

Built with machine learning

DOCUMENT EXTRACTION · LEGAL / FINANCEEXAMPLE

People re-read the same documents for the same fields, clauses or risks.

OUTCOME
Extracted fields with the source passage beside each result, uncertain cases to review.
TEST
Accuracy on a held-out set, with a review rate agreed in advance.

Built with generative AI

ANOMALY DETECTION · OPERATIONSEXAMPLE

Problems in a machine, process or transaction appear only after the damage has started.

OUTCOME
An alert on unusual behaviour, in the channel the team already watches.
TEST
How many real incidents it catches in time and how many false alerts it raises.

Built with machine learning

PLAN OPTIMISATION · PLANNINGEXAMPLE

Planners weigh too many options and constraints by hand.

OUTCOME
Practical alternatives that stay within capacity, timing and business rules.
TEST
Comparison with the current plan on cost, service level and feasibility.

Built with data science and optimisation

DECISION AUTOMATION · PROCESS OWNEREXAMPLE

A model produces a result, but someone still moves it between systems by hand.

OUTCOME
A workflow that sends data and results to the right system, approval where needed.
TEST
End-to-end tests, including logging, retries and human approval where required.

Built with data and integration

Yours will look different.

If the data exists and the result can be measured, it probably fits. Send it over and we'll tell you either way.

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