Machine learning

Models that forecast, score and decide, in production.

Ten years of machine learning inside enterprises, before and after large language models. Planners act on our forecasts, our scores pass audit, and our models keep working after the data drifts.

Talk to us See the results

History Today Ahead Forecast range Actual demand Capacity limit Agent books capacity ahead

Sales, sensor and operations data, cleaned and joined into one record.
Every forecast says how sure it is, so planners know when to trust it.
Back-tested on your past and watched in production, then retrained when it drifts.
When the range crosses a limit, a planner or an agent acts before the shortfall arrives.

Illustrative forecast

86%Prediction accuracy forecasting empty containers for a shipping line, in production.

70%Improvement in machine reliability for a global energy company.

25,000Support emails a month triaged automatically for a telecom operator.

1000 PB+Data processed for clients since 2016.

What we build.

Four families of model, each tied to a decision your people make every day, built on the data you already have.

Forecasting and planning

Demand, capacity, inventory and revenue forecasts from your sales, sensor and operational data, with every revision explained so planners trust them.

Risk and fraud scoring

Credit, claims and transaction scores with the reasons behind them, so a reviewer, an auditor or a regulator can follow each decision.

Predictive maintenance and quality

Sensor and inspection data used to catch failures before they happen and defects before they ship.

Speech and language analytics

Every call and conversation scored for quality and compliance, in the languages your customers speak.

Two researchers sitting with a bank clerk at her desk, watching how she works

Built where the decision is made.

Our researchers sit with the planners, underwriters and engineers whose decision the model will support, before they write a line of code.

Run like everything else we ship.

Models take the same path to production as our agents. We measure the baseline, test on your cases and keep monitoring after launch. How we deploy

Baseline firstWe measure how the decision is made today, and how well, before a model touches it.

Tested on your historyModels are back-tested on your past cases and run in shadow beside your team before they go live.

Monitored and retrainedWe watch drift, accuracy and cost in production and retrain each model on a schedule.

Where models meet agentsA planning agent acts on a forecast, and a claims agent uses a score to settle or escalate. On Addo Core, models and agents share the same data, controls and record.