AI Forecasting Engine

MATY

MATY predicts your demand accurately so your team plans with data, not intuition.

Connect your historical data, train models automatically, and get sales and demand forecasts your team can act on immediately.

The hidden cost of planning with stale data

25–40%

average error in manual forecasts

companies relying on spreadsheets or basic statistical methods average 25–40% MAPE. Every point of error means inventory in the wrong place or sales left on the table.

60–80%

of analyst time spent preparing data

on average, demand analysts spend 60–80% of their monthly time consolidating data before any analysis can happen.

4–8%

of potential sales lost to stockouts

industry studies show 4–8% of potential sales are lost to stockouts caused by inaccurate demand forecasts. For mid-sized companies, that's millions in uncaptured revenue each year.

Statistics based on M5 Competition (Makridakis et al., 2022), IDC/Deloitte Demand Planning Survey (2021–2023), and ECR Europe/GS1 (2022).

Three steps from spreadsheets to AI forecasting

1

Connect your data

MATY ingests your historical data from structured files (CSV, Excel) sent by email or loaded automatically via cloud repository. For more advanced setups, MATY can connect directly to your systems via REST API, eliminating manual file exports.

2

Models train themselves

MATY automatically selects and trains the best model for your operation — from classical time series to gradient boosting and deep learning. When new data arrives, the model updates.

3

Your team plans with the forecast

Demand and sales forecasts available in your operational dashboard, with confidence intervals and accuracy metrics (MAE, MAPE, RMSE) visible directly. Your team decides; MATY calculates.

Built for teams that need reliable forecasts, not more dashboards

Demand and sales forecasting

ML models trained on your historical data for accurate forecasts by product, region, or sales channel — up to a 12-month horizon.

Automatic retraining

Models update when new data arrives. No technical team required. Always aligned with your operation's current reality.

Existing data integration

Connect your historical data from structured files or directly from your systems via REST API. Supports sales, inventory, external variables, and event calendars.

Measurable, transparent accuracy

Accuracy metrics (MAE, MAPE, RMSE) visible in the dashboard and output reports — so the team knows exactly how reliable each forecast is.

Multi-market and multi-timezone

Multi-country operations support. Multi-currency, multi-timezone, and regional holiday calendars built in.

Enterprise-grade security

Cloud architecture with authentication, encryption in transit and at rest, and role-based access control. Compatible with high-security enterprise environments.

Measurable results from the first month

Up to 50%

reduction in forecast error

From days to hours

in forecast generation

Up to 35%

fewer stockout events

Statistics based on M5 Competition (Makridakis et al., 2022), BCG Henderson Institute (2023), Deloitte AI in Supply Chain (2023), and McKinsey Operations Practice (2023).

Se integra con tu stack actual

Microsoft 365Microsoft 365
AzureAzure
HubSpotHubSpot
Google WorkspaceGoogle Workspace
TeamsTeams

Before the pilot, our team relied on manual reports to estimate demand. With MATY, models update automatically and the team uses that time making decisions, not preparing data.

Head of Demand Planning · Pharmaceutical company, Chile

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