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Forecasting: Stay ahead with AI-Powered accuracy

Unlock and access the power of data-driven forecasting and transform the way you make true informed decisions.​

​thaink² enhances your forecasting with a cutting-edge AI intelligence

With a KPI-based approach

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Smart data preprocessing

with automated analysis detection : anomalies...

Statistics or Machine Learning

with identification of suitable models.

Forecast horizons

for projection over different time periods.

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Forecasting methodologies

We analyze and combine different forecasting approaches according to needs, sectors and business contexts.

Our goal is to ensure accurate, actionable and aligned results.

with the reality on the ground.

Application cases

Inventory & Supply

Stock shortages or overstocking can hinder your growth.

Thanks to our predictive models, you can optimize stock levels based on sales, seasonality, and logistics lead times, ensuring optimal product availability and smooth management.

stocks forecasting
retail forecasting

Sales/demand

When trends change faster than your predictions.

thaink² analyzes historical data, market signals and external factors to anticipate demand changes and adjust your business strategies in real time.

energy forecasting

​Energie

Plan your human and material resources precisely.

By cross-referencing your activity data, thaink² anticipates production peaks and off-peak periods, for more agile and profitable management.

cash forecasting

Cashflow

Financial visibility should never be a gamble.

Our algorithms anticipate your cash flows to secure liquidity, reduce risks, and strengthen your decision-making capacity.

Key advantages

10k

KPIs

Effortlessly generate forecasts on massive datasets.

50x

Faster Execution

Powered by SPARK technology for unmatched speed

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Fast-track onboarding

Build a forecasting culture in days, not weeks or longer.

Instant, secure, and ready-to-use access to thaink²'s solution

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R Package

(Github)

Having trouble producing accurate forecasts ?

Even when using advanced forecasting techniques, roadblocks can make your predictions unreliable.

❌ Too much data, poor data quality

❌ Lack of explainability

❌ Choosing the right model is complex

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