Predict What Sells Before It’s
Searched. Stock Before It’s Needed.

Use AI to Outpace Demand Shifts, Minimize Waste, and Maximize Margins.

Forecast Smarter. Waste Less. Grow More.

Demand uncertainty erodes margins. At Indus Net Technologies (INT.), we deploy AI forecasting models to anticipate demand, cut waste, and ensure shelves are always stocked right.

Forecasting isn’t planning — it’s profit protection.

0 %

improvement in demand forecast accuracy thanks to AI predictive analytics (edstellar)

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of retail leaders identify AI as critical for supply chain and sales improvement (edstellar)

What AI‑Driven Forecasting Must Enable in Today’s Retail Landscape

Retailers need forecasting tools that are predictive, adaptive, and omnichannel-aware — built to handle uncertainty, not just history.

Multivariate Demand Models

Combine sales history with weather, seasonality, holidays, influencer trends, and POS velocity

SKU-Store-Day Level Forecasting

Hyper-granular predictions across product, location, and time dimension — auto-refreshed daily

Real-Time Demand Signal Detection

Auto-detect demand spikes from social mentions, web traffic, loyalty behavior, or search volume

Promotional Impact Simulation

Model what-if scenarios for BOGO, bundles, flash sales, and optimize discount depth

Channel-Aware Forecasting

Distinguish between footfall-based demand and app/web/marketplace patterns

Stock & Reorder Optimization

Smart replenishment triggers that balance cost of stock vs. cost of lost sale

Return & Markdown Forecasting

Predict return rates and plan profitable exit strategies for low-velocity products

Collaboration Portals

Shared demand view for category managers, planners, vendors, and supply chain partners

In modern retail, the edge doesn’t come from selling more — it comes from anticipating smarter.

Why INT. Builds Forecasting Systems That Think Like Retailers

We build intelligence at the core of your demand stack — connecting storefront, inventory, weather, web, and behavior to deliver decisions, not just reports.

Retail-Trained Forecasting Models

Built using industry-specific datasets and retail ontology — from fashion to electronics to groceries

Custom ML Pipelines

Fine-tuned to your product categories, store clusters, and planning rhythms

Integration with ERP, POS & Commerce Platforms

Real-time sync with stock, transactions, campaigns, and shipment schedules

Dynamic Assortment Optimizers

Suggest ideal mix per store or region — based on margin, trend velocity, and past lift

Forecast Accuracy Dashboards

Visualize prediction accuracy, variances, and explainability across SKUs and stores

Elastic Scaling for Peak Demand

Handle millions of daily forecasts with cloud-native infrastructure

With INT., your forecasts adapt faster than the market — and get sharper with every cycle.

case study

Retailer Achieves 35% Forecast Accuracy Gain and 18% Lower Stockouts with INT.’s AI-Driven Forecasting

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75%

reduction in bounce rate from mobile users.

18%

improvement in average session time on mobile devices.

Get a Free Demand Forecasting & Inventory Planning Audit

We’ll benchmark your current forecasting models and identify where machine learning can unlock higher margins and lower missed opportunities.

You’ll receive:

  • Forecast error variance heatmap
  • Demand signal input coverage score
  • Assortment & promotion impact analyzer
  • AI-readiness and integration stack evaluation
WHO WE ARE

At INT., excellence and innovation drive everything we do.

We go beyond maintaining operations—we empower businesses with data, insights, and best practices to stay ahead in an ever-evolving digital landscape.

Years of Excellence
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Offices Worldwide
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