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Agentic AI for next gen demand planning

The challenge organizations face with demand planning is that it’s too important to leave to spreadsheets, and too human to hand entirely to algorithms. Forcastra unifies AI-driven forecasting, cross-functional S&OP.

Forcastra unifies AI-driven forecasting, cross-functional S&OP, and live scenario planning into one platform. It is built for planners who need to move fast, stay aligned, and take full ownership of the final number. It removes the friction that stalls enterprise AI, so intelligence drives the decisions that matter. 

$5M+
Savings unlocked
5,000+
Products forecasted
200k+
Predictions made

Why Forcastra AI

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Modular and agentic architecture
 
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Proven gains in forecast accuracy, backed by measurable inventory improvements

 

 

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Lower total cost of ownership than legacy planning systems
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True S&OP collaboration inside the platform 

 

Design principles

These principles guide every decision we make - what we build, what we skip, and how we measure success.

 

Principle 1: Every forecast must be explainable


When planners can't see why the model landed on a number, they stop trusting it and eventually stop using it. That's why every forecast comes with its reasoning attached: the drivers, the assumptions, and what changed since last cycle.

 

 

Principle 2 : Simulate before you commit


Promotions, new launches, supply constraints can make or break a quarter. Test unlimited what if scenarios before you lock in decisions and reduce surprises later.

 

Principle 3 : Planning is a team sport


Plans fail when forecasts stay siloed in spreadsheets. Forcastra brings cross functional teams into a shared workflow, so alignment happens by default.

 


Principle 4 : Overrides should be governed, not policed

 

Every planner adjustment is captured as a data point. Forcastra records it, attributes it, and measures its impact on forecast accuracy. This feedback loop improves results over time, with governance built directly into the workflow.

 


Principle 5 : If planners don't use it, nothing else matters

 

Forecast accuracy only matters if teams consistently use the system. Every feature we build is assessed on whether it meaningfully supports a planner’s daily work.

 

 

Platform capabilities

 

  • AI-assisted adjustments aligned to planning cycles 

  • Scenario planning enabled

  • Agentic forecasting foundation:  Continuously sense real-time signals, analyze bias, & improve with every planning cycle 

  • Tracks and governs overrides 

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  • Break demand down by driver: promotions, pricing, seasonality, and more.

  • Conversational agent: Ask a question, get a recommendation, and decide the next step 

  • Customizable workflow design 

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  • In-app collaboration through comments, reviews, & approvals 

  • Persona-based in-app workflows and access 

  • Audit trail and traceability based on consensus versions 

  • Agent-supported S&OP cadence: One platform for planning, review, and consensus 

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  • Integration with ERP, supply planning, and reporting systems 

  • Scalable, agent-native architecture with governance by design. 

  • Modular by design

  • Embedded MLOps 

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How Forcastra AI works

Built as a system of agents, not a sequence of steps. Each layer senses, decides, and acts on its own, so that intelligence keeps flowing through the system instead of waiting on a person to push it forward.

 

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Our engagement model

Every engagement is designed to prove value before you scale commitment.

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Discover:Typically, one focused week

We assess your planning maturity, data landscape, and where Forcastra will move the needle fastest.

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Architect & pilot:
Real impact in 4 weeks

We configure Forcastra for your SKUs, channels, and planning cycles, then run a live pilot on real data with real planners.

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Build & scale:
Production-ready, built to scale

We connect to your ERP, deploy governance and monitoring, and train your teams to run the platform.

Ready to see what demand planning looks like when it actually works?

We can set up a live demo built around your data, SKUs, and planning reality.