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Smarter forecasts, leaner stock. AI for food manufacturers.

Startup House is a Warsaw-based technology company implementing AI for food manufacturers and FMCG brands in Poland: demand forecasting, production planning, and plant digitalization. Founded in 2016, with over 100 products delivered.

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Trusted by:

Siemens
Geberit
PwC
Toyota
Lexolve
Rainbow
Chooose

Do these challenges

sound familiar?

Promotions destabilize sales forecasts.
Volatile raw material prices threaten operating margins.
Excess stock in the warehouse, gaps on the shelf.
Seasonality disrupts production planning.
Your ERP ignores dynamic market signals.

AI for production planning in FMCG

AI Demand Planner

Analyzes data, captures dependencies, and turns market signals into production plan recommendations. Supports your S&OP process — and where there is none, takes over its role.

How it works:

We combine hard data from your ERP with market signals your ERP can't see. An AI-powered multi-agent system delivers recommendations along with the data reasoning behind them. With AI Demand Planner, you make decisions with a full view of risks and opportunities.

What you get:

Decision Panel

Alerts, risks, and recommendations, all in one place, updated at a frequency you set.

AI Chat

Talk to your data. Check any recommendation and get the analysis you need.

Book a presentation

Our AI products

Pick what best fits your business needs:

KnowHub

All company knowledge in one place

KnowHub

Turn scattered procedures, requirements, and internal policies into a single source of truth.

Always up-to-date data

Faster onboarding on the production floor

Zero hallucinations: answers with direct source references

SmartSearch

Search that understands intent

SmartSearch understands intent, verifies facts against your data, and points to the exact source of every answer.

Analyzes full source content, not just tags

Intent-based search with condition prioritization

Fact verification for every result

AI Interface Layer

A conversational AI interface for your platform

Add an AI layer to your platform's interface, without rebuilding the whole system.

A ChatGPT-style interface with your branding

Higher feature adoption across the platform

Fewer routine queries, less load on Customer Support

Working with us, step by step:

01

AI Readiness Audit

We review and organize your company data and determine which market signals influence your demand.

02

Pilot

We launch the pilot and test the results.

03

Deployment

Integration with your ERP and production systems, without stopping plant operations.

04

Monitoring

Calibration and ongoing development of the production management system.

01

AI Readiness Audit

We review and organize your company data and determine which market signals influence your demand.

02

Pilot

We launch the pilot and test the results.

03

Deployment

Integration with your ERP and production systems, without stopping plant operations.

04

Monitoring

Calibration and ongoing development of the production management system.

Why you can trust us:

  • ISO 27001 compliance

  • GDPR compliance

  • Hosting and data processing in the EU

  • We do not train AI models on your company's data

  • Data encrypted in transit and at rest

See how we've helped our clients:

See how we've helped our clients:

Cloud-based platform for Siemens Financial Services in Poland

An omnichannel SaaS application that enables automated credit decisions 24/7 and cuts the leasing application process to 2 minutes.

Embedded AI in a cybersecurity platform serving Fortune 500 clients

By embedding a conversational AI layer into the platform, we cut customer onboarding time by 95% and turned a quarterly reporting tool into a daily decision-support system.

Read the case study

Frequently Asked Questions

No. A data audit is part of the first stage of our engagement. We check which signals actually move your demand and what data you already have. Sales history from your ERP is usually enough to begin. Gaps are identified and worked around, not treated as blockers.

Two things: access to your historical data (ERP, sales, promotions) and one business person who validates the system's recommendations with us. That's the difference between a demo and a system your team trusts.

That depends on how mature the process is in your company. If you have a working S&OP, the system supports every stage of it — from demand planning to the executive review — delivering forecasts and recommendations with clear reasoning. If there's no formal S&OP in place, AI Demand Planner takes over its function: matching demand to resources continuously, without waiting for the monthly meeting cycle.

We start read-only, in an isolated environment, with everything under NDA. We only access the data scope agreed during the audit, and nothing leaves your environment without your sign-off.

No. Your data stays yours: it grounds recommendations for your business and never trains models used by anyone else. Data is encrypted in transit and at rest.

That's exactly what historical validation is for. Before the pilot, we run the system on your past data and compare its recommendations against what actually happened. You see its accuracy on your own numbers before you decide.

Your ERP looks inward and backward: internal data and sales history. AI Demand Planner also looks outward, at the market signals that move your demand. And instead of another chart to interpret, it gives you a specific production recommendation with reasoning you can expand down to the raw data.

ERP systems including SAP and Comarch, plus warehouse and production systems and external market data sources. Integration is part of the deployment and requires minimal involvement from your team.

Let's talk about your production planning.

We'll check which market signals move your demand.

Book a free consultation

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Startup Development House sp. z o.o.

Aleje Jerozolimskie 81

Warsaw, 02-001

VAT-ID: PL5213739631

KRS: 0000624654

REGON: 364787848

Contact Us

hello@startup-house.com

Our office: +48 789 011 336

New business: +48 798 874 852

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