Pharmacy Case

Project Aporion: How we are reinventing pharmacy purchasing.

Where decades of industry experience meet state-of-the-art AI engineering.

A technological feat doesn't emerge in a vacuum. It emerges where decades of industry experience meet state-of-the-art AI engineering.

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Co-CreationMag. Simon Job, Knowledge Partner, Essenz Apotheken

117Pharmacies pre-registered
July 2026Purchasing module launch
GDPR& EU-AI-Act-compliant

IndustryPharmacies
PartnerMag. Simon Job, Essenz Apotheken
ModuleAI purchasing (Aporion)
LeverOperational edge

Co-Creation

Insider knowledge meets AI excellence.

Solving this problem not just in theory but in radically practical terms takes more than good programmers. That's why, at steps2grow, we always develop our industry solutions together with the strongest players in each respective market.

To build our pharmacy software Aporion, we entered into a strategic partnership with Mag. Simon Job (Essenz Apotheken). The goal: to fuse our partner's far-reaching, pharmacy-specific expertise with our deep software engineering competence.

From the system

This is what it looks like in Aporion.

No mockups, real views from the software: predictive forecasting from a single item to the batch run, the full feature set at a glance, and AI visibility from market analysis to the finished post. Every view can be clicked and examined in detail.

Aporion single-product forecast: recommended reorder level 85 units for two weeks of supply, with accuracy values from 90 to 95 percent across the forecast period.

The order quantity, already decided.

Aporion forecasts demand per item and gives the recommended reorder level, with stated accuracy. What is sufficient stays put. What runs short is shown first.

85 unitsrecommended reorder level = 2 weeks of supply
up to 95 %forecast accuracy across the horizon
multi-yearhistorical sales data as the data basis

Aporion multiple query: item list, analysis period of 32 weeks plus short- and long-term forecast model, the data set is flagged as up to date. — Select the item list, set the period and forecast model, the system computes the whole list in one run.

Aporion multiple forecast as a table: per item it shows stock level, expected sales and suggested order quantity, plus an accuracy of 90 to 95 percent. — Demand and accuracy for the whole item list at a glance. What runs short is shown first.

Aporion home screen with four modules: single query, multiple query, reports and discount lists. — One system, four modules: single and multiple query, BASG reports and discount lists, directly on the inventory management system.

Aporion market analysis with relevance scoring per topic cluster: current market trend 85 percent, new scientific findings 75 percent, seasonal development 65 percent, competitive analysis 70 percent. — AI market analysis: per topic cluster, trends are detected and weighted by relevance, the basis for visibility in AI answers.

Aporion GEO pipeline after completion: landing page created, chatbot trained, social media scheduled, with the next steps towards publication. — From opportunity to finished campaign: landing page, chatbot and social media from a single run.

Aporion GAIO overview with three campaign types: automatic Opportunity Detection, manual promotion campaign and high-performer scaling, all on the same AI pipeline. — Opportunity Detection, promotion campaign, high-performer scaling, all from the same AI pipeline.

Aporion conversion integration: landing page and vector database updated, chatbot trained, new documents and prioritised product recommendations for the assistant. — New content moves automatically into the knowledge base, the chatbot recommends the matching products.

Brand voice, channel, finished post complete with image, approve and schedule.

The Starting Point: The Data Chaos

The modern independent pharmacy is under enormous pressure: the administrative workload is growing rapidly while margins keep shrinking. At the same time, the back offices are awash in data chaos. A patchwork of Google Sheets, Microsoft Power BI, rigid ERP / inventory management systems, and isolated data cockpits prevents any clear overview. The result is an inefficient purchasing strategy that ties up valuable capital and resources every single day. What was missing was a unified system to break open these silos.

The Method: The Knowledge Partnership in Action

The principle of our collaboration is clearly defined: we provide the technology, our partner provides the reality. As an industry-specific knowledge partner, Mag. Simon Job delivers the exact process requirements, KPI definitions, and the complex systematics of purchasing optimization first-hand. steps2grow translates these highly complex operational logics into an intelligent, unified SaaS model. This ensures the system solves precisely the problems that actually cost money in day-to-day pharmacy operations.

The Lab: From Practice, for Practice

We don’t build past the market. What works on paper has to hold up in practice. That’s why selected features and AI models of Aporion are piloted directly in our partner’s real-world pharmacy operations. Through this immediate feedback on practicality and user acceptance in live operation, our models learn faster, and the system adapts to the actual workflows of the pharmacy staff, not the other way around.

The Foundation: Security and Compliance

In the healthcare and pharmacy sector, trust is the most important currency. That’s why Aporion isn’t just technologically leading, it’s a flagship project in regulatory terms too. As the developer, steps2grow ensures compliance with the GDPR. Beyond that, we align the platform with the requirements of the EU AI Act, including risk classification and transparency obligations for every AI feature in use.

The Result: Aporion

What emerged is a platform that tears down data silos, semi-automates purchasing through Predictive AI, and turns gut feeling at the point of ordering into a reliable forecast. Aporion gives pharmacists their time back to focus on what matters: the person standing at the counter. And it makes the local pharmacy the first port of call once again, even when the search has long since started with an AI.

The Result

What emerged is a platform that tears down data silos, semi-automates purchasing through Predictive AI, and turns gut feeling at the point of ordering into a reliable forecast.

117: Pharmacies pre-registered
July 2026: Purchasing module launch
GDPR: & EU-AI-Act-compliant

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