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DURATION
A Munich-based software company was scaling rapidly, offering a cloud ERP and accounting platform designed specifically for property management companies.
Their platform already supports over 400 property managers and 300,000 housing units, giving each customer a dedicated workspace that mirrors the unique financial logic of their properties.
But as Impower scaled, so did the operational load. The system was processing roughly 100,000 invoices and 700,000 bank transactions every month. Even with a modern SaaS platform, too much of the accounting workflow still relied on manual intervention. This not only slowed down day-to-day operations but also limited how efficiently property managers could use the platform at scale.
They recognized that to stay competitive in a fast-digitizing industry, it had to take a bold step forward: introducing AI-driven automation.
The property management sector faces two key pressures:
The solution was designed for Germany, where the client serves property management companies through its multi-tenant SaaS platform. The platform is built to scale with increasing regulatory, operational, and financial demands specific to the European market.
The solution needed to comply with EU data protection standards (GDPR), ensure trust through transparency, and adapt to diverse financial structures across property managers.
Impower faced three critical challenges:
1. Manual accounting at scale. Despite supporting hundreds of property managers, too much of the accounting process still required human input, creating inefficiencies.
2. Customer needs. Users demanded faster, more reliable tools to manage repetitive tasks like invoice assignment and reconciliation.
3. Competitive pressure. The market was moving toward intelligent automation, and Impower needed to innovate to maintain its position.
Linnify designed and implemented an agentic AI service layer to automate accounting workflows.
Linnify acted as the strategic AI partner, guiding the client through the entire journey, from defining the AI architecture and validating the Proof of Value, to developing, testing, and deploying the agents into production. Our team ensured that the solution not only met immediate operational goals but also laid a scalable foundation for future AI-driven innovation within the platform.
We designed a standalone Agent Service with real-time synchronous endpoints and integrated it with the client’s ERP system through APIs. By applying an agentic AI architecture with contextual memory, reasoning, and monitoring, we ensured the agents could adapt to customer-specific workflows while remaining transparent and auditable.
The measurable impact was substantial: invoice field extraction accuracy improved from around 70% (tested across only 4–5 fields with a single prompt) to 96% across 15 tested fields after our solution was deployed.
On the reconciliation side, automatic mapping of bank transactions increased from 75% to 95%, dramatically reducing the need for manual intervention.
The project successfully automated the most resource-intensive workflows, invoice processing, and bank reconciliation, reducing manual effort and improving scalability. Beyond immediate efficiency gains, it positioned Impower as a forward-looking competitor in the property management industry.
The collaboration highlighted Linnify’s ability to apply agentic AI to multi-tenant ERP systems, proving how complex manual processes can be transformed into scalable, intelligent workflows.
1. What was automated in this project?
The most resource-intensive workflows: invoice processing and bank transaction reconciliation.
2. How quickly was the system delivered?
The first AI agent was deployed into production in just two months.
3. What makes this approach different from traditional automation?
Instead of rigid rule-based systems, the agentic AI used contextual memory and adaptive learning to continuously improve over time.
4. How did this benefit the client’s users?
Manual effort was reduced, accuracy increased, and workflows became more efficient and scalable.
5. How does this project reflect Linnify’s expertise?
It demonstrated Linnify’s ability to design, build, and deliver production-ready AI solutions for complex ERP environments under tight deadlines.
