Exopen is a cloud-based platform for data-driven business performance management, reporting and analysis. We gather data from ERP systems, CRM and other data sources into a shared, harmonised data foundation. This lets CFOs, finance teams and management groups work more efficiently with reporting, forecasting, analysis, AI and decision support.

No. Exopen builds on top of the systems you already use. You keep working in your ERP systems and other operational systems as usual. Exopen extracts, structures and harmonises the data for further reporting and analysis in tools like Excel, Power BI, Exopen AI or Exopen's own tools.

Exopen connects to your existing systems and handles the data flows into the platform. These can be ERP, CRM, project systems, time tracking systems or other relevant data sources. We take responsibility for keeping the integration flows working, monitored and evolving over time. That reduces the need for manual exports, in-house integration projects and person-dependent handling.

A shared data foundation means that data from several systems is collected, structured and quality-assured in a way that makes it usable for reporting, analysis and steering. It creates one common version of the numbers, even when you use multiple ERP systems, different charts of accounts, currencies, companies or data sources.

Yes. That is a central part of Exopen's offering. With Exopen you can keep working in familiar tools such as Excel and Power BI, but with a more reliable and up-to-date data foundation behind them. You can also use Exopen's own tools for reporting, planning, AI and analysis.

Traditional BI tools often visualise data, but don't always solve the underlying problem: that the data is scattered, unstructured or hard to trust. Exopen combines integrations, data modelling, quality assurance and analytics tools in a managed platform. That way you don't just see the data – you can trust it and use it for steering, reporting, forecasting and AI.

Yes. Exopen creates the structured and quality-assured data foundation needed for AI to become useful in practice. With Exopen AI you can explore your data through natural dialogue, find anomalies, discover correlations and get faster insights based on harmonised data from across the business.

Exopen is built on Microsoft Azure and modern principles for secure cloud infrastructure, data storage and access control. The platform is developed for companies with high requirements for security, traceability and control. You own your data, while Exopen helps you make it available, structured and useful for the right people and the right tools.

Exopen is especially well suited for companies and groups with multiple systems, multiple legal entities, complex reporting or high demands on data quality. Typical customers are organisations where the CFO, finance team and management need better control, faster reporting and a more scalable foundation for analysis, planning and business performance management.

We usually start with a walkthrough of your systems, data sources, reporting needs and goals. Then we set up the relevant integrations, build the data foundation and create the reports, analyses or tools you need. The goal is to quickly establish a stable foundation that can grow with the organisation over time.

Exopen acts as a central integration and transformation layer that standardizes and harmonizes financial and operational data from ERP and business systems. It is an enabling layer with deep integration logic and a unified data model, not just a set of generic connectors.

Exopen uses a shared financial and operational data model. It standardizes data across all connected sources so every report builds on the same structure, regardless of which ERP the data came from.

Yes. Exopen has ready-made integrations for more than 45 cloud-based ERP systems, plus generic integration engines that understand ERP mapping and can harmonize data from other business systems.

When each system defines data differently, the same figure can mean different things in different reports. That leads to manual reconciliation, delayed insight and weak data quality — which undermines trust in both reports and forecasts.

More than simple connectors. It requires integrations that understand the business logic of each source system, a centralized data model that standardizes financial and operational data, and automated quality control so every figure can be traced back to its origin.

AI is only as good as the data behind it. When financial and operational data sits in one shared, quality-assured structure, AI can be used with control and traceability — answering questions against your KPIs, detecting deviations in margin and cash flow earlier, and analyzing the whole group in one context.