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The Problem

Hundreds of transactions across Revolut and similar platforms. Receipts scattered in folders like Dropbox.

Hours wasted manually matching everything for your tax advisor. A classic bottleneck for growing companies.

From manual reconciliation to an autonomous Finance Agent

This case study documents the development of an AI agent that takes over operational responsibility in financial administration – secure, scalable, and transparent

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The Architecture: Security by Encapsulation

The agent does not act in isolation. We created an infrastructure that separates AI intelligence from secured cloud execution.

Intelligence Layer: Governs logic and decision-making.

AWS Workbench: Executes code in a secured, sandboxed environment (Security-First).

Connectivity: Direct, auditable access to banking interfaces (Revolut) and document storage (Dropbox).

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The Core Challenge: Financial Reconciliation

Why isn't traditional automation sufficient here?

Traditional automation fails when data is incomplete. If a receipt is missing or amounts differ due to fees, standard scripts stop working.

Our agent was trained to "think" like a human accountant: it matches contexts, recognizes fee structures, and proactively requests missing information.

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60 min Dauer

What exactly does the system do?

01

Operational Workflow: A Daily Routine

The Agent's Workflow

02

Key Results & Lessons Learned

03

Data Privacy & GDPR Compliance

When automating sensitive financial processes, data security is our top priority. Our system design strictly separates intelligence from data storage.

Local Data Sovereignty: All sensitive data is processed within the secured AWS infrastructure (Region: EU/Frankfurt).
No Model Training: We exclusively use APIs that guarantee customer data is NOT used to train global AI models.
Audit Trail: Every access the agent makes to Revolut or Dropbox is fully logged and remains traceable at all times.

Anonymized Processing: Personally Identifiable Information (PII) is masked or anonymized before being passed to the language model whenever possible.
Zero-Retention Policy: Transaction data is loaded ephemerally for processing and is not permanently stored outside of your controlled systems.

WE ARE THE EXPERTS

Not Off-the-Shelf Software. A New Way of Working

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We don't sell finished products; we develop autonomous agent systems for unique business processes.