Auxilius, a Munich-based company building AI-native governance, risk, and compliance technology for enterprises, has closed a pre-seed round of approximately €1.3M led by High-Tech Gründerfonds, with participation from Techstars and several industry-focused business angels.
Founded in late 2025 by Christian Hoppe and James Barnes, Auxilius will use the funding to scale its engineering team and build out its Control Intelligence knowledge graph, the layer that gives each automated control its organizational context by linking risks, controls, and decisions back to the business objectives they are designed to protect.
Addressing The Market Opportunity
Around 80 percent of enterprise controls are still executed manually. Auditors pull samples, second-line teams chase spreadsheets a quarter after the relevant risk has already materialized, and control owners screenshot evidence instead of receiving decision support. Policies are written, but generating traceable, auditable proof of adherence remains a persistent and largely unsolved problem for large organizations.
The result is a compliance function that is perpetually reactive, expensive to run, and structurally unable to keep pace with the speed at which regulatory and operational requirements change.
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How The Technology Works
Auxilius converts company policies, risk-and-control matrices, and regulatory text into deterministic, executable code. Rather than sampling a subset of data for periodic review, the control runs continuously across the full population of data. When a rule changes, the code changes with it, eliminating the lag between regulatory update and compliance response.
The platform’s Control Intelligence knowledge graph provides the organizational context that allows a control to be automated once, deployed across multiple processes, and kept current as regulations and business processes evolve. Internal audit moves from periodic sampling toward continuous assurance. Internal control shifts from quarterly attestation toward ongoing monitoring. The result is a model where audit-ready evidence becomes a byproduct of day-to-day operations rather than a separate, manual exercise.
Growth And Market Traction
Auxilius is already serving its first paying enterprise customers, including European banks and industrial groups, with early results showing faster time-to-value, broader control coverage, and reduced manual effort across compliance functions.
The company was founded by Christian Hoppe, a former EY Equity Partner with 15 years of GRC and SaaS experience, and James Barnes, previously Software Architect at Sopra Steria CSS, with deep expertise in enterprise AI, ERP, and cloud architecture.
Expansion Plans
The pre-seed funding will support growth of the engineering and domain team and continued development of the Control Intelligence knowledge graph. The near-term focus is on deepening automation coverage across enterprise control activities in internal audit, internal control, and operational risk functions.
Looking Ahead
Christian Hoppe, CEO and co-founder of Auxilius, described the shift the platform represents for how enterprises approach assurance: “We’re building a new model for assurance: continuous, auditable, and aligned with the decisions C-level teams have to make under regulatory pressure. The gap we close is between what’s mission-critical for the business and what the underlying data can truly support with auditable evidence. That’s when a control stops documenting compliance and starts informing the decision.”
Hanna Sasse, Investment Manager at HTGF, outlined what drove the firm’s conviction: “What convinced us very early on was Chris and James’ rare domain depth in GRC paired with enterprise-grade engineering and their big vision: making audit-ready evidence a byproduct of day-to-day operations, as regulatory and operational change accelerates. We’re excited to support Chris, James, and the team on this journey.”
About Auxilius
Auxilius is a Munich-based AI-native company founded in late 2025 by Christian Hoppe and James Barnes. The company automates enterprise control activities by converting policies and control rules into deterministic, executable code that runs continuously across the full population of organizational data. Its platform serves internal audit, internal control, and operational teams at European banks and industrial groups, and is building a Control Intelligence knowledge graph to provide organizational context for automated controls at scale.
