Organizations face challenges in identifying and managing conflicts of interest and external influences, which can lead to financial losses, fraud, reputational damage, and compromised decision-making. Existing methods for detecting these conflicts are often manual, time-consuming, and unable to process large datasets effectively. This lack of transparency and accountability erodes trust among stakeholders and the public.

Conflixis offers an AI-powered risk engine that analyzes extensive internal and external datasets to proactively identify conflicts of interest and external influences within organizations. The platform enhances transparency and accountability in decision-making by uncovering hidden relationships between staff, clients, suppliers, and other parties. By monitoring these conflicts, Conflixis helps organizations ensure fair and transparent decisions, promoting trust among stakeholders and mitigating potential risks. The system also facilitates compliance with legal and regulatory requirements, reducing the risk of reputational and financial harm.

AI-driven analysis of internal data (e.g., employee records, procurement data) to identify potential conflicts.

Aggregation and analysis of publicly available data to uncover external relationships and influences.

Relationship identification engine that explores millions of data points to identify connections.

Benchmarking capabilities to contextualize risk findings against similar organizations.

Identification of external influence by analyzing employee interactions with third parties.

Customizable reporting and alerting to highlight critical conflicts and risks.

Conflixis primarily targets large organizations across various sectors, including healthcare, finance, and government, that require robust conflict of interest detection and management solutions.