Causum Launches Mars to Enforce AI Rules Before Decisions Are Made

LOS ANGELES, CA – February 24, 2026 – As enterprises race against a ticking clock of stringent new AI regulations, Los Angeles-based Causum today announced a novel platform designed to govern automated decisions before they are executed. The company unveiled Mars®, a “decision-time” AI governance platform, and launched an aggressive market entry program offering a complimentary decision-mapping service that consulting firms typically charge between $15,000 and $150,000 to perform.

The move comes as businesses worldwide face immense pressure to comply with landmark legislation like the EU AI Act and California's updated privacy rules, which for the first time mandate auditable proof of human oversight and risk management for every significant AI-driven decision.

The Regulatory Gauntlet: A Ticking Clock for Compliance

The AI governance landscape is no longer a matter of best practices; it is rapidly becoming a domain of hard law with severe penalties. Two major regulatory frameworks are converging on a single, challenging requirement: organizations must be able to prove, on demand, what decisions their AI systems make, what rules govern them, and that effective human oversight is in place.

In Europe, the EU AI Act—the world’s first comprehensive AI law—sets a critical deadline of August 2026 for most companies deploying “high-risk” AI systems. These systems, which include AI used in employment, critical infrastructure, and credit scoring, must adhere to strict obligations, including continuous risk management, detailed technical documentation, and robust human oversight. Non-compliance carries staggering fines of up to €35 million or 7% of a company’s total worldwide annual turnover, whichever is higher.

Across the Atlantic, California is enforcing its own stringent rules. The California Consumer Privacy Act's (CCPA) regulations on Automated Decision-Making Technology (ADMT) have core compliance obligations that become mandatory by January 1, 2027. These rules require businesses to provide consumers with the right to opt-out of ADMT for “significant decisions” and to access meaningful information about the logic used. Crucially, as legal analysis from firms like Baker Botts has noted, simply having written policies is no longer sufficient. Organizations must implement and prove technical safeguards that can withstand an independent audit.

A Shift from Autopsy to Prevention

Causum argues that the existing market of AI governance tools is fundamentally ill-equipped for this new reality. Most current solutions focus on monitoring AI models and their data streams, analyzing behavior for bias or drift after a decision has already been made. Causum's founder and CEO, Dr. Reza Fatahi, likens this approach to performing a post-mortem examination.

"The governance market built an entire industry around watching AI after it decides. That is an autopsy, not governance," said Dr. Fatahi in the announcement. "You can't un-ring the bell on a bad decision that has already impacted a customer or a critical system."

Mars® is engineered to address this gap by shifting governance from a reactive to a proactive stance. The platform uses what the company calls “ontologically structured knowledge graphs” to formalize an organization's internal policies, ethical guidelines, and regulatory constraints into a machine-enforceable rulebook. When an AI system is about to make a decision, Mars intercepts it and evaluates the proposed action against this knowledge graph in a specialized runtime environment. Only decisions that comply with the pre-defined rules are permitted to execute.

This “decision-time” enforcement provides a clear, auditable trail that demonstrates not only that policies exist, but that they are being actively enforced on a per-decision basis, directly addressing the core demands of the new regulations.

Performance and a Cost-Free Head Start

To prove its efficacy, Causum benchmarked Mars® against ValuePrism, a proxy for evaluating key decision-maker logic. According to the company, Mars demonstrated an 82% mean accuracy across 900 evaluations. The results reportedly showed it outperforming hardened retrieval-augmented generation (RAG) systems by a factor of 2.2 and standard zero-shot language models by 4.2. These figures suggest a significant leap in accurately interpreting and applying complex organizational rules compared to other advanced AI techniques.

Causum connects this governance gap to the slow enterprise adoption of more advanced AI. A 2025 Deloitte study found that only 11% of organizations have deployed agentic AI—systems capable of autonomous action—into production. Causum posits this is not due to a lack of technological capability, but a lack of infrastructure to safely govern such powerful systems.

To accelerate adoption and help companies prepare for the regulatory deadlines, Causum has launched its Key Decision-Making Authority (KDMA) program. The initiative offers the first 25 qualifying organizations in regulated industries a structured inventory of their AI decisions at no cost. This deliverable—a foundational step in any serious governance effort—involves identifying all AI decision points, mapping the rules and authorities that govern them, and creating a benchmark dataset. Participants in the program will retain full ownership of this dataset with no further obligations, giving them a critical head start on their compliance journey.