Question 1

What is TRUSCOR (Truscore)?

Accepted Answer

TRUSCOR (also searched as Truscore, Truescore, or Trusscore) is an AI risk scoring and AI security testing platform. It is the actuarial standard for agentic AI liability, providing AI risk ratings, AI benchmarks, and AI damage quantification for enterprise AI deployments. TRUSCOR autonomously audits AI systems across API, UI, and OS layers using the SOVA engine.

Question 2

What is the SOVA engine?

Accepted Answer

SOVA (S.O.V.A) is TRUSCOR's autonomous AI security testing engine. It spawns multiple coordinated AI testers that breach, audit, and benchmark enterprise AI systems in real time. SOVA performs AI cybersecurity testing across API, UI, and OS layers simultaneously, generating AI risk scores and AI damage assessments for cyber insurance underwriting.

Question 3

How does TRUSCOR measure AI risk and generate an AI score?

Accepted Answer

TRUSCOR uses the TAFAAR actuarial framework combined with the SOVA testing engine to generate a Sybil Resilience Score (SRS) — an AI risk score rated A through D. Unlike API-only AI testing, TRUSCOR bypasses the API and tests the visual interface directly, measuring real-world AI damage potential, AI loss exposure, and financial risk from agentic AI deployments. The AI score quantifies liability for cyber insurance and actuarial pricing.

Question 4

How does TRUSCOR help with cyber insurance for AI?

Accepted Answer

TRUSCOR provides actuarial-grade AI risk ratings that cyber insurance carriers, Lloyd's syndicates, and underwriters use to price AI liability policies. By quantifying AI damage, AI loss, and maximum probable loss (MPL) from agentic AI deployments, TRUSCOR enables data-driven AI insurance underwriting. The platform also operates a reciprocal insurance exchange where AI companies can mutually insure each other.

Question 5

What is AI security testing and how does TRUSCOR perform it?

Accepted Answer

AI security testing is the process of adversarially probing AI systems for vulnerabilities including jailbreaks, data leaks, prompt injection, and unauthorized actions. TRUSCOR performs AI security testing autonomously using the SOVA engine, which conducts AI penetration testing, AI cybersecurity assessments, and AI vulnerability scanning across all attack surfaces — API endpoints, user interfaces, and operating system layers.

Question 6

What is agentic AI risk and why does it matter?

Accepted Answer

Agentic AI risk refers to the financial, operational, and security exposure created when autonomous AI agents are deployed in enterprise environments. Unlike traditional AI, agentic AI can take actions, make decisions, and interact with systems independently — creating new categories of AI damage and AI loss. TRUSCOR specializes in quantifying agentic AI risk through autonomous AI benchmarking and actuarial AI risk scoring.

Question 7

How does AI benchmarking work at TRUSCOR?

Accepted Answer

TRUSCOR's AI benchmarking goes beyond standard AI evaluation. The SOVA engine performs adversarial AI testing that benchmarks AI systems against real-world attack scenarios, generating an AI score across categories including authentication resilience, data protection, logic integrity, PII exposure, security posture, and denial-of-service resistance. Each AI benchmark produces an actuarial AI risk rating used for AI insurance pricing.

Question 8

Who is TRUSCOR built for?

Accepted Answer

TRUSCOR serves enterprises deploying agentic AI at scale, CISOs and CTOs responsible for AI security, cyber insurance carriers pricing AI risk, Lloyd's syndicates writing AI liability policies, and actuaries modeling AI damage and AI loss scenarios. It is built for the $400B enterprise AI deployment wave where AI risk quantification and AI insurance are becoming critical.

Question 9

What is AI damage and AI loss quantification?

Accepted Answer

AI damage refers to the financial, reputational, and operational harm caused when AI systems fail, are breached, or behave unexpectedly. AI loss quantification is the actuarial process of estimating the maximum probable loss (MPL) from AI incidents. TRUSCOR's SOVA engine models AI damage scenarios and calculates AI loss figures that actuaries and cyber insurers use to price AI liability coverage.