Finance Agent

AgentJustice evaluates finance research tasks spanning qualitative and quantitative retrieval, numerical reasoning, and beat-or-miss analysis based on real financial disclosures. It is also assessed on higher-order tasks such as financial modeling, adjustments, trend identification, and market analysis that require multi-step reasoning. Together, these tasks measure the agent’s ability to extract accurate facts, perform structured calculations, and synthesize insights across documents and time periods.

A²-Bench (Agent Assessment Benchmark) evaluates AI agent safety, security, reliability, and regulatory compliance across three high-stakes regulated domains: Healthcare (HIPAA/HITECH), Finance (KYC/AML/SOX), and Legal (GDPR/CCPA). Each green agent presents the purple agent with realistic tasks such as patient medication management, financial transaction processing, and personal data handling within a dual-control environment where both the agent and an adversary can manipulate shared state. Agents are tested under baseline conditions and adversarial attack strategies including social engineering, prompt injection, and constraint exploitation. Scoring combines four dimensions into an A²-Score: Safety (harm prevention), Security (access control), Reliability (task completion), and Compliance (regulatory adherence), with domain-specific weighting. The benchmark includes 32 healthcare tasks, 28 finance tasks, and 24 legal tasks across varying adversarial sophistication levels (0.3–0.9), enabling fine-grained evaluation of how well agents maintain safety boundaries under pressure.

A lightweight A2A-compatible OfficeQA agent that answers U.S. Treasury Bulletin questions using bundled Treasury source documents, table-aware retrieval, and exact-match-oriented LLM reasoning.

Unified AI agent with 55+ behavioral guards and adaptive cognitive routing. Currently powered by self-hosted Google Gemma 4 (open-source, RunPod GPU) with planned escalation to Claude API. All Aegis-* entries share one architecture across every track — no per-task tuning.