PLATFORM

    VALIDATE WHAT AI DOES.

    Gadriel AI Behavioral Assurance (GBA) validates the behavior of AI systems — RAG, LLM workflows, agents, MCP, A2A — before they ship. Pre-production, behavioral evidence that the system is ready to deploy and safe to operate.

    WHAT WE DO

    FOR

    Teams building and deploying AI systems — including RAG applications, LLM workflows, agents, MCP, A2A, and AI-powered applications.

    WHO

    Need to prove those systems are accurate, secure, policy-aligned, cost-efficient, and safe to operate — before they create business risk.

    PROVIDES

    Pre-production behavioral validation of AI systems across key dimensions: accuracy, security, authentication, authorization, bias, tool use, agent behavior, and FinOps.

    UNLIKE

    Security-only tools that test one dimension, runtime-only tools that act after risk is already live, or manual testing that is hard to scale and difficult to prove.

    ONLY

    Gadriel validates the behavior of AI-powered systems before they ship — giving teams reproducible, audit-defensible evidence that the system is ready to deploy and safe to operate.

    CANONICAL FRAME
    GADRIEL

    PRE-FLIGHT

    Behavioral validation before deployment.

    COMPLEMENTARY · RUNTIME

    IN-FLIGHT

    Runtime guardrails — complementary category after pre-flight behavioral validation.

    COMPLEMENTARY · OBSERVE

    POST-FLIGHT

    Observability after events occur — complementary category after operation.

    COMPLEMENTARY means these categories matter, but they do not replace Gadriel's pre-flight behavioral validation before autonomous AI ships.

    No aircraft carries passengers without airworthiness certification first. No autonomous AI should reach production without behavioral validation.

    EIGHT PILLARS

    THE VALIDATION SURFACE.

    Eight risk pillars, five mathematical methods, one canonical frame. Each pillar is independently scored, evidenced, and reproducible — the same inputs always produce the same outputs.

    SECURITY

    Adversarial robustness, prompt injection, data exfiltration.

    COMPLIANCE

    EU AI Act, NIST AI RMF, ISO 42001, SR 11-7.

    SAFETY

    Harmful output, jailbreak resistance, content boundaries.

    OPERATIONAL

    Latency, error handling, retry, SLO adherence.

    FINOPS

    Token economics, runaway cost, budget enforcement.

    COHERENCE

    Instruction following, goal stability, output consistency.

    TEAMWORK

    Multi-agent coordination, handoff fidelity, collisions.

    BIAS

    Demographic parity, distributional fairness, drift.

    WHY GADRIEL

    RIGOR

    Reproducible. Audit-defensible. Same input, same output. Math, not opinion. Cosine similarity, KL divergence, spectral analysis, mutual information, PAC bounds.

    OPERATOR

    Built by 25-year cybersecurity practitioners with three USPTO patents — not VC-prompted founders chasing the AI wave.

    CATEGORY

    Pre-production behavioral validation across eight pillars — not observability, not red-teaming-only. We do not blur.

    EVIDENCE INSTRUMENTATION

    Measurable assurance signals, not marketing noise. Quiet confidence. Strong claims when defensible. The work speaks.

    GADRIEL · GBA
    STATUS: CLEARED

    VALIDATE BEFORE YOU SHIP.

    For platform trust owners, CISOs, Chief AI Officers, and model risk managers preparing autonomous AI for production. Run a scoped 4–6 week Proof of Value against your real AI system.

    REQUEST PROOF OF VALUE →
    FAQ

    QUESTIONS, ANSWERED.

    What is Gadriel AI Behavioral Assurance (GBA)?+

    GBA validates the behavior of AI-powered systems — RAG, LLM workflows, agents, MCP, A2A — before they ship. It produces reproducible, audit-defensible evidence that the system is ready to deploy and safe to operate.

    How is GBA different from AI guardrails or runtime protection tools?+

    Guardrails and runtime-protection tools act after risk is already live and typically check a single dimension. GBA validates AI system behavior across eight pillars before deployment — so risk is caught before it reaches users, not just blocked when it appears.

    How is GBA different from observability tools?+

    Observability (Arize, LangSmith, Langfuse) is post-flight — it tells you what happened. GBA is pre-flight — it tells you whether the system should fly at all, with reproducible behavioral evidence.

    Does GBA use LLM-as-judge?+

    No. GBA uses mathematical validation — cosine similarity, KL divergence, spectral analysis, mutual information, PAC bounds. Same input, same output. Reproducible and audit-defensible. We do not use AI to judge AI.

    What are the eight pillars?+

    Security, Compliance, Safety, Operational, FinOps, Coherence, Teamwork, and Bias. Each pillar is independently scored and evidenced.

    What AI systems does GBA support?+

    RAG applications, LLM workflows, single and multi-agent systems, MCP and A2A integrations, and AI-powered applications built on any major model provider.

    Who is GBA for?+

    Platform trust owners, CISOs, Chief AI Officers, Heads of AI, and model risk managers preparing autonomous AI for production in regulated or high-stakes environments.

    Which frameworks does GBA map to?+

    EU AI Act, NIST AI RMF, ISO 42001, and SR 11-7. Each finding is tagged to the relevant control so the validation report drops into existing governance and audit workflows.

    How do I get started?+

    Request a Proof of Value. We scope a 4–6 week pilot against one of your AI systems, run the eight-pillar validation, and deliver a reproducible report you can take to your governance, security, and risk stakeholders.