AI Governance frameworks, adversarial AI Red Team testing, Prompt Injection Defense, and OWASP LLM Top 10 assessment — four disciplines, one coherent view of whether your AI systems can be trusted.
Four pages, four disciplines, all part of the same trust story — not four disconnected tools.
Enterprise AI governance mapped to NIST AI RMF, ISO 42001, and the EU AI Act — risk management, model audits, and responsible-AI framework implementation for regulated industries.
NIST AI RMF · ISO 42001 · EU AI ActAdversarial testing for LLMs and AI agents — jailbreak attempts, data exfiltration paths, and agent-permission abuse, mapped to MITRE ATLAS.
MITRE ATLAS · Adversarial TestingDirect and indirect prompt injection detection — input validation, instruction-hierarchy enforcement, and RAG/document-pipeline exfiltration defense.
LLM01 · Direct + Indirect InjectionFull LLM01–LLM10 coverage screening — prompt injection through model theft — scored against your stated deployment and use case.
OWASP LLM Top 10 v1.1The same frameworks the AI Trust Suite pages already document — mapped once, referenced everywhere.
One self-serve assessment with a published price; the other three are scoped engagements — booked directly, no sales runaround.
Most vendors sell AI governance and AI security as two separate products from two separate companies — a compliance platform that maps your AI systems to NIST AI RMF or ISO 42001 but doesn't test whether those systems can actually be attacked, sold alongside a security tool that finds prompt injection vulnerabilities but has no opinion on regulatory framework alignment. Buying both usually means two separate contracts, two separate vendor relationships, and no single view of whether an AI system is both compliant and defensible.
A governance framework can confirm that your AI system has documented risk controls, a model card, and an assigned accountable owner — none of which tells you whether the system is actually resistant to a jailbreak attempt or a data-exfiltration prompt. Compliance and security are different questions, and answering only one leaves the other as an open, untested assumption.
A red team report that finds five prompt-injection vulnerabilities is only actionable once someone maps those findings back to the governance controls that should have caught them, and to the regulatory obligations (EU AI Act risk-tier requirements, NIST AI RMF's "Manage" function) that make fixing them non-optional rather than a backlog item.
The AI Trust Suite pages on this platform share the same OWASP LLM Top 10 taxonomy, the same MITRE ATLAS adversarial technique references, and the same governance framework mappings — so a finding on the Red Team page and a control on the Governance page describe the same underlying risk in the same vocabulary, rather than requiring a translation layer between two vendors' incompatible terminology.
Is the AI Trust Suite a single bundled purchase? No — it's four independent disciplines, not a bundle. The OWASP LLM Top 10 Assessment is self-serve at its own published price (₹9,999); AI Governance, AI Red Team, and Prompt Injection Defense are each scoped on a free call since engagement size varies by AI system complexity. The Suite is a way of understanding how the four pages relate, not a separate checkout product.
Do I need all four disciplines? Most organizations start with whichever gap is most urgent — often the OWASP LLM Top 10 screening — and add governance framework mapping or red-team engagement once an AI system moves toward production or a regulated use case.
What about MCP (Model Context Protocol) security? If your AI systems connect to MCP servers, that's a closely related but separately scoped discipline — see the dedicated MCP Security Scanner (tool-permission, auth, and injection-surface audit specific to the MCP protocol).
Every AI Trust Suite page has its own free content. The OWASP LLM Top 10 Assessment is self-serve at a published price; the other three are scoped on a free call. Start wherever your risk is most urgent.