We help Regulated Industries securely adopt, assess, govern, and operate AI systems with confidence.
Click any pillar to explore specific capabilities and advisory outcomes.
Help executive leadership and risk committees understand, prioritize, and manage AI security risk before capital allocation and architectural commitments.
Develop enterprise-wide AI security roadmaps aligned with business objectives and threat tolerances.
Holistic evaluation of AI systems, data pipelines, model assets, and business logic dependencies.
Deep-dive architecture assessments of LLM stacks, RAG vector stores, and orchestration middleware.
Design AI risk oversight committees, operating models, and clear cross-functional accountability.
Security auditing and contractual risk evaluation of third-party foundation models, SaaS AI tools, and APIs.
Independently test whether AI systems, models, and tool-calling agents are secure, resilient, and attack-proof before they reach production.
Adversarial penetration testing simulating advanced threat actors against LLMs, agent workflows, and plugins.
Comprehensive testing across direct system prompt overrides, indirect data-driven injections, and jailbreaks.
Testing model weight inversion, data memorization, evasion perturbations, and hallucination vulnerabilities.
Validation of tool-calling permissions, unauthorized database write boundaries, and multi-agent privilege boundaries.
Auditing open-source checkpoints, fine-tuning datasets, training pipelines, and embedding model integrity.
Rigorous security gate sign-off verifying controls before live deployment to end customers or staff.
Protect AI systems, APIs, and autonomous agents while they operate live in production environments.
Runtime monitoring and inline blocking of unauthorized agent actions, file access, and API calls.
Real-time semantic filtering for prompt injection, toxic content, data leakage, PII redaction, and topical drift.
Dynamic rule evaluation and context-aware enterprise access controls across LLM transactions.
Telemetry tracking agent decisions, confidence distributions, tool invocation trees, and anomalous loop behaviors.
Real-time SIEM/SOC integration for specialized AI threat events, jailbreak attempts, and distributed scraping.
Establish management systems, policies, standards, and regulatory audit readiness across global and domestic frameworks.
Full lifecycle advisory and gap analysis to achieve ISO/IEC 42001 AI Management System certification.
End-to-end framework implementation for managing organizational AI risks, responsibilities, and documentation.
Alignment with NIST AI RMF, RBI FREE-AI framework, SEBI mandates, and CERT-In directions.
Drafting actionable internal AI policies, developer standards, acceptable use guidelines, and vendor thresholds.
Comprehensive cataloging and continuous risk scoring of all enterprise models, agents, datasets, and third-party AI.
Prepare boards, executives, developers and operational teams to understand, operate, and govern AI systems safely.
High-level briefings on fiduciary obligations, liability, systemic AI risk, and board oversight mechanisms.
Practical sessions for C-suite leaders on risk prioritization, regulatory developments, and AI budgeting.
Hands-on defensive engineering for AI/ML engineers on prompt injection prevention, sanitize layers, and safe tool use.
Interactive adversarial training for internal security teams to evaluate LLMs and agentic vulnerabilities.
Comprehensive lead implementer and auditor training for governance, compliance, and internal audit staff.
