Modular Controls for AI & System Governance
Enterprise Compliance & Governance for AI Assurance
Enterprise Compliance & Governance for AI Assurance
MicroEAI delivers provable AI assurance through a unified compliance infrastructure layer that governs AI behavior using ethics, risk management, and audit controls. The platform correlates AI behavior with multi-source evidence to ensure outcomes are explainable, traceable, and defensible.
Built on ethics-by-design, MicroEAI embeds fairness checks, policy alignment, and responsible AI safeguards directly into governance workflows. Human-in-the-loop oversight ensures accountable review, controlled approvals, and transparent decision-making.
With end-to-end traceability, MicroEAI links AI behavior to internal policies, external regulations, and operational evidence—producing regulator-ready audit reports and a measurable risk posture at both project and enterprise levels.
Ethics-by-Design
Built-in fairness checks and responsible AI safeguards
End-to-End Traceability
Links AI behavior to policies, regulations, and evidence
Regulator-Ready
Audit reports and measurable risk posture dashboards
Oversight Across AI and System Evidence
MicroEAI provides real-time oversight across all AI modalities by detecting bias, hallucinations, prompt injection, unsafe responses, and policy violations. It analyzes outputs from ML models, LLM applications, agentic systems, audio, video, documents, and logs—ensuring every output is explainable, risk-scored, and compliant with organizational and regulatory standards. TSC+ enables organizations to move from reactive audit to proactive, accountable AI operations.
LLM + Infrastructure Compliance View
MicroEAI-Cypher monitors infrastructure activity and AI-enabled application behavior to detect risk and validate policy compliance. It ingests logs from endpoints, identity systems, networks, and applications to uncover misconfigurations, control violations, and compliance gaps—without requiring model or prompt access. Mapped to GxP, ISO, NIST, GDPR, and internal SOPs, Cypher generates audit trails, risk posture, and domain-specific compliance reports for regulated enterprises.
Domain-Aware Prompt & Action Governance
Ethico Agent enables organizations to interact with their governance layer in real time. It evaluates every prompt for compliance with internal SOPs and external frameworks like EU AI Act, ISO 42001, and HIPAA. It draws from an organization-specific corpus and MicroEAI’s domain-aligned external corpus to generate context-aware responses, simulate audits, and trace policy justifications. Autonomous agents drive the experience—transforming static policy documents into an intelligent, navigable, and explainable compliance system.
Healthcare-Specific Fairness Intelligence
MicroEAI enables healthcare and life sciences teams to audit LLM-generated interpretations for bias, fairness, and ethical compliance. It flags hallucinations, demographic disparities, and alignment issues with medical standards—delivering explainability, ethical scoring, and audit documentation. This ensures safe, inclusive, and compliant use of LLMs in diagnostic, decision support, and patient-facing scenarios.
Agentic Governance Layer (TSC+ SDK)
MicroEAI TSC+ SDK wraps around any LangChain, AutoGen, OpenAI Agent, or custom LLM stack — enforcing 500+ real-time governance checks across tool calls, outputs, memory, and reasoning steps. This SDK acts as the control fabric for AI systems, governing tool usage, enforcing scoped access, applying moderation filters, logging rationale, and keeping agent actions within policy — all managed via declarative YAML. Whether you’re deploying copilots, multi-agent systems, or internal LLM apps, MicroEAI delivers the missing layer of AI assurance — trusted, compliant, explainable, and enterprise-ready.
AI Compliance via Infrastructure Logs
A pharmaceutical enterprise engaged MicroEAI-Cypher to evaluate infrastructure logs for cybersecurity risk and compliance oversight—without accessing prompt or model data. Using logs from endpoint protection tools, user sessions, and application activity, the system flagged GenAI-related risks and mapped them to applicable internal SOPs and external frameworks (including GxP and ISO). MicroEAI-Cypher generated per-log risk posture scores, traceable audit trails, and regulatory compliance reports, including formatted audit reports aligned with FDA 21 CFR Part 11—providing the organization with actionable insights for both internal review and external readiness.
BIAS and Fairness Review in Clinical AI Use Cases
A university-affiliated healthcare group leveraged MicroEAI to evaluate LLM-generated interpretations used in patient-facing contexts. The platform flagged biased phrasing, hallucinated statements, and inconsistent framing across demographic groups. Traceability was ensured through explainability layers and ethical scoring, supporting both internal policy assurance and future regulatory alignment.
TSC+ Trust, Safety & Compliance
TSC+ forms the core governance layer for responsible AI. It ensures that AI behavior aligns with internal policies, external regulations, and ethical standards—while remaining transparent and auditable.
Key Capabilities
- Bias & Fairness Controls Detect sensitive attributes, measure fairness signals, and prevent discriminatory outcomes.
- Explainability & Decision Transparency Provide traceable reasoning paths, impact analysis, and compliance-linked explanations.
- Policy Alignment Engine Map AI behavior to internal SOPs and global regulations (EU AI Act, HIPAA, ISO, FDA, OWASP).
- Responsible AI Safeguards Enforce ethical guardrails, abuse detection, and domain-aware controls.
- Human-in-the-Loop Governance Structured reviewer workflows with controlled approvals and accountability.
- Project & Enterprise Audit Reports Generate regulator-ready reports and measurable AI risk posture dashboards.
CSA+ Cyber Security & AI Compliance
CSA+ extends governance beyond model outputs to the operational layer—analyzing infrastructure evidence, system behavior, and misuse patterns to enforce cybersecurity and compliance integrity.
Key Capabilities
- Prompt & Behavioral Risk Intelligence Detect manipulation, misuse patterns, and adversarial behaviors.
- Infrastructure Log Correlation Analyze AI and non-AI logs for anomalous actions, misuse triggers, and policy breaches.
- OWASP Risk Mapping Align behavioral signals to AI and cybersecurity risk frameworks.
- Structured Output Governance Validate structured AI-generated artifacts (e.g., configuration scripts, database queries) for policy compliance and execution safety.
- Cyber-AI Compliance Analyzer Correlate AI behavior with infrastructure telemetry for traceable compliance enforcement.
- Operational Risk Posture Dashboard Provide measurable, enterprise-wide cybersecurity and AI compliance visibility.
MTC+ Multimodal Trust & Compliance
MTC+ ensures that audio and video artifacts associated with AI systems are monitored, evaluated, and governed under the same assurance framework.
Key Capabilities
- Deepfake & Impersonation Risk Detection Identify manipulated or synthetic media that may introduce compliance or reputational risk.
- Media Bias & Representation Controls Evaluate fairness and representation risks in audio and video outputs.
- Media-Based Social Engineering Detection Surface impersonation, phishing, and misinformation patterns.
- Media Compliance Mapping Align media artifacts to internal governance standards and regulatory obligations.
- Evidence-Backed Media Audit Trails Provide traceable, reviewable audit documentation for media-driven incidents
Modular Controls for AI & System Governance
Bias scoring, multi-output prompt validation, ethical risk flags, compliance matching, and audit assurance across AI, media, and infrastructure.
Unified Compliance Infrastructure Layer
MicroEAI operates as a centralized compliance infrastructure layer that governs AI behavior across models, operational evidence, and media artifacts.
It enforces consistent policy alignment, measurable risk controls, and audit-ready assurance at enterprise scale.
Ethics & Responsible AI Controls
Ethics is embedded directly into governance workflows, ensuring AI behavior aligns with fairness, accountability, and regulatory expectations.
Responsible AI safeguards prevent bias, misuse, and policy violations before risk becomes impact.
Audit Assurance Layer
Governance decisions are converted into regulator-ready documentation and measurable assurance artifacts.
MicroEAI provides project-level audit reports and enterprise-wide AI assurance with defensible evidence.
End-to-End Traceability Engine
Every AI outcome is linked to supporting evidence, compliance mappings, and risk decisions.
Traceability ensures transparency from AI behavior through policy evaluation to final assurance.
Risk Intelligence & Posture Dashboard
MicroEAI transforms fragmented signals into a measurable AI risk posture.
Leadership gains real-time visibility into compliance health across projects and enterprise environments.
Structured Output Governance
Structured AI-generated artifacts are validated for compliance and execution safety before deployment.
This prevents unsafe automation, configuration misuse, and downstream system risk.
Prompt & Behavioral Risk Intelligence
MicroEAI detects manipulation, adversarial signals, and misuse patterns that threaten compliance integrity.
Behavioral intelligence ensures AI systems remain aligned under real-world operational conditions.
Infrastructure & Operational Evidence Analysis
AI governance extends beyond models by correlating operational logs and system signals with AI behavior.
This ensures compliance enforcement reflects real-world execution, not theoretical behavior.
Media Trust & Compliance Controls
Audio and video artifacts associated with AI systems are governed under the same compliance and risk framework.
Media-driven risks such as impersonation, misinformation, and bias are detected, evaluated, and documented.
Why AI Oversight Requires Infrastructure-Level
Governance
Modern AI risk spans models, prompts, logs, and media. MicroEAI enforces compliance, ethics, and traceability at infrastructure scale—beyond observability alone.
Enable explainability, audit assurance, human-in-loop oversight, and regulatory compliance across AI, media, and infrastructure signals.
Clause-level traceability across datasets, models, multi-event LLM outputs, logs, and policies with automated governance alignment.
Detect unsafe completions, abuse triggers, policy breaches, prompt misuse, and infrastructure anomalies across LLMs, ML systems, agents, and logs.
Fairness checks, sensitive attribute audits, reviewer workflows, and verifiable checkpoints enforce ethical behavior across text, media, and system actions.
