Leveraging Agentic and Generative AI for Compliance Evaluations

AI is more than a typical new technology. It is shaking the foundations of global economic models and creating both massive chaos and opportunity. While AI was originally named after algorithms that loosely mimic the human brain, the reality is that today the term encompasses many different approaches. Some of them vastly outpace the human brain while others still fail to compete with our natural cognitive gifts.

Economic growth requires innovation, and AI is likely the greatest innovation of human civilization. But because AI technologies are varied and technical, it is often difficult for investors and buyers to evaluate and differentiate various AI approaches. This phenomenon gives rise to massive hype cycles, which AI developers use to secure investment for further development, but which also lead to disenchantment and tech pessimism. These dynamics do not lessen the sheer analytical power and potential of AI to transform business operations.

Generative AI burst onto the world scene in November 2022 with the public release of OpenAI’s ChatGPT. Since then, generative AI applications have taken the world by storm, but few enterprise-grade, scaled applications have made their way into common use. While core Large Language Model (LLM) technology is useful for chats and human-style interaction with machines, scaled and enterprise applications are not as obvious or easy to enable.

At Vero AI, AI and LLMs are viewed as investigative, statistical technology that helps us understand data. What makes AI special compared to traditional, pre-AI statistics is its ability to make sense of complex, messy, unstructured data (such as text and imagery) in a way that was impossible just a few years ago. While there are many controversial uses of AI, such as those involving facial recognition that may result in bias, invade privacy, or make unjustified decisions about human lives, at its base level AI is just a statistical approach. It is what we do with the results that can be either beneficial or harmful to humanity. While generative AI is core to the Vero AI solution and capability, it is not on its own sufficient to deliver the platform’s results.

Generative AI enables powerful natural language interaction with machines, but is subject to the need for prompt engineering, hallucinations, and unreliability of generated output. The Vero AI approach takes the best of generative AI but combines it with more precise coding that uses traditional machine learning and quantitative statistical approaches. On top of this, Vero AI allows for easy tailoring and customization of outputs, giving users unlimited ability to fine-tune their results.

Vero AI vs. Traditional Generative Chatbots

Generative chatbots are aimed at individual users who want to dynamically interact with content by asking questions and getting human-like generated answers. In contrast, Vero AI is a multi-agent, multi-modal platform that leverages neurosymbolic AI—building logic on top of LLM functionality. LLMs are deep learning models trained on huge amounts of data. They are very good at interpreting and carrying out human commands. Vero AI uses LLMs to analyze text and other forms of data, and compare them to various criteria (such as controls in a compliance framework or procurement requirements). The Vero AI engine reports the evidence for each evaluation, so auditors or other users can verify it.

Vero AI Analytics Platform: Core Components

The Vero AI analytics platform is a generative AI-native intelligence engine capable of precisely automating human reasoning and logic at scale. It uses a variety of AI and agentic processes, including:

• ​Document Ingestion Architect: Extracts and retrieves relevant content from diverse document formats using web scraping and parsing techniques.
• ​Intelligent Document Ingestion Engine: An AI-driven system that autonomously monitors and ingests new documents from a client’s folder, triggering the processing pipeline for continuous, real-time analysis.
• ​Semantic Dissection Engine: Segments extracted content into context-aware, meaningful units for streamlined processing.
• ​Contextual Embedding Engine: Converts segmented text into rich contextual embeddings using advanced transformer models.
• ​Relevance Evaluation Processor: Analyzes the embeddings by mapping them to predefined evaluation criteria to assess their relevance.
• ​Dynamic Relevance Optimization Engine: Uses advanced language models to dynamically assess and reorder text chunks based on contextual precision, ensuring only the most relevant and high-value chunks are selected for downstream processing.
• ​Quantitative Scoring Engine: Computes numerical relevance scores based on how well the content aligns with the evaluation criteria.
• ​Insight Synthesis Module: Transforms evaluation results into actionable insights and concise, high-level summaries.
• ​Strategic Guidance Orchestrator: Provides prescriptive recommendations and strategic next steps based on evaluation outcomes.
• ​Cognitive Validation Module: Cross-references outputs with trusted sources to filter out inaccuracies and prevent hallucinations, ensuring data accuracy.

Customizable Scoring and Evaluation

While Vero AI can score any set of standards automatically, a key feature is that users can tweak the scoring to enable more complex evaluative logic. For example, if a certain control requires comparison of one value to another in a different document, or another specific operation, this can easily be added to the scoring logic. This fine-tuning capability allows Vero AI’s platform to automate much of the review process with maximal accuracy.

Comparison: Off-the-Shelf Generative AI vs. Vero AI

• ​Scale: Off-the-shelf generative AI evaluates one document at a time, while Vero AI can process hundreds of controls across hundreds of documents simultaneously.
• ​Helpfulness: Vero AI populates comprehensive results and actionable insights, while generic AI may produce misaligned summaries with unnecessary information.
• ​Consistency: Vero AI ensures a consistent process across projects, while generic AI relies on unpredictable user queries.
• ​Security: Vero AI keeps your data within secure walls (e.g., Google Cloud Platform), while generic AI may share data with large tech companies for training.
• ​Purpose: Vero AI is purpose-built for compliance and audit needs, not just general chat.

Vero AI Platform Outputs

The Vero AI analytics engine produces detailed reports that auditors can use to decrease review time and enhance accuracy. For example, in a CMMC Level 2 Readiness Assessment, the platform processes evaluations, maps evidence, and summarizes requirements met, potential gaps, and details for each control. The platform also provides diagnostics and actionable recommendations.

Example: ISO 27001 Audit Score Improvement Guide

• ​Rapid Score Improvement Strategy: Outlines critical areas where documentation and evidence updates will yield the greatest improvement in audit score.
• ​Key Areas to Prioritize: Identifies impactful documentation gaps, such as information security awareness, risk management, leadership commitment, and access control.
• ​Accelerated Document Creation with LLM Support: Provides prompt templates and guidance for creating or enhancing required documents (e.g., Security Policy, Risk Assessment, Statement of Applicability, Access Control Policy, Incident Response Plan).

AI Agents in Vero AI

The core Vero AI analytical engine can be deployed for many purposes, including:

• ​Compliance Evaluation Agent: Evaluate any content across any compliance frameworks, saving auditor time and enhancing accuracy.
• ​Questionnaire Agent: Instantly complete security questionnaires and RFPs using your own database of policies and previous responses.
• ​ROI Agent: Upload quantitative outcome data to evaluate the effectiveness of business processes and policies.
• ​Policy Agent: Suggest and tweak policies relevant for your business using your own content and external frameworks.
• ​Third-Party Risk Agent: Automate vendor assessments to ensure compliance throughout your partner ecosystem.
• ​Procurement Agent: Create custom procurement standards and quickly choose between multiple vendors.
• ​Custom Agents: Process any data against any requirement, such as analyzing organizational survey comments for themes and red flags.

Data Security and Privacy

Vero AI prioritizes data security and privacy, adhering to industry best practices and regulations like SOC 2 and ISO 27001. Key principles include data minimization, transparency, and compliance. Vero AI employs a Secure Development Process, secure coding practices, and regular security testing to protect client data. Risks associated with third-party software and libraries are managed carefully, and test data is handled with care.

The Future of Compliance

Vero AI envisions a future where organizations can know everything about their compliance stance, all at once and all the time. The platform enables monitoring of legislative compliance with current and future legislation globally. Beyond compliance, Vero AI allows organizations to monitor the effectiveness and ROI of business processes, merging compliance with business intelligence. Advanced processing yields risk and predictive analytics to help control the future of your business.