AI can’t replace GRC professionals, but it can supercharge them

You know your GRC program best, which means you also know its limits. The Anecdotes suite of AI agents is here to help you do things that were previously impossible and to increase your program efficiency along the way. It's time to say goodbye to past restraints and say hello to the supercharged future of GRC.

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Data-powered, AI-enhanced. The better way to GRC.

If you had unlimited time and zero deadlines, maybe you could manage the perfect GRC program on your own. But since that’s never going to happen, we’ve created a better way. The Anecdotes platform gives you data-driven automation, to save you valuable time and effort, and AI agents work alongside you to help you build a stronger GRC program - effortlessly.

Meet the AI agents powering the next era of GRC

Policy Guardian

Keep your policies always in check, with the agent continuously analyzing them for operational gaps and ensuring full compliance.

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Scale Advisor

Scale and expand your GRC program with zero effort by allowing the agent to leverage your existing work to build out your program.

Screenshot Activator

Unlock deep analysis and scoping capabilities for your manual evidence to gain valuable insights into your posture.

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AI + human expertise:
A partnership you can trust

At Anecdotes, AI is a choice, not a requirement. You have full control over when and how you use any of the AI agents. When you do use our agents, we ensure that your data remains yours. We never use your data to train AI models for other companies - your insights remain your competitive edge.

Frequently Asked Questions

What is AI-driven GRC?

AI-driven GRC uses artificial intelligence to automate and enhance GRC processes. By analyzing real-time data, AI tools can help organizations meet regulatory standards more efficiently and dynamically, adapting to the unique needs of each organization.

How does Anecdotes' AI technology work with my existing GRC processes?

Our AI tools are seamlessly integrated into our GRC platform. By managing your program with Anecdotes and leveraging the AI tools, you can enhance existing processes with real-time insights, automate manual tasks, and benefit from data-driven recommendations tailored to your specific needs.

What makes Anecdotes’ AI different from other GRC tools?

Anecdotes stands out by offering contextually aware AI tools that adapt to your organization’s unique GRC patterns. Unlike static solutions, our AI learns and evolves with your program, providing ongoing, personalized insights and support.

How does the AI learn and adapt to my organization’s specific needs?

Anecdotes’ AI tools continuously learn from your real-time GRC data and adapt to changes in your program. This means the system becomes more accurate and responsive over time to keep up with the evolving needs of your business.

What types of GRC tasks can AI tools help automate?

Anecdotes’ AI tools can enhance a variety of tasks, including policy analysis, audit management and risk assessments. By performing these routine tasks with GRC tools, your GRC team can focus on strategic decision-making and more complex issues.

Is customer data collected and used to train or fine-tune AI models? Can customers opt-out of having their data used for AI training or improvement?

No, Anecdotes' platform does not host, train, or fine-tune AI models with customer data or any other data, our platform’s AI features are powered by Google Vertex AI.

How do you secure data in transit and at rest, especially training data?

Anecdotes does not host or train AI models with customer data or any other data, the HTTPS traffic to and from Google Vertex AI is encrypted and enforced with TLS1.2 and above between all components.

Do you process or store sensitive data in your AI pipelines? and how do you ensure compliance with regulations like GDPR, HIPAA, or CCPA when using AI?

At present, the customer bucket is only storage used by the AI pipline as a source and destination. In order to maintain the completeness, integrity, accuracy, and traceability Anecdotes does not modify any customer data provided as an input within our AI pipelines.
Anecdotes do not use customer data to train AI models, and no data is leaked or exposed externally. Any output generated is stored securely within the customers’ own storage buckets, not in our systems.
Risk of non-compliance with said regulations is mitigated by not sending or using customer data to train the AI model.

Where is the AI processing/data hosting geographically located and do you have a Data Protection Agreement (DPA) in place?

The selected region is GCP US-Central1 and Anecdotes' DPA can be access at https://www.anecdotes.ai/data-processing-exhibit

How do you detect and mitigate bias in your AI features?

We leverage Google’s Vertex AI models for key tasks like vector search, text generation, and embedding creation. While these models benefit from Google's rigorous bias evaluation processes (responsible AI practices across their model lifecycle), we recognize that bias can still manifest depending on specific use cases and data contexts. Here's how we handle it:
1. Task-Specific Bias Evaluation
Our team conducts manual reviews of model outputs during development to identify patterns of bias or poor performance that automated metrics might miss.
2. Mitigation Strategies
We implement automated post-processing to validate and adjust outputs, ensuring they are coherent, accurate, and aligned with intended use cases.
Human-in-the-loop review is integrated into our development cycle to catch and correct any unexpected behaviors or biases.
3. Customer Collaboration and Opt-In Control
Our AI features are offered only to opt-in customers, ensuring they are fully informed and aligned with the deployment.

Is there a human-in-the-loop process for critical decisions?

All prompts and system instructions are human-predefined and human-in-the-loop review is integrated into our development cycle to catch and correct any unexpected behaviors or biases.

How do you validate the accuracy and reliability of your AI feature results?

We actively assess performance using labeled data. Labeled datasets and manual labeling processes help us evaluate outputs for fairness, correctness, and reliability across diverse scenarios. Our team conducts manual reviews of model outputs during development to identify patterns of bias or poor performance that automated metrics might miss.

How do you handle AI hallucinations or incorrect outputs?

We implement automated post-processing to validate and adjust outputs, ensuring they are coherent, accurate, and aligned with intended use cases.
Human-in-the-loop review is integrated into our development cycle to catch and correct any unexpected behaviors or biases.

How are AI features integrated into your product’s workflows, are these optional and can these be viewed, configured, and controlled by the customer?

AI features offered by Anecdotes’ platform are available within the relevant module, customers can opt-in or opt-out from these AI powered features in the settings using on/off toggle.

Is there a fallback if the AI component is unavailable or fails?

AI powered features are opt-in add-ons so in case it fails no suggestions are presented but this does not affect the core platform or the module in which the AI feature was enabled.

What happens to customer data after contract termination?

All AI generated and processed data is stored within the dedicated customer storage, upon customer contact termination customer data is purged permanently.

What kind of monitoring and logging is in place for AI-driven features?

Logging and monitoring includes but not limited to; rejection rate, accuracy drops, and feature usage.

Do you have an AI governance policy or framework in place?

Yes, Anecdotes has an AI Governance and Security Framework in place which aligns with ISO42001, ISO27001 and NIST AI RMF.