Consistent, Defensible Data Mining Review — with Zero Overhead

Auto Review is Agentic AI for data mining, fully replacing the manual component of first-level document review in cyber incident response matters. Instead of simply enabling contract reviewers to work faster, Auto Review performs the first-level review itself, allowing IR teams to move directly to QC without the hassle of maintaining a full roster of contract reviewers.

For cyber incident response cases, Agentic AI is faster and more cost-effective than GenAI.

GenAI uses large language models (LLMs) to assist human reviewers. While this can speed up review somewhat, GenAI still requires humans to read and validate every document due to limitations like hallucinations, difficulty with long documents, and inconsistent handling of structured data.

Agentic AI, as used in Canopy’s Auto Review, doesn't just augment the first-level review. It fully executes first-level review, automatically mapping entities and values (including across spreadsheets and databases) and generating confidence level reporting that directs QC. It does all of this directly within the Canopy Data Breach Response software — no hiring, training, management, or secure workspaces required.

GenAI tools typically use generic GPT models to augment human reviewers, meaning every document still requires manual oversight. Auto Review goes further by combining multiple AI technologies with Canopy’s proprietary AI to automate first-level review entirely, eliminating the need for humans to review every document before QC.

Yes. Auto Review is designed to replace the human component of first-level review, not just accelerate it. A single project manager can skip directly to QC, significantly reducing review timelines, labor costs, and the administrative hassle of maintaining a full-fledged review team.

Manual document review is inherently error-prone, especially at scale. Auto Review eliminates common issues like keystroke errors and inconsistent judgment, while also overcoming GenAI limitations such as hallucinations, fragmented entities, and difficulty handling long or complex documents. Further, Auto Review doesn't suffer from fatigue, leading to more accurate decision-making and faster review timelines. And Auto Review's built-in confidence level reporting provides transparent, clear guidance for subsequent QC review.

Auto Review can review most documents that are supported by Canopy. This includes PDFs, images, and text-based files as well as spreadsheets and other tabular data, which are often difficult and time-consuming for human reviewers or GenAI tools to interpret correctly. After Auto Review is run, all supported documents are marked as reviewed, given a confidence level rating, and ready to be batched as needed for QC.

By replacing what is often the largest labor expense in data mining projects (human-executed first-level review), Auto Review enables data breach response teams to complete review in days instead of weeks. Auto Review further eliminates the burden & cost of hiring contract reviewers, managing their availability, provisioning access, or maintaining secure office space and equipment.

Auto Review enables managed review providers to quickly and confidently handle cyber incident response projects, linking high volumes of personal data to individuals without the inefficiencies and risks of manual or GenAI-assisted review workflows.

Auto Review also eliminates the need for digital forensics & incident response (DFIR) organizations to sub out their document review, enabling them to offer end-to-end data mining services in-house & grow a new line of business with zero overhead. 

Auto Review also offers downstream benefits: legal counsel receive critical insights to make data breach determinations faster; cyber insurance providers receive predictable bids on cyber claims servicing costs; and targeted organizations can trust that their already-compromised data is securely handled in-region.