Auto Review: Agentic AI for Incident Response Data Mining
Canopy's Auto Review automates the first-level review phase, alleviating the administrative burden of managing a roster of reviewers.
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Skip Straight to QC with Auto Review
First-level review is often the most time-consuming and costly phase of data mining. By automating it, Canopy's Auto Review fundamentally changes how organizations approach these projects.
Instead of managing hiring, training, scheduling, and a workplace for each discrete project, incident response providers can now initiate first-level review with just a few clicks. That means you get:
Reduced Operational Bloat
By removing the bulk of manual labor from the review process, Auto Review eliminates the burden & cost of hiring contract reviewers, managing their availability, provisioning access, or maintaining secure office space and equipment.
Superior Accuracy & Confidence
Agentic AI avoids keystroke and judgment errors while overcoming limitations found in generic AI tools. Auto Review’s confidence level reporting guides the QC process so review managers can prioritize their time and effort.
Faster Project Resolution
Auto Review Is Faster, Smarter, and More Cost-Effective Than GenAI
Auto Review doesn’t just speed up your human reviewers — it is your first-level review team.
Instead of limiting Auto Review to a single technology or third-party tool like GPT-powered competitors, we have integrated a host of approaches and artificial intelligence technologies with our proprietary algorithms to deliver your first-level review with superior speed and accuracy. This includes automatic mapping of all spreadsheets and other tabular data. Then, Canopy’s built-in confidence level reporting directs your QC focus.
GenAI vs Agentic AI for Data Breach Response
Traditionally, data mining review has involved dozens of reviewers grinding through thousands or even millions of documents to link personal data with people. This fully-manual first-level review is slow and costly, with major administrative needs involved with managing a roster of contract reviewers and a secure working environment for every project.
Then came GenAI, primarily leveraging large language models (LLMs). While some software companies currently market this as game-changing for review, many GenAI approaches simply enlist generic GPT models. These require high levels of technical expertise to reliably detect PII and link it to entity records. Even then, users must navigate the notorious LLM hallucinations and other inadequacies of GenAI on its own, including the inability to handle value and entity fragments or manage lengthy documents.
In short, while GenAI can speed up first-level review, it can’t replace it. You still need human oversight of every single document prior to QC review, which means you still need to put in the administrative work associated with managing a team of reviewers.
Canopy goes further than GenAI. Auto Review is truly Agentic AI for incident response data mining. With Auto Review, incident response providers can now initiate first-level review with just a few clicks — accelerating project timelines from weeks to days, alleviating people and workspace management needs, and freeing up valuable resources for higher-level decision-making.
Frequently Asked Questions
What is Canopy's Auto Review?
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.
Which is better for data mining review: Agentic AI or GenAI?
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.
How is Auto Review different from GenAI data breach response tools?
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.
Does Auto Review really allow me to offer data mining review services without a full team of first-level reviewers?
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.
How does Auto Review improve accuracy and reduce risk?
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.
What types of data can Auto Review handle?
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.
How does Auto Review impact project timelines and costs?
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.
Who benefits from Auto Review?
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.
Auto Review's enhanced speed and cost-savings also offer downstream benefits: legal counsel receive critical insights to make data breach determinations faster, and cyber insurance providers save on cyber claims servicing costs.
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