Bugcrowd has officially launched Bugcrowd AI Analytics, a new reporting capability that makes it dramatically easier to understand and act on security data. Now available to organization owners in the Bugcrowd Platform, AI Analytics lets users ask plain-language questions for instant, accurate insights into program performance, vulnerability trends, and organizational risk. 

As security data grows in volume and complexity, AI Analytics imbeds clarity and speed directly into the Platform.

A smarter way to work with security data

Security teams deal with thousands of data points spanning vulnerabilities, targets, rewards, researcher activity, asset categories, and program performance metrics. While each report contains valuable information, the broader meaning of security results is often difficult to uncover.

Leaders face questions that are simple to ask but historically difficult to answer:

  • What is our most critical risk right now?
  • Are we improving compared to last quarter?
  • Why are medium-severity findings increasing?
  • Which programs or assets are driving the most exposure?
  • What patterns emerging across our organization require immediate action?

Traditionally, answering these questions required pulling dashboards, exporting raw data, and stitching together insights manually. The result was slow reporting, limited visibility, and a reactive rather than predictive understanding of risk.

A new approach: Conversational, context-aware analytics

Bugcrowd AI Analytics changes how organizations interact with their security data. Instead of navigating charts or predefined dashboards, users can simply ask questions in natural language and receive immediate answers.

AI Analytics lives inside the Bugcrowd Platform and uses generative AI to interpret queries, analyze program-wide data, and deliver the following:

  • Real-time summaries of organizational risk
  • Researcher and program performance
  • Narrative summaries
  • Contextual insights that move beyond raw numbers

In other words, AI Analytics allows leaders to shift from manually assembling reports to having a true intelligence layer that gives data meaning.

For example, a user can ask focused questions based on their needs. Consider the following: 

  • Target:
    Which target generated the most critical P1 submissions last quarter?
  • Timeframe comparison:
    What is our average triage time compared to the previous quarter?
  • Severity:
    What is the total number of valid submissions we’ve received in the last 90 days, broken down by severity?
  • Reward:
    What is the average reward amount per submission, based on severity?

AI Analytics evaluates an organization’s data, identifies relevant relationships or patterns, and responds with a clear, structured analysis.

How AI Analytics works

AI Analytics combines structured program data, generative AI, and a conversational interface to deliver a smart reporting layer inside the Bugcrowd Platform.

Core capabilities

Natural-language exploration of data
Ask questions in plain English and receive immediate, accurate answers.

Fast identification of systemic risks
Surface organizational patterns that would otherwise be buried inside dashboards or reports.

Instant summaries for stakeholders
Generate explanations and narratives suitable for executives, audits, and board updates.

Organization-level trend insights
Understand performance across all programs, engagements, and time periods.

AI-assisted reporting
Export predefined dashboards as PDFs and extract chart data as CSVs for further analysis.

Together, these capabilities allow users to move from analysis to action in seconds rather than hours, reducing the reporting burden and strengthening decision-making.

What you can ask AI Analytics

Here are just a few examples that illustrate how customers can use the capability in daily workflows:

Identify top risks
“What is our most critical risk this quarter?”

Review researcher performance
“Which researchers submitted the highest-impact findings this month?”

Benchmark asset exposure
“Which targets have produced the most P1 or P2 findings in the past 90 days?”

Prepare leadership reporting
“Summarize our security program performance for reporting.”

Every response is generated from an organization’s actual Bugcrowd program data, ensuring relevance, accuracy, and role-based visibility.

Built for accuracy, privacy, and trust

AI Analytics is built to uphold Bugcrowd’s strict security, privacy, and data governance standards:

  • All interactions are scoped by role-based access
  • No customer data is used to train underlying LLM models
  • Structured datasets reduce the chance of hallucinations
  • Queries and responses remain within Bugcrowd’s secure cloud environment

This ensures that organizations can fully leverage the advantages of generative AI while maintaining complete control of their data.

The combined power of AI Analytics and AI Triage Assistant

While AI Triage Assistant focuses on deep insights related to specific vulnerabilities, AI Analytics addresses the bigger picture: organization-wide posture and systemic risk.

Together, they provide tactical insight into the impact of individual findings and strategic visibility into broader trends and risk trajectories. This dual approach gives security teams a full-spectrum intelligence layer that accelerates both day-to-day triage and long-term decision-making.