AI-Assisted Discovery Architecture
AI assists research, organization, classification, and analysis — helping analysts work faster without making unsupported claims about autonomous security capabilities.
From search intent to intelligence records
A staged pipeline where each step adds structure, evidence, and confidence to the results.
Search Intent
Define what to discover.
Discovery Providers
Query configurable providers.
Candidate Domains
Extract and deduplicate.
Validation
Validate candidates.
Enrichment
Add evidence and metadata.
Intelligence Records
Produce structured records.
What AI-assisted discovery does
The discovery engine coordinates providers, normalization, and enrichment into one reproducible workflow.
Intelligent Search Queries
Generate targeted queries to surface relevant public assets.
Multiple Discovery Providers
Combine configurable search and discovery providers.
Location-Aware Discovery
Incorporate location context into discovery where relevant.
Result Normalization
Normalize heterogeneous results into a consistent shape.
Domain Extraction
Extract candidate domains from discovery results.
Deduplication
Remove duplicate candidates across providers.
Classification
Classify candidates into structured categories.
Evidence Enrichment
Attach supporting evidence and public metadata.
Confidence Scoring
Score findings to support review and prioritization.
AI is used to assist research, organization, classification, and analysis. It supports human review rather than making autonomous decisions or unsupported claims about security outcomes.
See AI discovery at work
See how AI-assisted discovery turns public signals into structured intelligence for your organization.