incident_management · saas · workflow
Doppel's AI agent cuts security operations workload by 30% in 30 days using OpenAI o1
Cybersecurity teams are overwhelmed by alert volumes; nuanced decisions about phishing takedowns require detailed manual analysis that is difficult to scale when ingesting over 10 million websites, social media accounts, and mobile apps daily.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Daily data ingestion
Every day, Doppel ingests more than 10 million websites, social media accounts, and mobile apps to identify phishing attacks worldwide.
Outcome
Doppel's AI agent automated 30% of security operations workload in under 30 days, exceeded human-level benchmarks with a lower false-positive rate and more genuine threats uncovered, and delivered faster response times to customers.
What failed first
Traditional machine learning filtered out obvious false positives but could not make the nuanced judgment calls required for takedown decisions, which require interpreting unstructured data such as screenshots, time-series activity, and customer-specific policies.
Results
Time saved30 days
Volume30%
Grounding & classification
Source type: technical build writeup
25 fields verified against source quotes, 1 dropped as unverifiable.
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