◆ Gentoo Logic · Modeling Warehouse

Architecture comparison

Abnormal Security vs SentinelOne

Abnormal Security runs closer to the foundational model (Native (own / self-hosted weights)) than SentinelOne (Native (own / self-hosted weights)). Shared foundation: proprietary / self-built models (highlighted).

Abnormal Security

Cybersecurity

Proximity
Native (own / self-hosted weights)
Models
proprietary / self-built models
Cloud · datastore
AWSPostgreSQLAmazon S3 (data lake/object storage)Elasticsearch/OpenSearch (log/search, inferred)
Compliance
SOC 2 (inferred from enterprise email security norm)ISO 27001 (inferred)GDPR-aligned data processing (inferred)
Architecture

Abnormal runs a cloud-native, API-first behavioral AI platform that integrates with cloud email and collaboration suites (e.g., Microsoft 365, Google Workspace) outside the mail flow, ingesting user, email, and identity telemetry into proprietary behavioral models and a data lake to drive detection, response, and human-risk scoring.[1][5][7][8][9] Its core is a proprietary behavioral foundation model and related ML pipelines hosted in its own cloud environment, exposed through its SaaS console and APIs rather than via public/open-source model distribution.[7][9]

SentinelOne

Cybersecurity

Proximity
Native (own / self-hosted weights)
Models
proprietary / self-built modelsAnthropic · ClaudeOpenAI · GPT
Cloud · datastore
AWSownSnowflake
Compliance
SOC 2FedRAMP
Architecture

Purple AI combines SentinelOne’s own Ultraviolet models with Anthropic Claude + OpenAI GPT over its Singularity data lake; exposes a Purple MCP server for agentic SOC investigation.

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