AI-Native Threat Detection — Embedded Intelligence Layer

Embedded Intelligence Layer / 02

Scoped engineering

Detect behavior that static rules and isolated alerts cannot explain.

Behavioral analytics, anomaly detection and AI-assisted investigation embedded into Bellot defensive services—not sold as a disconnected AI project.

01
Data

Authorized sources and verifiable quality

02
Intelligence

Models, context and Harpia correlation

03
Control

Policy, oversight and traceability

Strategic problem

Technology begins with the risk that must be understood.

Relevant threats often appear as weak deviations distributed across identities, devices, networks and time. Static thresholds miss context while ungoverned models create new noise.

Anomaly is not proof of attack. Models require representative data, monitoring and human validation before consequential use.

The Bellot difference

Intelligence designed into defense—not added afterward.

AI is embedded in the defensive workflow and measured against operational context. It augments analysts instead of becoming a stand-alone promise.

Operating model

From the environment to continuous improvement.

01Observe
02Baseline
03Detect
04Correlate
05Validate
06Learn

Engagement outputs

The engagement ends with explicit decisions, artifacts and responsibilities.

The final composition depends on the agreed scope. These are the core artifacts guiding the engagement.

01

Detection hypotheses and data-readiness assessment

02

Evaluated rules or model package with documented baselines

03

Monitoring, analyst-feedback and governance plan

01

Capabilities

  • Behavioral and anomaly detection
  • AI-assisted event correlation
  • Contextual alert prioritization
  • AI-assisted threat hunting
  • Suspicious-behavior detection
  • Automated triage and investigation support
02

Applications

  • Credential compromise
  • Distributed attack sequences
  • Abnormal device behavior
  • Insider-risk investigation
  • Threat-intelligence enrichment
03

Architecture

  • Normalized, authorized evidence
  • Behavior and entity context
  • Harpia models and correlation
  • Analyst feedback, monitoring and governance
04

Operational outcomes

  • Earlier investigation signals
  • Less repetitive triage
  • Explainable prioritization
  • Improved detection feedback loops

Harpia / Proprietary Intelligence Engine

The proprietary intelligence engine connecting Bellot architecture.

Harpia is embedded across services: it relates signals, supports behavioral detection, prioritizes investigations and recommends governed actions. It is not sold as a separate AI project.

Meet Harpia
Harpia intelligence and correlation core

Next step

Start with the operation, the signals and the expected impact.

Build a defensive capability that can evolve.

Talk to Bellot