Platform Architecture
A continuously learning cyber defense platform built around identity, trust relationships, attack paths, autonomous reasoning, and recovery-first security operations. Unlike traditional security products that correlate alerts after the fact, Logic Bounce continuously models enterprise reality and acts on that understanding in real time.
Overview
Every capability within the Platform is powered by a shared security graph and autonomous reasoning architecture. Rather than maintaining separate databases and isolated security tools, the platform continuously models enterprise reality through a unified operational understanding.
LAYER 01
Identity • Endpoint • Cloud • SaaS • Network • AI Agents
LAYER 02
Unified Telemetry Fabric
LAYER 03
Continuous Security Graph
LAYER 04
Autonomous Reasoning Engine
LAYER 05
Policy & Trust Engine
LAYER 07
Autonomous Response Orchestration
LAYER 08
Recovery & Resilience Layer
Layer 01
The Unified Telemetry Fabric ingests, normalizes, correlates, and enriches data from every security, identity, cloud, and AI source across the enterprise.
Convert disparate telemetry into a common operational model.
Identify relationships across users, assets, applications and identities.
Reconstruct complete attack timelines from distributed events into a single timeline.
Map human, machine, cloud and AI identities into a common identity model.
Layer 02
The Security Graph serves as the platform's continuously updated model of enterprise reality. It represents identities, resources, permissions, trust relationships, attack paths, and business context.
Continually model identities, assets, permissions, sessions, applications, cloud resources, AI agents, and trust relationships.
Continuously evaluate privilege escalation, lateral movement, credential exposure and trust abuse.
When a compromise occurs, "Who can be reached?", "What systems were exposed?" and "What privileges were obtained?" are calculated instantly.
Trust relationships are continuously recalculated across User → SaaS, User → Cloud, Agent → API, Application → Database.
Layer 03
The Autonomous Reasoning Engine acts as the operational brain of the platform, continuously investigating, correlating, prioritizing, and explaining security events.
The Security Operations Brain. The reasoning engine continuously evaluates threats, exposure, behavior, risk and trust instead of simply processing alerts.
When suspicious activity appears, the platform automatically gathers evidence, builds timelines, identifies root cause, determines blast radius and recommends response.
Creates a narrative which correlates across the dimensions of identity, endpoint, cloud, network, and AI activity.
Generates attack narratives automatically, taking into account initial access, persistence, privilege escalation, lateral movement, and objectives.
Layer 04
Human-governed autonomy ensures that every automated decision remains aligned with business requirements, risk tolerance, governance policies, and trust models.
The platform never operates without governance. Enable policies that define allowed actions, approval requirements, risk thresholds and business constraints.
The platform continuously evaluates identity, device, session, agent and application trust.
A range of automations are available including Auto Investigate, Auto Enrich, Auto Contain, Notify Analyst, Require Approval, and Escalate to Leadership — triggered depending on the risk level of the case.
Layer 05
Machine-speed response actions allow the platform to contain threats in seconds rather than hours.
The platform can take actions in the event of an incident including endpoint isolation, session termination, account disablement, privilege reduction, token revocation, SaaS containment, and AI agent suspension.
The platform continuously detects, investigates, decides, responds, validates and learns.
Layer 06
Recovery-first architecture ensures rapid restoration of trusted operational states after security incidents.
Traditional security asks "How do we stop attacks?" but a recovery-first architecture asks "How quickly can we restore trust?"
The platform recovers identities, workloads, cloud resources, endpoints and AI systems to a known-good state.
The platform automatically validates integrity, restores configurations, rebuilds trust and confirms operational readiness.
AI Native Security
Protect AI agents, autonomous workflows, MCP servers, machine identities, and LLM-powered business systems.
Protects AI agents, LLM applications, MCP servers, autonomous workflows and machine identities by instituting agent identity governance, prompt injection defense, runtime monitoring, tool invocation validation and agent trust enforcement.
Platform Benefits
Security teams are facing adversaries that increasingly leverage AI to search for vulnerabilities 24/7 and launch attacks at scale with nearly limitless variation. An autonomous SOC supplements security teams by providing tireless, around-the-clock alert triage, investigation, and response, leading to:
Shared Operational Understanding
Unified Investigations
Consistent Governance
Machine-speed operations
Enhanced Security Posture
Using AI analytics to make connections between disparate intelligence signals.
Reducing noise through automated alert triaging. Escalating only real critical alerts by clearing away false positives.
Using AI to identify and respond to emerging threats while freeing up human analysts for threat hunting.
Enhanced Operations
Automating repetitive, time-consuming security operations processes and using AI to generate documentation, transform data, and quickly build workflows.
Incidents are resolved faster through the use of intelligent prioritization, AI-accelerated investigation and response, and contextual case enrichment.
The ability to translate natural language commands into technical actions allows junior analysts to operate at a higher level.
Enhanced Productivity
Automating repetitive tasks to focus on more rewarding work.
Intelligently assigning case workloads by skill, experience and availability.
By increasing efficiency, reducing operational overhead, and minimizing security breaches.
Move beyond fragmented security tooling and adopt a continuously learning cyber defense platform.