Oplane

What Oplane does

Oplane provides an always-on security expert for AI-first engineering teams, helping them see and fix every threat in their architecture in minutes. It addresses the gap in traditional security tooling that wasn't built for the speed and complexity of AI-native systems, including AI-generated code volume, architectural threats missed by static analysis, and the demand for continuous evidence for audits. Oplane offers continuous threat modeling that understands the full architecture, not just code, and integrates seamlessly into existing developer workflows. It connects to repositories with read-only access, understands the entire stack including services, data flows, cloud, IaC, and agent tools, and delivers findings directly to pull requests and IDEs. The platform is built for security teams, ensuring GDPR compliance, EU-based operations, and strict data isolation, never training models on customer code or data. Oplane aims to transform security from a periodic project to a continuous, software-driven process that keeps pace with AI-first development.

Products

• Continuous Threat ModelingAlways-on threat modeling that understands the full architecture, not just the code. It maps the architecture, highlights threats visually, and provides fixes. It replaces stale documents with living threat models that update as code changes.
• PR AnalysisAutomated security review on every pull request, analyzing changed files against the existing threat model, surfacing architectural findings with severity and context, and proposing code-level fixes. It integrates with GitHub and GitLab.
• AI Coding SecuritySecures AI-generated code at the source by running as an MCP inside AI agents like Claude Code, Cursor, and Copilot. It provides threat-model-aware suggestions and automated review within the agent's pipeline to catch architectural risks before code is committed.
• Audit-ready by defaultContinuously collects SOC 2 and ISO evidence, ensuring organizations are always audit-ready without dedicated security headcount. It provides a per-PR audit trail and live posture reports for enterprise buyers and auditors.
• Board reportingProvides real-time evidence of security posture for audit committees and boards, replacing annual snapshots with a live picture of risk.
• ComplianceOffers traceable evidence for regulators covering frameworks like FDA / MDR, PCI DSS, SOC 2, ISO 27001, and DORA, detailing who found what, when, and what actions were taken.

Key capabilities

• Always-on security expert for AI-first engineering teams
• Continuous threat modeling that understands full architecture
• Integrates with GitHub and GitLab for read-only access
• Understands services, data flows, cloud, IaC, and agent tools
• Findings delivered to pull requests and IDEs
• GDPR compliant with EU-based team and hosting
• No training models on customer code or data
• Automated security review on every pull request/merge request
• Architectural checks for AI-generated code within agents (MCP integration)
• Provides specific security requirements and implementation guidance
• Analytics dashboard for security posture, PR resolution rate, requirements completion, team adoption, and threat model coverage
• AI-assisted remediation with clear guidance
• SSO, role-based access control, audit logs
• Self-hosted or hybrid deployment options for regulated workloads

Use cases

• Identifying and fixing architectural threats in AI-native systems
• Scaling security for AI-paced development
• Ensuring continuous compliance for SOC 2, ISO 27001, FDA/MDR, PCI DSS, DORA
• Securing AI-generated code and agent-built features
• Automating security reviews for pull requests and merge requests
• Providing continuous evidence for enterprise buyers and audits
• Governing security across hundreds of repositories consistently
• Monitoring and reporting on organizational security posture in real-time
• Unblocking AI adoption by providing a paper trail for legal and risk teams

AI approach

Oplane uses AI/ML to analyze architectural risks in code, especially for AI-native systems and AI-generated code. It focuses on design-level risks that traditional scanners miss, such as prompt injection, tool misuse, and cross-service trust gaps. The company states it never trains models on customer code or data.

Tech named: ML-based SAST

What it says sets it apart

• Always-on, continuous threat modeling that updates with architecture changes, unlike periodic manual reviews or stale documents
• Focuses on architectural threats that code-level scanners miss (e.g., prompt injection, tool misuse, cross-service trust gaps)
• Built specifically for AI-native systems and AI-generated code, addressing risks introduced by agents and MCP servers
• Integrates directly into developer workflows (PRs, IDEs, AI agents) for in-the-moment security feedback
• Provides actionable, code-level fixes and guidance tailored to the codebase
• Offers continuous, audit-ready evidence for compliance and enterprise buyers, replacing snapshots with live posture reports
• Security expertise encoded as software, not consultants or documentation
• Full data isolation and never trains models on customer code, repos, or threat models

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.