Active Remediation Platform
for the Agentic Enterprise
Detect, diagnose, remediate, and verify issues across code, AI agents, cloud, and production before they impact the business.
Protect what humans and AI agents build, change, deploy, and run.
Detection Is Not Enough
Security, DevOps, and platform teams are overwhelmed by findings, alerts, failed deployments, cloud misconfigurations, vulnerable code, and unsafe AI agent actions. The hard part is not finding issues. The hard part is understanding what matters, fixing it safely, and proving the fix worked.
Too many findings, not enough fixes
Security tools generate thousands of alerts. Teams triage endlessly but remediate rarely. Vulnerability backlogs grow while actual risk stays unresolved.
AI agents can make unsafe changes
Coding agents, deployment bots, and AI-assisted pipelines can introduce vulnerabilities, misconfigurations, and policy violations at machine speed.
Code-to-cloud context is fragmented
Vulnerability scanners see code. CSPM tools see infrastructure. Neither knows how they connect. Without full context, prioritization is guesswork.
Remediation is slow, manual, and unverified
When fixes do happen, they're driven by tickets, spreadsheets, and manual handoffs. No one confirms the fix actually worked or that it didn't break something else.
The Active Remediation Platform
A context-aware remediation system that combines diagnostics, agents, actions, and verification.
Context Engine
Context-AwareContinuously builds software, delivery, cloud, and runtime context so every remediation decision understands impact, dependencies, ownership, and business risk.
Pre-Remediation Diagnostics
Root-Cause AnalysisDiagnoses root cause, blast radius, policy impact, deployment impact, and safe remediation paths before any action is taken.
Remediation Agents & Actions
Agentic ExecutionSpecialized AI agents generate fixes, create pull requests, repair configurations, trigger workflows, execute compensating controls, and guide human operators.
Verification
Verified OutcomesValidates that the remediation resolved the issue, did not introduce new risk, and preserved application and production health.
From Code to Cloud to Production
Detect, diagnose, remediate, and verify at every stage — with AI agents and human approval checkpoints built in.
Code & Agents
Vulnerable dependencies, secrets in code, unsafe AI agent commits, policy violations
Dependency chain analysis, secret entropy scoring, agent action policy audit
Auto-PR for patches, secret rotation triggers, agent action rollback
Re-scan post-merge, SAST pass, policy compliance confirmed
Active Defense & Remediation
Across the Software Lifecycle
Code & Agent Active Remediation
Secure human-written and AI-generated code, coding agents, repositories, dependencies, secrets, and pull requests before merge.
Code-to-Cloud Active Remediation
Protect software delivery from risky human and AI agent actions across CI/CD, GitOps, artifacts, infrastructure, and cloud changes.
Runtime Active Remediation
Continuously defend applications, containers, Kubernetes, and cloud environments from drift, misconfigurations, vulnerable workloads, and runtime risk.
Active Diagnostics & Remediation
Diagnose and resolve deployment failures, Kubernetes issues, delivery problems, and operational incidents with context-aware AI.
Autonomous Where Safe.
Human-Guided Where Needed.
Remediation Labs supports multiple levels of control: recommendations, pull requests, approval-based execution, automated compensating controls, and verified autonomous remediation.
Every action is governed by policy. Every autonomous execution requires that context, blast radius, and risk are fully understood. Humans stay in control of what matters most.
Surface prioritized, context-aware remediation options to the right owner at the right time.
AI agents draft the patch, config change, or runbook — ready for human review.
Automatically open a pull request with the fix applied, linked to the finding and context.
Route high-impact changes through policy-defined approval workflows before execution.
Apply the fix directly — code merge, config update, workflow trigger, or compensating control.
Confirm the issue is resolved, no new risk introduced, and application health preserved.
Feed outcomes back into the context engine — improving prioritization, diagnosis, and future remediation quality.
Why Remediation Labs
Context-Aware Remediation
Every fix decision is informed by the full software, delivery, cloud, and runtime context — not just the raw finding.
Root-Cause Diagnostics Before Action
We diagnose blast radius, dependencies, policy impact, and safe fix paths before any remediation runs.
Agentic Workflows with Policy Guardrails
AI agents operate within defined policy boundaries — no autonomous action without context, scope, and approval where required.
Human-in-the-Loop Control
Critical and high-impact actions go through human approval flows. Operators stay in control of what matters.
Code-to-Cloud-to-Runtime Coverage
One platform that spans the entire lifecycle — not a point tool that sees one slice of the risk surface.
Verification-First Remediation
No remediation is complete until it's verified. Every fix is confirmed to have resolved the issue without introducing new risk.
| Capability | Traditional AppSec | CSPM Tools | Observability | Remediation Labs |
|---|---|---|---|---|
| Finds issues | ✓ | ✓ | ✓ | ✓ |
| Root-cause diagnosis | — | — | Partial | ✓ |
| AI-assisted remediation | — | — | — | ✓ |
| Human approval workflows | — | Partial | — | ✓ |
| Code-to-cloud context | — | — | — | ✓ |
| Verified fix confirmation | — | — | — | ✓ |
Stop Managing Findings.
Start Remediating.
Turn alerts, risks, and incidents into verified fixes across code, cloud, and production.
Trusted by enterprise security and platform teams