Context-Aware Decisions
Every remediation decision is grounded in software topology, cloud state, runtime context, policy constraints, ownership, and business risk.
Remediation Labs · Company
Building the Future of
Active Remediation
Remediation Labs is creating the platform that helps organizations safely diagnose, remediate, and verify issues across software, cloud, AI agents, and production systems.
As AI agents gain the ability to write code, change infrastructure, and operate systems, organizations need a trusted control layer that ensures those actions remain safe, compliant, and verifiable.
Our Origin
Why We Started Remediation Labs
The software industry solved detection.
Security toolsidentify vulnerabilities
Observability platformsidentify incidents
Cloud platformsidentify misconfigurations
But organizations still struggle to answer the most important question:
How do we safely fix problems at scale?
As software delivery becomes increasingly autonomous and AI agents gain the ability to make production-impacting changes, remediation becomes the next major challenge facing engineering and security organisations.
The tools that exist today were built to find problems. They were not built to fix them — not at the speed, scale, and complexity that modern software systems demand.
Remediation requires context: understanding what the software does, who owns it, what it depends on, and what a safe fix looks like in the specific environment where the risk exists. Remediation requires diagnosis. It requires policy governance. It requires verification.
Remediation Labs was created to solve that challenge.
We are building the platform that moves enterprises from finding problems to verifying that those problems are fixed.
Our Mission
Our Mission
Move the industry from
findings to verified fixes.
Diagnose before action
Never execute a remediation without first understanding root cause and blast radius.
Context before automation
Automation without context creates new risk. Every action must be informed by the full software and infrastructure picture.
Verification before trust
Every fix must prove it worked before the finding is closed. Unverified remediation is incomplete remediation.
Human governance where needed
High-impact, high-risk, or policy-sensitive changes require human approval. Organisations must remain in control.
Autonomous remediation where safe
When context is clear, blast radius is understood, and policy permits, automation should operate at full speed.
The Vision
The Active Remediation Vision
The world is moving from detection-and-wait to continuous, verified remediation — driven by the pace of AI.
Traditional World
Detect
Alert
Ticket
Wait
Findings accumulate in a backlog. Tickets sit unresolved. Risk compounds. The organisation detects problems faster than it can fix them.
Agentic World
Detect
Diagnose
Remediate
Verify
Every issue is diagnosed, remediated, and verified — automatically where safe, with human approval where required. Risk resolves as fast as it is detected.
Organizations are entering an era where AI agents operate across the full software lifecycle:
AI agents write software
AI agents modify infrastructure
AI agents operate systems
AI agents participate in production
Active Remediation Requirement
Active Remediation is required to govern and validate those actions — ensuring that everything AI agents build, change, and operate remains safe, policy-compliant, and verifiable.
What Makes Us Different
What Makes Remediation Labs Different
Six design decisions that separate active remediation from detection-only security tools.
Diagnostics First
Understand root cause and blast radius before making any change. Diagnosis is not optional — it is the foundation of safe remediation.
Agentic Remediation
Specialized AI agents generate and coordinate remediation actions — one per domain, each trained for its surface area.
Human-in-the-Loop Governance
Humans remain in control of high-impact decisions. Policy-defined approval gates ensure that autonomous action never operates beyond its mandate.
Code-to-Cloud-to-Production Coverage
One platform spanning code, supply chain, delivery, cloud infrastructure, Kubernetes, and live production. No gaps, no context switching.
Verification Built In
Every remediation must prove it worked — security posture restored, no regressions introduced, compliance confirmed, and audit evidence captured.
The Future
The Future of Software Operations
Humans and AI Agents Working Together
Future enterprises will operate with humans and AI agents in a continuous collaboration — each contributing where they are most effective.
How future operations work
HumanDefine objectives
AI AgentPerform analysis & detection
AI AgentGenerate fixes & remediation
HumanApprove where required
SystemVerify outcomes
Remediation Labs as the control layer
Remediation Labs Control Layer
Connects
Humans
AI Agents
Software Delivery
Cloud
Runtime
Delivering
Contextual Detection
AI Remediation Agents
Human Approval Flows
Verified Outcomes
Policy Governance
Safe Execution
Our Principles
Our Principles
The beliefs that guide every platform decision and product choice.
Context Matters
Never remediate without understanding dependencies and impact. A fix applied without context can be more damaging than the original issue.
Diagnose Before Acting
The fastest fix is not always the safest fix. Diagnosis reveals root cause, blast radius, and the path that minimizes risk.
Trust Through Verification
Every change should be validated. Unverified remediation creates a false sense of security and can hide regression.
Responsible Autonomy
Automation should increase safety, not reduce it. AI agents must operate within policy boundaries, with clear scope and human override.
Human Governance
Organisations must remain in control. High-impact changes require human visibility, approval, and accountability.
Enterprise Ready
Built for scale, compliance, auditability, and operational reliability. Security and platform teams require systems that can be trusted at enterprise scale.
Who We Serve
Who We Serve
Built for engineering and security teams operating at enterprise scale in regulated, high-velocity, and AI-driven environments.
Security Teams
AppSec, cloud security, and vulnerability management teams that need to move from findings to fixes — not just reports.
AppSecCloud SecurityVulnerability Management
DevOps Teams
Teams responsible for CI/CD pipelines, delivery automation, and deployment reliability who need context-aware diagnostics.
CI/CDDeploymentPipeline Security
Platform Engineering
Platform teams building internal developer infrastructure who need automated, policy-governed remediation across the stack.
Developer PlatformsIDPGovernance
Cloud Operations
Cloud and infrastructure teams managing CSPM, IaC drift, misconfiguration, and Kubernetes security at scale.
CSPMIaCKubernetesMulti-Cloud
Site Reliability Engineering
SRE teams who need rapid incident diagnosis, runtime risk detection, and verified remediation without production disruption.
Incident ResponseRuntimeReliability
Enterprise Architecture
Architecture and strategy teams designing platforms for a world where AI agents operate alongside human engineers.
AI GovernanceEnterprise SecurityStrategy
Join Us in Building the Future
Join Us in Building the
Future of Active Remediation
The next generation of software systems will be built and operated by both humans and AI agents.
Remediation Labs is building the platform that helps organisations trust those systems.
Trusted by enterprise security and platform teams
SOC 2 Type II
GDPR Compliant
Enterprise SLA
On-Prem & Cloud
SSO / SAML