AI Incident Response: Rapid Containment. Expert Resolution.
When your AI system fails—producing harmful outputs at scale, experiencing a jailbreak, or suffering an adversarial attack—we mobilize within 24 hours. Senior experts. Independent assessment. No vendor conflicts.
Active incident? Email emergency@qilabs.ai for immediate response.
What Counts as an AI Incident?
If any of these scenarios match your situation, you need AI incident response now.
Model Failure at Scale
Your AI system begins producing harmful, unsafe, or incorrect outputs affecting customers, users, or stakeholders at scale. When a model fails, containment is critical.
Adversarial Attack
Someone deliberately crafted inputs to manipulate or exploit your AI system. Prompt injection attacks, jailbreaks, or adversarial examples in production systems require rapid forensics.
AI-Generated Deepfake
Your AI system generated synthetic media (images, audio, video) that causes reputational damage, violates policies, or facilitates fraud. Tracing the source and scope is urgent.
Training Data Poisoning
You discover malicious or corrupted data was used to train your model. Data poisoning incidents can introduce subtle biases, vulnerabilities, or harmful behavior patterns.
LLM Jailbreak in Production
An LLM deployed in customer-facing systems or critical workflows gets jailbroken, bypassing safety guidelines and exposing private data or enabling harmful use cases.
Autonomous Agent Malfunction
An autonomous AI agent takes unintended actions—executing trades, deleting data, interacting with systems inappropriately. Understanding what happened and preventing recurrence is urgent.
Our AI Incident Response Process
Fast. Thorough. Repeatable. Here's how we work.
Emergency Intake & Team Assignment
We take your initial report, assess urgency and scope, assign a dedicated senior expert team, and begin gathering critical information: system architecture, incident timeline, affected systems, and data classification.
Technical Forensics & Scope Assessment
Our team conducts deep technical investigation: examining logs, model behavior, training data lineage, access patterns, and system architecture. We identify root causes, affected users/data, and containment options.
Preliminary Findings & Containment Recommendations
You receive a preliminary assessment with findings so far, confirmed incident scope, immediate containment recommendations, and regulatory notification obligations. You get transparency to act fast.
Full Assessment Report Delivered
Complete incident forensics report, including root cause analysis, impact assessment, regulatory notification brief, remediation priority matrix, executive summary, and detailed technical findings suitable for regulators and legal teams.
Remediation Support & Resilience Planning
We help implement remediations, support regulatory submissions, design controls to prevent recurrence, and help you build AI resilience for the future.
What You Get From AI Incident Response
Incident Forensics Report
Technical, detailed, audit-ready documentation of what happened: root cause analysis, system behavior timeline, contributing factors, and forensic findings. Suitable for regulators, legal, and technical teams.
Impact Assessment
Clear identification of affected systems, data, users, and business impact. Scope is quantified: how many users, what data, what duration, what downstream effects. No surprises later.
Regulatory Notification Brief
Jurisdiction-mapped obligations and guidance: GDPR breach notification requirements, sector-specific rules, timing obligations, and content requirements. We map what you must do and when.
Remediation Priority Matrix
Ranked, prioritized remediation actions with effort/impact assessment. Not all fixes are equal. We help you focus on high-impact, feasible remediations first.
Executive Summary
Board-ready, non-technical summary: what happened, why, impact, and next steps. Written for decision-makers who aren't AI experts.
Implementation Support
Available for follow-up questions during remediation, regulatory submission support, and control design to prevent recurrence. We don't hand off and disappear.
Why Independence Matters in AI Incident Response
When your AI vendor assesses their own incident, they have a built-in conflict of interest: minimizing scope and severity protects their reputation and avoids liability. When we assess it, we have no such incentive.
We tell you exactly what happened. Not what's convenient. Not what's legal-safe. What actually happened. This independence matters because:
- Scope accuracy: We won't minimize the number of affected users or duration of the incident.
- Root cause honesty: We identify systemic issues, not just surface triggers.
- Regulatory compliance: We map actual obligations, not convenient interpretations.
- Preventive value: We identify what needs to change to prevent recurrence, even if it's uncomfortable.
- Liability protection: Honest, third-party assessment protects you better than minimized vendor assessment.
Case Study: European Healthcare AI System
The Situation: A European healthcare organization deployed an AI diagnostic recommendation system. The system began generating erroneous clinical recommendations due to data drift in production. The internal team assessed the problem as isolated to recent predictions.
The Issue: Initial internal scope: ~50 affected cases. Potential regulatory impact: minor incident notification.
Our Finding: Through comprehensive forensics and model behavior analysis, we identified that the data drift had affected the model for 6+ months. Actual affected cases: ~150, including older cases not in initial scope. The problem was more systemic than initially recognized.
The Impact: By identifying the true scope early, the organization:
- Made accurate regulatory disclosures (avoiding incomplete notification, which carries higher penalties)
- Implemented proper model retraining and validation
- Built data drift detection systems to prevent recurrence
- Avoided estimated €8M in potential regulatory fines from understated disclosure
This organization benefited from independent assessment that would have been impossible from their vendor, who had incentives to minimize scope.
Frequently Asked Questions
How fast can you start an AI incident response?
We guarantee 24-hour initial mobilization. Email emergency@qilabs.ai with incident details and we assign a senior expert team immediately. For active, critical incidents, we can often begin preliminary forensics within 2-4 hours of first contact.
What access do you need to conduct an AI incident investigation?
We typically need: system logs and event data; model artifacts (weights, architecture, training data lineage); infrastructure and access logs; deployment configuration; and stakeholder interviews. We work within your security and compliance constraints and under NDA. We don't need production system access—we work with data exports and read-only access.
Can you work with our legal team under attorney-client privilege?
Yes. Our work can be engaged under attorney direction and attorney-client privilege to protect findings from discovery. Discuss privilege structure with your legal team and we'll coordinate. This is common in incident response.
Don't Wait. Every Hour Matters.
If you're facing an AI incident right now, contact us immediately.
emergency@qilabs.aiAverage response time: less than 24 hours