How Kavak built proactive incident detection with Autonoma AI

Introduction

Kavak’s Solutions Center is a specialized area responsible for analyzing and managing technological incidents that affect the company’s critical processes. Its goal is to guarantee operational continuity and resolve incidents efficiently, reducing the impact on both users and customers. The department follows ITIL-based practices for managing the incident lifecycle and coordinating with specialized support teams. Real-time monitoring with Datadog allows proactive detection of system failures, primarily focused on APIs. However, Kavak needed to expand visibility into issues that directly impacted the customer experience on www.kavak.com and other internal applications critical to customer-facing operations.

To meet this goal, Kavak adopted Autonoma AI’s intelligent agents to run simulated user journeys across all critical operational flows. These simulations allow the team to detect errors the moment they appear, before they affect real users, and reduce friction in how inventory and content are presented to customers. The types of issues detected range from functional to design-related errors. For Kavak, it’s essential that every flow not only functions correctly but also provides a flawless user experience, free from visual inconsistencies and displaying accurate vehicle information, which builds trust in the buying process.

How Autonoma Integrates into Kavak’s Workflow

Autonoma AI is configured to continuously test production environments, automatically creating Jira tickets whenever an anomaly is detected. These tickets are routed to the Solutions Center for review and, if necessary, escalation to the product or technology teams.

Previous Architecture (Before Autonoma)

Before Autonoma, Kavak relied on a SWAT team responsible for:

• Monitoring social media to identify user reports regarding issues on kavak.com (e.g., missing or inconsistent vehicle data, wrong images, etc.).
• Manually browsing the website to validate or anticipate potential customer complaints.

This reactive process depended heavily on manual detection, user feedback, and social media monitoring.

Current Architecture (With Autonoma)

With Autonoma, the workflow has become proactive and automated:

• Autonoma runs scheduled tests across kavak.com and selected internal apps.
• Any anomaly automatically generates a Jira ticket for the Solutions Center.
• Proactive actions are triggered as soon as a potential incident is detected.
• Workarounds are automatically created for low-impact repetitive issues unresolved by engineering.
• A significant reduction in user complaints and social media reports.
• The SWAT team can now focus on customer experience during transactions, rather than detecting website errors.

Automated Verification and Continuous Learning

Autonoma also enables Kavak to automatically re-run tests for recurring issues. When a report is received in Jira, the Solutions Center can trigger Autonoma directly from the ticket to verify whether the issue persists, capturing concrete evidence for replication and resolution. This automation has dramatically reduced the time required for the Solutions Center to reproduce and document incidents.

Results and Impact

By leveraging AI-driven automation, Kavak’s Solutions Center has built a highly resilient, data-driven operation, designed to provide a 360° view of potential incident scenarios. This integration ensures:

• Operational excellence
• Unmatched incident resolution SLAs
• The best possible customer experience

Through its collaboration with Kavak, Autonoma AI empowers the Solutions Center to move from reactive incident management to a proactive, intelligent, and continuously improving operation.