Traversal functions as an AI Site Reliability Engineer (SRE) designed to manage complex system incidents. It reduces alert noise, surfaces root causes by analyzing telemetry and code changes, and guides teams toward rapid remediation. The platform enables engineers to fix issues with single-click actions and automatically generates evidence-based post-mortem reports.
Funding
$48M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
HVNFounders
Product
Problem
Modern software systems generate vast amounts of telemetry data, including logs, metrics, and code, making it difficult for developers to quickly identify the root causes of errors and latency. Traditional observability workflows are complex, often overwhelming engineers with a flood of alerts and logs, leading to alert fatigue and prolonged debugging times.
Solution
Traversal provides an AI-powered site reliability agent that analyzes telemetry data to automatically troubleshoot, resolve, and even prevent production incidents. The platform parses logs, metrics, traces, and codebases to pinpoint the root causes of errors and latency, translating complex data into natural language for easier understanding. By autonomously surfacing the blast radius, key bottleneck services, and candidate root causes with supporting evidence, Traversal significantly reduces the time to resolution for complex incidents. Traversal integrates with existing systems through read-only access and flexible deployment models, offering optional on-prem deployment and ensuring data privacy.
Target Audience
Traversal is designed for Site Reliability Engineers (SREs), DevOps teams, and software engineers in enterprises with complex infrastructure and microservices architectures.
Features
- AI-driven root cause analysis using causal machine learning, LLM reasoning models, and AI agents
- Automated incident troubleshooting, resolution, and prevention
- Integration with existing observability stacks, including Datadog, Prometheus, Grafana, and others
- Read-only access and flexible deployment options (on-premise or cloud)
- Support for heterogeneous data sources
- End-to-end self-healing capabilities
- Optional self-hosting for strict data residency requirements