Traversal

About Traversal

Traversal provides an AI-powered Site Reliability Engineer (SRE) agent that autonomously ingests and traverses enterprise telemetry data, including logs, metrics, and traces. The platform uses causal machine learning and LLMs to diagnose root causes, determine blast radius, and suggest remediation for production incidents in real time. It integrates with existing observability stacks to offer a unified view and natural-language explanations for faster debugging.

<problem>Modern enterprise applications generate massive, heterogeneous telemetry—logs, metrics, traces, and code—making it hard for engineers to locate the true root cause of incidents quickly. Traditional observability workflows require manual digging through alerts and data, leading to alert fatigue, long debugging cycles, and costly downtime.</problem> <solution>Traversal delivers an AI‑powered Site Reliability Engineer (SRE) agent that autonomously ingests and traverses petabytes of telemetry to diagnose, remediate, and even prevent production incidents. By combining causal machine‑learning, large language models, and an orchestrated tool‑calling architecture, the platform surfaces the blast radius, key bottlenecks, and evidence‑backed root causes in real time. It translates complex findings into natural‑language explanations, enabling engineers to focus on fixing rather than hunting. The system integrates with existing observability stacks via read‑only access and supports flexible deployment models, including on‑premise and cloud, preserving data privacy while providing a single pane of glass for incident response.</solution> <features> - Causal inference and LLM‑driven root‑cause analysis that distinguishes symptoms from true causes - Autonomous incident troubleshooting, remediation, and preventive actions - Orchestrated tool calls that can query logs, metrics, traces, and code repositories in seconds - Seamless integration with major observability tools (Datadog, Prometheus, Grafana, VictoriaMetrics, Mimir, Elasticsearch, OpenSearch, New Relic, Splunk, etc.) - Read‑only access and optional on‑premise deployment for strict data‑residency requirements - Single‑pane‑of‑glass view that consolidates heterogeneous data sources into a unified incident timeline - Scalable architecture capable of traversing petabyte‑scale datasets in real time </features> <target_audience>Traversal is aimed at Site Reliability Engineers, DevOps teams, and software engineers in large enterprises that operate complex, microservices‑based infrastructures and need faster, more accurate incident resolution.</target_audience> <traction>By mid‑2025 Traversal had secured enterprise customers including Digital Ocean, Eventbrite, Cloudways, and several undisclosed Fortune 100 financial services firms. A partnership with Digital Ocean reported a 37 % reduction in mean time to resolution over six months, translating into millions of dollars saved in downtime and developer productivity. The company publicly launched its AI SRE agent in June 2025 and continues to expand its integrations across the observability ecosystem.</traction> <sources> - https://fortune.com/2025/06/18/traversal-emerges-from-stealth-with-48-million-from-sequoia-and-kleiner-perkins-to-reimagine-site-reliability-in-the-ai-era/ - https://www.traversal.com/post/launch-announcement - https://www.kleinerperkins.com/perspectives/traversal_series_a/ - https://tech.cornell.edu/news/traversal-ai/ - https://www.traversal.com/about-us - https://www.traversal.com/blog - https://www.aol.com/traversal-emerges-stealth-48-million-111152692.html - https://sequoiacap.com/article/partnering-with-traversal-because-every-engineer-remembers-their-first-time-troubleshooting/ - https://www.sequoiacap.com/podcast/training-data-traversal/ </sources>

What does Traversal do?

Traversal provides an AI-powered Site Reliability Engineer (SRE) agent that autonomously ingests and traverses enterprise telemetry data, including logs, metrics, and traces. The platform uses causal machine learning and LLMs to diagnose root causes, determine blast radius, and suggest remediation for production incidents in real time. It integrates with existing observability stacks to offer a unified view and natural-language explanations for faster debugging.

Where is Traversal located?

Traversal is based in New York, United States.

How much funding has Traversal raised?

Traversal has raised 48000000.

Location
New York, United States
Funding
48000000
Employees
48 employees
Major Investors
Sequoia Capital, Kleiner Perkins, NFDG, Hanabi Ventures

Find Investable Startups and Competitors

Search thousands of startups using natural language

Traversal

⚠️ AI-generated overview based on web search data – may contain errors, please verify information yourself! You can claim this account with your email domain to make edits.

Executive Summary

Traversal provides an AI-powered Site Reliability Engineer (SRE) agent that autonomously ingests and traverses enterprise telemetry data, including logs, metrics, and traces. The platform uses causal machine learning and LLMs to diagnose root causes, determine blast radius, and suggest remediation for production incidents in real time. It integrates with existing observability stacks to offer a unified view and natural-language explanations for faster debugging.

traversal.com3K+
New York, United States

Funding

$

Estimated Funding

$20M+

Major Investors

Sequoia Capital, Kleiner Perkins, NFDG, Hanabi Ventures

Team (40+)

No team information available.

Company Description

Problem

Modern enterprise applications generate massive, heterogeneous telemetry—logs, metrics, traces, and code—making it hard for engineers to locate the true root cause of incidents quickly. Traditional observability workflows require manual digging through alerts and data, leading to alert fatigue, long debugging cycles, and costly downtime.

Solution

Traversal delivers an AI‑powered Site Reliability Engineer (SRE) agent that autonomously ingests and traverses petabytes of telemetry to diagnose, remediate, and even prevent production incidents. By combining causal machine‑learning, large language models, and an orchestrated tool‑calling architecture, the platform surfaces the blast radius, key bottlenecks, and evidence‑backed root causes in real time. It translates complex findings into natural‑language explanations, enabling engineers to focus on fixing rather than hunting. The system integrates with existing observability stacks via read‑only access and supports flexible deployment models, including on‑premise and cloud, preserving data privacy while providing a single pane of glass for incident response.

Features

Causal inference and LLM‑driven root‑cause analysis that distinguishes symptoms from true causes

Autonomous incident troubleshooting, remediation, and preventive actions

Orchestrated tool calls that can query logs, metrics, traces, and code repositories in seconds

Seamless integration with major observability tools (Datadog, Prometheus, Grafana, VictoriaMetrics, Mimir, Elasticsearch, OpenSearch, New Relic, Splunk, etc.)

Read‑only access and optional on‑premise deployment for strict data‑residency requirements

Single‑pane‑of‑glass view that consolidates heterogeneous data sources into a unified incident timeline

Scalable architecture capable of traversing petabyte‑scale datasets in real time

Target Audience

Traversal is aimed at Site Reliability Engineers, DevOps teams, and software engineers in large enterprises that operate complex, microservices‑based infrastructures and need faster, more accurate incident resolution.

Traction

By mid‑2025 Traversal had secured enterprise customers including Digital Ocean, Eventbrite, Cloudways, and several undisclosed Fortune 100 financial services firms. A partnership with Digital Ocean reported a 37 % reduction in mean time to resolution over six months, translating into millions of dollars saved in downtime and developer productivity. The company publicly launched its AI SRE agent in June 2025 and continues to expand its integrations across the observability ecosystem.

Sources:
Want to add first party data to your startup here or get your entry removed? You can edit it yourself by logging in with your company domain.