Introducing Railtown's Root Cause Analysis ⚡️

Fix errors quickly, increase your output

Monitor, diagnose, and prioritize errors efficiently with the help of AI and Machine Learning. Reduce the time spent on fixing errors without compromising product quality.

Root Cause analysis powered by AI

Railtown uses AI and Machine Learning on top of the error logs and dev tickets to determine the root cause of error and which environment it came from. Identify the source of an error in minutes instead of hours in a single dashboard.

Discover errors early, in real-time

Detect errors starting from dev machines, even before the code is checked in, all the way to production. Catch errors early and deploy codes with less error.

Deep integration with the
entire CI/CD environment

Railtown analyzes errors across the entire CI/CD environment, allowing users to locate the origin of each error identifiying the ticket for each error quickly.

Source Environment

Trace the environment where the bug originated, even down to local environments, to catch bugs before they get to production, including key PII and security flags. By grouping errors by root cause, we can alert the team to system-critical errors while dramatically reducing notifications for low-priority issues. The error dashboard provides full visibility into when errors happen, who is fixing them, and the status of the tickets.

Catch critical errors before they spread

With SmartClustering™, Railtown.ai groups errors by root cause. No more wasted time tracking down small, related errors. Railtown automatically matches errors with tickets to find common root causes for you.

  • Catch errors starting in the local developer box
  • Detect errors before code is checked to minimize errors in pipeline
  • Track the entire CI/CD environment from one tool
  • Receive notifications wherever is most convenient for your team: Slack, Email, Teams, Webhook, etc.

Ticket Likelihood

Our AI engine compiles all related errors across all environments into a single notification, tracks back to its first appearance, and matches the ticket that most likely caused the error for an efficient software building process. 

  • Reduce time spent on scouring information
  • Deliver lightning-speed fixes
  • Create and track fix-it tickets

Get immediate feedback, lessen context switching and reduce technical debt

  • Developers focus on current tasks without the distraction of unexpected production issues
  • Teams can manage technical debt more effectively and promote best sustainable development practices
  • Teams receive immediate feedback on their code changes, allowing them to address issues before it escalates

Impact you can clearly see

0%
fewer incidents
0h+
saved per week, per dev
0min
to know which error to fix

Railtown.ai gives us the confidence and peace of mind that we won’t miss important issues and will help us quickly get to the root cause

Khalid Ansari - Founding Partner 
Read Case Study

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