Bug prediction for pull requests
Pinpoint PRs requiring remediation, and expedite the delivery of those that don’t.


Give reviewers the cheat codes
Shepherdly calls out the riskiest areas of the change based on how code is performing in production.

Prioritize PR reviews by risk
Senior engineers can focus on the PR’s where they can have high impact by remediating risk before a change ships.
Find the outliers
of risk within a change
Each risk score is broken down by its independent predictors so you can hone your review & remediation steps before it’s merged.


Uncover which areas
are driving bugs
Highlight which areas are unique to each team and repository, enabling them to pull forward the most impactful outcomes supported by actual production error telemetry.
Teams can scale decision-making by incorporating this context directly into the PR flow.
Track the risk building
up in your releases
Leverage historical trend data to support your tech debt initiatives, understand which teams have the right risk/reward ratio, and measure efficacy of process changes.

Quickly Identify Hotspots
Narrow down the modules and files that are the the most buggy.
Easily integrate within your existing tech stack
Shepherdly monitors GitHub activity, bug tracking systems, and your error observability stream to produce a risk score for each pull request.


Research driven
Derived from academic and company research spanning thousands
of papers from Computer Scientists and practitioners.

Code Reviews Do Not Find Bugs

Better Effort-Aware Just-ln- Time Defect Prediction

Implementations Through a Developer-informed Oracle
Customer spotlight
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