To innovate, you use data. To make product decisions, you use data. Product and engineering are becoming synonymous, yet product development often is subjective, while you use data.
In the absence of meaningful data, the narrative for your product vision is typically reduced to time, resources, and story points. More often than not your project planning sessions are based on subjective feelings. It's difficult to continuously improve and delivery at scale, when you're telling stories with arbitrary data.
Data. Metrics. Reporting. The very things you need to make product and roadmap decisions are what the software engineers building product need in their day-to-day work.
Feature development often takes a back seat to conflicting engineering priorities. Building product and managing technical debt is a balancing act for any enterprise. A lack of visibility into the what, why and how of your product development, means more agile startups are continuously improving and going to market faster.
Debug your product development processes with objective data. Turn code into a shared language you can use to make more informed decisions and ship features faster.
Is product development getting faster or slower?
What features are blocked and stuck in code review?
How are business critical projects progressing?
Remove blind spots. Get insights and trends to help you better understand the efficiency of your releases.
See the work more clearly and reduce engineering cycle time. Get a powerful visualization of all commits and pull requests.
Get a comprehensive view of your software engineering team's contributions and work patterns.
As engineering teams get larger, it’s more complicated; more repos, more code, more people. Without a tool like GitPrime that pulls it all together, it’s almost impossible to get a handle on what’s going on.”Adam Abrevaya, VP Engineering, CloudHealth
Increase in Impact to the Codebase
Increase in Features Delivered
Decrease in Bugs Introduced
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Accelerate software delivery cycles and time to market.
Better understand how engineering resources are deployed.
Calculate real costs for new and ongoing initiatives.
Spot healthy and unhealthy work patterns.
Focus on facts over feelings, and objectivity over subjectivity.
Turn code into a language that everyone can understand.