engineering investment report
AI-driven visibility into your engineering team's work
A suite of monthly reports (100% automated by AI) that categorize your team's actual work in GitHub and give you the control to make smarter decisions on resources, timelines, and productivity
The problem
Are your teams working on priorities or simply keeping the lights on?
As an engineering leader, you need to ensure your teams are focused on the right work. But tracking workload allocation is incredibly manual and often inaccurate.
And automated solutions like Jellyfish and LinearB are expensive, complicated to set up, and have a major flaw — they rely on information in your project management tools being properly labeled and categorized.
And automated solutions like Jellyfish and LinearB are expensive, complicated to set up, and have a major flaw — they rely on information in your project management tools being properly labeled and categorized.
the solution
Full-picture visibility of your engineering teams — 100% automated by AI
features
Insights to help you maximize your impact
See how much time is spent on strategic work
You can’t move forward if your team is constantly bogged down by bugs and operational work.
Have the proof you need to justify more headcount, adjust targets, or make process improvements.
Have the proof you need to justify more headcount, adjust targets, or make process improvements.
Our weekly trendline chart lets you easily identify periods when bugs, O&M, and admin are eating into your priority work
See how engineer contributions stack up
Easily identify your highest and lowest performing engineers, or situations where bugs and O&M are unevenly balanced across your team
Our issue assignees chart shows the allocation of work across each of your engineers, making it easy to compare and benchmark
See how much you’re spending on bugs
Understand where your team is spending its effort and how that impacts your engineering costs
Our financial impact analysis uses industry benchmarks to estimate how much you’re investing in bug work
Get started
how it works
Get reports without adding to your team’s workload
Unlike costly tools that burden your team, our AI-driven reports need no manual updates or labeling. While your data stays secure and never shared
AI-generated analysis
Our AI model will analyze issues and pull requests in your Github instance and automatically generate insights surrounding your operational effectiveness
Receive your personalized report
Our team presents your personalized Engineering Investment Report where we highlight potential insights, raise questions, and make recommendations
Repeat
We’ll help you run this analysis on a monthly, quarterly or bi-annual basis to ensure you always have a clear picture of what your teams are working on
What questions can you answer with the Engineering Investment Report?
We asked our customers “What strategic questions will these types of insights help you answer?” Here’s some of what they said…
Which projects are consuming the most developer time?
Are our top engineers spending too much time on low-value tasks?
Do we have the right balance of resources to meet upcoming deadlines?
Which teams or engineers are consistently exceeding expectations, and why?
Are we correctly estimating the time and resources needed for our projects?
Are we dedicating enough resources to innovation versus maintenance?
What is the ROI of investing in better QA or automated testing?
Are our junior devs receiving the right amount of mentorship and challenging work?
Which projects are at risk due to resource constraints or underperformance?
Which parts of our codebase are most prone to bugs?
It’s time to unlock your team’s ability to deliver more
Want insights like these for your engineering team?
Contact our sales team to start your report—monthly or quarterly options available.
Contact our sales team to start your report—monthly or quarterly options available.