Sleuth vs. minware
Sleuth tracks DORA and DevEx metrics with AI insights, but their deployment-focused approach limits broader code and quality analytics.
If you want to get better at planning, quality, and process efficiency with actionable metrics, Sleuth’s first-generation platform is inadequate.
The problem with first-gen platforms like Sleuth
Sleuth’s first-gen platform relies on existing data fields (PR cycle time, deployment count, etc.) They will get you in the right ballpark, but are:
Lagging, unactionable
They tell you what happened, but not what caused it. Why are cycle times slow – is it interruptions, bad estimates, large tickets? How do I get better?
Disconnected from impact
Sleuth’s metrics use arbitrary unit counts (tickets, PRs, etc.), which don’t tell you what matters.
Cumbersome and manual
If you want additional visibility (work type, tech debt, active dev effort, etc.), you have to painstakingly label tickets or log time by hand.
“Instead of AI replacing engineers, maybe it should help them get better.”
Kevin Borders
Founder & CEO, minware
minware’s AI & data platform offers insights without effort
minware uses modern methods to derive metrics with higher-level meaning (e.g., active development time per ticket) that are:
Actionable
See exactly where problems lie so you know where to improve.
Impact-Focused
Measure the effect on available engineering time instead of arbitrary unit counts.
Automatic
Compute high-level properties without having to log time, impose mandatory fields, or change the way you work.
minware answers real questions
CEOs don't ask about Sleuth metrics like cycle times. minware answers real questions like these (links go to live demo):
minQL and BI report builder let you customize anything
Sleuth has nice metric visualizations and lets you configure alerts. However, the customization is only surface level and the reports themselves are locked in place.
All minware reports are built on top of the minQL query language and fully editable. Access any field from any data source to create custom metrics with powerful formulas, including custom event cycle times.
Say goodbye to spreadsheets and SQL.
How Does Sleuth Stack Up?
Sleuth makes it easy to get started, but configuring everything to link and name different aliases can still be a lot of work.
We've made minware work out of the box to deliver instant value with zero-effort setup, comprehensive prebuilt reports paired with limitless customization opportunities, and an AI chat analyst that makes insights accessible to everyone.
No story points? Crazy ticket statuses? No tickets in PRs? No problem, we’ll figure it out.
Feature
minware
Sleuth
Instant Data Connection
LLM-Powered AI Insights
AI Chat
Automatic active coding time analysis
Comprehensive pre-built reports
Query anything in your data set
Why choose Sleuth over minware?
This question may be the opposite of what you were expecting.
Sleuth does one thing well – DORA metrics – and is an easy solution if your boss is just asking for that, or if you are only responsible for DevOps.
If that’s all you want and you are not interested in deeper, more actionable metrics, then minware might be overkill.
We evaluated similar first-gen DORA metrics tools a few years ago ourselves, but saw how they just don’t make it easy to get better.
If you want to unlock your team’s full potential...