Faros AI vs. minware
Faros AI is a relatively new entrant to development analytics. They have set a new standard with their level of customizability and open-source offering.
They also have an AI query interface, but the underlying data is not built using modern modeling methods.
If you want to actually get better at planning, quality, and process efficiency without building everything yourself with actionable metrics, Faros’ first-generation platform is inadequate.
The problem with first-gen metrics
Faros’ first-gen metrics rely on existing data fields (PR cycle time, deployment count, etc.) They will get in 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
Faros’ 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 replace tedious non-engineering work that wastes their time.”
Kevin Borders
Founder & CEO, minware
Next-gen data models offer insights without effort
Next-gen data models use 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.
Next-gen data models answer real questions
CEOs don't ask about Faros metrics like cycle times. Next-gen data models answer real questions like these (links go to live demo):
minQL and BI report builder let you customize anything
Faros also cares about customization and exposes a lot of fields for building custom metrics. However, the reports are still based on low-level SQL queries, so customizing them is not easy from the UI
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.
Zero-effort setup
Faros is more powerful than most other dev analytics software, but the setup is very much do-it-yourself. To get it fully configured, prepare to spend weeks tailoring it to your needs.
We’ve invested heavily in making minware work out-of-the box with fully automated configuration and no process changes. All you need to do is hook up version control and ticketing systems with a few clicks. Any customizations are quick and easy with minQL.
No story points? No sprints? No tickets in PRs? No Org Chart? Different usernames in Git/Jira? Crazy ticket statuses? No problem, we’ll figure it out.
Setup Difficulty
minware
Faros
Intensive (Weeks)
Self-Service (Hours)
Zero Effort
Why choose Faros over minware?
This question may be the opposite of what you were expecting.
With Faros' open-source offering, you can modify and extend it in any way, such as creating completely custom data connectors.
However, to get more than limited out-of-the-box modules, you need to work with low-level SQL queries.
minware's approach is a bit different. We still offer deep customizability with minQL, but our goal is to make it as easy as possible.
If Faros' flexibility appeals to you, but you don't want to spend a bunch of engineering time setting it up...
