Sleuth VS DevPerform
Compare Sleuth VS DevPerform and see what are their differences
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DevPerform is engineering intelligence for engineering leaders: delivery metrics and developer sentiment in one product, so when a number moves you can ask the team about it and see both answers side by side.
Connect GitHub, GitLab, or Bitbucket and DevPerform computes DORA metrics, phased cycle time, review health, throughput, and investment allocation automatically โ no agents on developer machines, no CI changes, and your source code is never stored. Anonymous developer surveys (DX Core 4, eNPS, engagement) roll into a 0โ100 Experience Index you can trend wave over wave, and survey results can be triaged into team-visible focus areas with follow-through tracking.
It is deliberately not a surveillance tool: there are no individual rankings or leaderboards, survey answers sit behind an anonymity threshold, and AI adoption and impact are measured at team level only.
Fully self-serve: instant interactive demo, free public repo benchmark, public pricing, free tier, and a 14-day Pro trial. No sales call required.
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DevPerform's answer:
Engineering leaders โ VPs, directors, and team leads โ at software teams of any size, from a small startup to a large enterprise. DevPerform is self-serve, so small teams can start in minutes, and it scales to large orgs and monorepos without agents or CI changes. Any company building software on GitHub, GitLab, or Bitbucket is a fit.
DevPerform's answer:
DevPerform was built by engineers who kept seeing the same gap: delivery dashboards that flag a slow week but can't explain it, and engagement surveys nobody acts on. Putting the two in one loop โ number moves, team explains, leadership commits, next survey shows the follow-through โ turned out to be the product. Launched in 2026, bootstrapped and self-serve from day one.
DevPerform's answer:
DevPerform pairs delivery metrics (DORA, cycle time, review health) with anonymous developer surveys in one product. Metrics tell you what is slow; surveys tell you why โ and when a number moves you see both side by side, then close the loop: mark a survey dimension as a focus area, set a goal on it, and the next wave shows whether it worked.
DevPerform's answer:
It's self-serve end to end where most of this category is sales-led: an instant demo with no signup, a free public repo benchmark, public pricing from $0, and a 14-day Pro trial with no credit card. Setup reads your GitHub, GitLab, or Bitbucket metadata directly โ no agents on developer machines, no CI changes โ and everything ships on two public tiers with no seat minimums or annual-only contracts.
DevPerform's answer:
React + TypeScript frontend, Python (FastAPI) backend, PostgreSQL, deployed on Kubernetes. Data comes from the GitHub, GitLab, and Bitbucket APIs โ repository metadata only; source code is never stored.
Based on our record, Sleuth seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I can tell you how my product (sleuth.io) does it. If it detects a push to master that isn't deployed, it adds a PR/commit status check of red to every open PR. Then at the end of the deployment and optionally after a final check, it reports the commit as deployed, which then triggers code that adds a PR/commit status check of green to every open PR. Source: almost 4 years ago
For starters, there a number of tools such as Sleuth (disclaimer: am co-founder) that will measure the metrics for you. There are also open source options like Four Keys and many vendors like Gitlab also provide some or all metrics as well, though make sure they are measuring things as you expect. Source: almost 4 years ago
Sleuth co-founder here. My dev team uses our own tool to track DORA metrics, and I've found there are some things the metrics are great for, and others that don't really pan out. I made a video it, but the tl;dr; is metrics themselves don't do anything, but can be useful to track progress of an existing initiative, keeping performance as you scale, or alerting on outliers. Source: about 4 years ago
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