Deadlines keep slipping
Status updates sound reasonable, but it is still unclear whether the delivered work matches the time and budget invested.
AI-powered engineering analytics
Activity is visible. Contribution is harder to see
DevGhost analyzes Git history, estimates the amount of substantive work behind code changes, and shows teams and developers on one comparable scale.
BlogHunting Ghosts: How to See What Developers Really ContributeDevGhost is a software-engineering analytics tool that estimates the cognitive effort behind code changes and turns it into Ghost% — a team's delivered output measured against a pre-AI baseline. It is built for engineering owners and managers, and it uses no time tracking, screen capture, or keystroke logging — only the code changes themselves.
When reports are not enough
Common engineering problems, backed by data instead of impressions
DevGhost complements deadlines, tickets, and delivery metrics with an estimate of the work behind code changes.
Employees and contractors are hard to compare
Different processes and reporting styles obscure each contributor’s output. DevGhost brings them onto one scale.
AI was rolled out, but the impact is unclear
See whether productivity changed after AI adoption and which working practices actually produce results.
Team assessment depends on perception
Digital signals help surface sustained dips and strong developers whose exceptional output has become invisible.
Benchmark
What DevGhost reveals
01
Real Output
Measure real engineering output, not commit volume.
02
Delivery Pace
See what's keeping delivery moving — and where it's getting stuck.
03
AI-Era Gap
See how far your team is from AI-era speed.
Built for
Who DevGhost is for
No agent to install. No surveys to run. DevGhost reads your Git history and turns it into a clear picture of how engineering work actually flows — not how many commits were logged.
Founders & CEOs
“I'm investing in engineering. Where is that effort turning into shipped progress, and where is it getting diluted?”
Where your delivery actually comes from — which teams and repositories drive it, and how much of the effort reaches shipped work.
CTOs & engineering leaders
“Where is delivery slowing down, and which repositories are carrying the work?”
Delivery patterns down to the contributor level, the bottlenecks worth a closer look, and how that changed before and after your AI rollout.
Investors & due diligence
“Does this engineering team produce at the level the story suggests?”
An outside-in read of how engineering work is distributed — by contributor, team, and across the codebase — without interviews, surveys, or internal dashboards.
Contributor-level signals, always shown in context — built to inform management conversations, not automate verdicts about people.
Process
How it works
1
Connect repositories
Link your GitHub or GitLab account, or add public repos by URL. Commit history is extracted automatically.
2
Run analysis
AI estimates cognitive effort for each commit — accounting for complexity, not just diff size.
3
Review Ghost%
See each developer's Ghost% — the ratio of estimated productive output to expected capacity.
DevGhost On-Prem · waitlist
Does your code need to stay inside the company?
Join the On-Prem waitlist. Your answers help us understand the use case, Git setup, and internal LLM requirements before the first technical call.
- Source code, changes, and analysis results stay inside company infrastructure
- Read-only access to your internal Git
- Analysis through an approved model in your internal LLM environment
Pricing
Simple credits-based pricing
One credit per analyzed commit; a squash PR counts as half its internal commits. Exact cost is shown before every run.
Free$0/mo
- 2,000 credits when you sign up
- 500 free credits every month
- Full product — no feature limits, no card
Pro$100/mo
- Up to 4,000 credits / month
- Priority pipeline lane
Business$500/mo
- 24,000 credits / month — best value
- Everything in Pro
- Lower per-credit top-up pricing
FAQ
Questions teams ask
Are you monitoring developers? Where do the hours come from?+
No — no time tracking, no screens, no keystrokes. We analyze only the code changes themselves and estimate their cognitive difficulty in the hours of a reference developer. It's a yardstick, not a timesheet.
How exactly do you estimate effort?+
It's not "one call to a neural network" but a multi-stage pipeline in which AI is only one layer. First a model reads the code changes themselves — what actually changed — and judges the cognitive difficulty for a reference developer, rather than counting lines or commits. On top of it runs a deterministic algorithmic layer: the system classifies the nature of each change, separately recognizes high-stakes work (for example infrastructure, data migrations, security), filters out mechanical and generated changes (mass find-replace, generated and moved code, formatting), and applies sets of correction rules and guardrails so a single model guess can't swing the result. Large and combined commits are handled in more detail. The same standard is applied to everyone automatically, each commit is evaluated once and the result is fixed — hence comparability and reproducibility.
My team uses AI. Does that break the metric?+
On the contrary — that's the whole point. We compare your team against a reference developer who works without AI; if AI lets you deliver more per day, Ghost% goes up, and that gap from the "pre-AI norm" is exactly what the product shows. It's not a distortion — it's the result.
What is Ghost% and how do I read it?+
The ratio of your daily output to the output of the reference developer. 100% is on par with the reference, higher means you deliver more per day, lower means less. It's not hours and not overtime: a high number doesn't mean "burning out," and a low one by itself doesn't mean "weak."
How much can I trust it?+
It's a model, not a measurement. No one can reconstruct the real time, so the value is in one set of rules for everyone: strong for trends and comparisons, not for accuracy to the hour for a single person. A tool to ask better questions, not to pass verdicts.
Can I use it for reviews, pay, or layoffs?+
Not on its own. It's a team signal and a trend to start a conversation, not an individual verdict: one metric doesn't capture quality, impact, or context.
Is there a free plan, and what does an analysis cost?+
Yes. Every account starts with a batch of credits and gets a fresh free allowance every month — no card required and no feature limits: the free plan is the full product. One credit covers one analyzed commit, and a squash-merged pull request counts as half its internal commits. The exact cost of a run is shown before it starts.
Ready to see what's really happening?
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