Actual hours vs AI estimates
Compare logged developer time with AI-generated estimates for both AI-assisted and manual development.
Verify engineering effort, not just code
See whether development time matches the work delivered.
InsightPM analyzes every pull request and compares actual logged hours against AI estimates with and without AI assistance — so founders and clients can verify engineering effort without reading code.
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Read-only GitHub permissions
PR #482 — Support multiple email recipients in report exports
insightpm/reports · opened by @hudv · +312 −94Actual logged time
14h 30m
Hours tracked by the developer.
AI-assisted estimate
6 – 8 h
Expected effort with active AI tool usage.
Manual estimate
10 – 12 h
Expected effort without AI assistance.
Plain-English explanation
This pull request looks smaller than the time logged. Similar work should likely take less time with active AI-assisted development.
Why InsightPM
Verify engineering effort without becoming technical.
InsightPM turns code changes into plain-English business reports. For every pull request, it shows what was delivered, how complex the work was, how much time was logged, and whether that time looks reasonable compared to AI-generated estimates.
Check if logged hours look reasonable
Compare actual developer time against AI-generated estimates based on the real scope of the pull request.
See whether AI is improving productivity
Understand whether the work looks AI-assisted, manually implemented, or slower than expected for the size of the change.
Understand what was actually delivered
Get a plain-English summary of the scope, business impact, risks, and effort behind every pull request.
Who it's for
Built for people who pay for development but do not read code.
Founders without a technical background
Know whether your team is moving efficiently and whether the hours logged make sense for the work delivered.
Agency clients
Verify time & material development work with independent AI-based effort estimates.
Product owners and managers
Understand what shipped, how much effort it required, and where delivery may be slower than expected.
Small agencies
Use InsightPM internally to review developer productivity, estimate quality, and AI adoption across the team.
Features
From pull request to effort verification.
Every feature in InsightPM exists to answer one question: does the logged time look reasonable for the work actually delivered?
AI productivity signal
See whether the pull request shows signs of effective AI-assisted development or mostly manual work.
Plain-English PR summary
Understand what changed, why it matters, and what was delivered without reading code.
Effort reasonableness check
Spot work that looks overestimated, underestimated, or inconsistent with the actual scope.
Risk and complexity context
Use risk and complexity signals only as supporting context for effort evaluation.
Jira and GitHub connection
Connect development activity and logged time to pull requests for a clearer view of delivery.
How it works
How InsightPM works
From your repository to a plain-English verdict on whether the logged hours look reasonable.
Connect GitHub
InsightPM reads pull requests from your repositories.
Connect Jira or add actual hours manually
Use logged Jira time or enter actual time manually for each pull request.
AI analyzes the pull request
The platform reviews the scope, complexity, changed files, and business impact.
Compare actual time with AI estimates
InsightPM shows whether the logged time is aligned with AI-assisted and manual development estimates.
Get a plain-English verdict
See if the work looks reasonable, slower than expected, or potentially inflated.
Use cases
Common questions InsightPM helps answer
Use evidence from real pull requests to start better conversations about time, scope, and productivity.
Is 18 hours reasonable for this pull request?
Get an independent AI-based estimate of expected effort and compare it to the actual logged time.
Would this work be faster with active AI tool usage?
See the gap between AI-assisted and manual estimates to understand the productivity opportunity.
Is my outsourced team logging realistic time?
Verify time & material work with an independent second opinion on effort and scope.
Are developers actually using AI to improve productivity?
Look at AI usage signals across pull requests to understand real AI adoption in the team.
Which pull requests look slower than expected?
Surface the changes where logged time is well above AI-based estimates, so you know where to look.
What was delivered in business terms, not technical jargon?
Read a plain-English summary of scope, business impact, and effort behind every pull request.
Pricing
Pay as you analyze pull requests
Use credits to analyze pull requests and compare actual hours against AI-based effort estimates. No subscription.
Starter Credits
For solo founders trying InsightPM on a single project.
$10
for 100 credits
Analyze pull requests and compare actual hours against AI-based estimates.
Buy creditsTeam Credits
For agency clients reviewing time & material development work.
$20
for 200 credits
Verify effort across multiple pull requests with independent AI estimates.
Buy creditsGrowth Credits
For active product owners and small agencies.
$50
for 500 credits
Track effort reasonableness and AI usage signals across a busy backlog.
Buy creditsScale Credits
For organizations verifying multiple teams and repositories.
$100
for 1000 credits
Run effort comparison at scale across repositories and contributors.
Buy creditsCredits are used to analyze pull requests and compare actual hours against AI-based effort estimates. Credit usage may vary depending on pull request size, complexity, and product feature.
Need a custom or Enterprise package? Contact support.
FAQ
Common questions about effort verification
How does InsightPM verify development time?
InsightPM analyzes every pull request and generates two AI-based effort estimates: one assuming active AI-assisted development, and one assuming fully manual implementation. It compares those estimates against the actual logged hours from Jira (or hours entered manually) so you can see whether the time looks reasonable for the scope of work delivered.
Is this a developer monitoring or surveillance tool?
No. InsightPM does not track keystrokes, screens, or developer behaviour. It gives founders and clients an independent second opinion on effort, scope, and delivery pace based on the actual content of pull requests — so conversations about time and productivity can be based on evidence, not guesses.
Do I need a technical background to use it?
No. Every pull request gets a plain-English summary covering what was delivered, how complex the work was, how much time was logged, and whether that time looks reasonable. You do not need to read code.
Can InsightPM guarantee that AI was used — or that time was inflated?
No. InsightPM provides signals and independent estimates, not guaranteed detection. Results are framed as "looks reasonable", "higher than expected", or "AI usage signal: low/high" — supporting context to help start better conversations, not accusations.
How does it connect to my repository and time tracking?
You install the official InsightPM GitHub App and pick which repositories it can read. You can connect Jira to use logged time, or enter actual hours manually per pull request. All GitHub permissions are read-only and can be revoked at any time.
Is my source code safe?
We only read the metadata and diffs of pull requests you explicitly authorize. We do not clone or store your full source tree, and we do not train models on your code.
How much does it cost?
InsightPM sells prepaid usage credits. Standard packs are $10 / 100 credits, $20 / 200 credits, $50 / 500 credits, and $100 / 1000 credits. Pay as you go — no subscription. New accounts get free credits to try the product.
Contact
Talk to us
Questions about effort verification, custom packages, or anything else — send a message and we'll get back to you.