🐈 Hello, Product Hunters!

Development Analytics.
Stop Dashboards. Start Prompting.

Welcome to the future of SDLC visibility. Keypup is the first autonomous agent that turns plain English into full-scale, prescriptive engineering dashboards & diagnosis. Connect your Git and Jira, and we do the rest.

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Hey Keypup, we're from Product Hunt. What exactly do you do?

We give you total visibility without the heavy lifting.

Skip months of BI setup. Just ask: "Why are our PR cycle times slowing down?"

I'll instantly query your tools and generate a full interactive dashboard.

Can you show me an example?

Absolutely! Here is a dashboard generated entirely from natural language. We also added prescriptive insights to show you exactly how to fix bottlenecks.

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Why Keypup for your team?

Your data shouldn't be locked behind complex queries. We are replacing dashboards with direct, immediate answers.

Prompt-to-Dashboard

Forget drag-and-drop. Simply describe a business problem, and the Keypup AI Agent instantly creates an entire, multi-insight dashboard mapping GitHub and Jira logic automatically.

Automated Contextualization

Zero-config logic. Every insight comes fully loaded. The AI automatically sets correct timeframes, configures deep drilldowns, and writes the documentation explaining why it matters.

Deep Synthesis & Analysis

The AI performs a detailed post-game analysis of your metrics. It identifies hidden correlations—like Change Failure Rate vs. Review Participation—and narrates the story of your SDLC in plain English.

The Improvement Loop

The Holy Grail of Engineering Management. The AI suggests specific improvement actions, and autonomously creates a new monitoring dashboard specifically designed to track success over the next 30 days.

Radical Use Cases

Seeing the Future:
From Chat to Action

Transform hours of manual configuration into a 10-second prompt with our autonomous intelligence engine.

Velocity & Performance Benchmark

DevEx & Flow Optimization

Shadow Work & Leakage

Continuous Velocity & Performance Benchmark

Benchmark Jira issue Cycle Time against your historical 6-month average. The AI dives into the issue level and maps it to specific GitHub PR metadata (size, review cycles) to find hidden drags on velocity and suggest actionable WIP limits.

AI Recommendations

Recommendations

Stale Item Cleanup: Issues like DP-607 and DP-1092 are heavily inflating your current cycle time. I recommend closing these if the work is no longer active or splitting them into smaller, manageable tasks.
Size Matters: Check the new Correlation Chart—if cycle times spike at the 300-400 LOC mark, enforce a “Small PR” policy to bring your current 153.9-hour average back down toward the 28.6-hour benchmark.

To keep your velocity within the top 20% of your historical performance, I recommend:

WIP Limits: Use the “In Progress” list to flag any issue that hits 80% of your benchmark time.
PR Sizing: Based on the correlation chart, if you see cycle time spike significantly at a certain LOC threshold (e.g., >300 lines), implement a team policy to break down PRs before they reach that size.
Weekly Review: Review the “Above Benchmark” list during every sprint ceremony to unblock linked PRs before they stagnate.

DevEx & Flow Optimization

Adopt the SPACE framework instantly. AI synthesizes disparate data—Git commit timestamps, Jira transitions, and PR comments—to create heatmaps of activity, measure Flow Efficiency, and monitor burnout risk automatically.

AI Recommendations

Key Recommendations

Enforce Smaller PRs: This is the single most impactful change. Reducing PR size to under 500 LOC will naturally improve Flow Efficiency, lower Review Time, and reduce the need for after-hours work.
Distribute the Review Load: Encourage other senior members (like twilliams-kp or adamaziz15) to take on more review responsibilities to alleviate the pressure on John Foo.
Investigate February’s Burnout Spike: Review the project timeline for February 2026 to see if that pressure was avoidable or if it’s likely to recur in the coming months.

Shadow Work & Roadmap Leakage

Detect "Orphan Commits"—GitHub activity not linked to any Jira issue. The AI calculates the exact "Cycle Time Tax" this untracked effort is putting on your roadmap, giving you the ammo to adjust scope and processes.

AI Recommendations

Key Recommendations

Enforce Jira Linking: Consider implementing a Git hook or CI check to require a Jira key in commit messages for the DoeProj repositories.
Capture Maintenance in Jira: Even security patches and releases should be represented by “Maintenance” or “Release” issues in Jira to ensure the roadmap accurately reflects team capacity.
Analyze High-Leakage Periods: Review the events of November 2025 to understand what caused the 51-hour drag on cycle time and whether those types of requests can be better managed in the future.
Increase Visibility: This dashboard suggests that your team is working hard, but much of that work is “invisible” to stakeholders. Bringing this effort into Jira will improve both capacity planning and roadmap accuracy. 🧠

Development Analytics.
Stop Dashboards. Start Prompting.