Quantypace
Flow metrics and Monte Carlo forecasting for Linear + GitHub teams to answer "when will this ship?" with probability distributions instead of guesses.
Cost / License
- Freemium (Subscription)
- Proprietary
Platforms
- Online
- Software as a Service (SaaS)
Features
- Goal Tracking
- Real time collaboration
- Ad-free
- Dark Mode
- No Coding Required
Quantypace News & Activities
Recent activities
- elvirus839 added Quantypace
elvirus839 added Quantypace as alternative to Haystack Analytics, Velocity, Coderbuds and Athenian
Quantypace information
What is Quantypace?
Quantypace provides flow metrics and probabilistic forecasting for engineering teams using Linear and GitHub. Track full cycle time from issue creation through PR review to deployment, identify bottlenecks in your delivery pipeline, and forecast ship dates with confidence intervals (P50/P85/P95) using Monte Carlo simulation.
Built for engineering managers and tech leads who need better sprint planning, more effective retrospectives, and delivery confidence based on data rather than estimates.
Key features:
- Code-to-Deploy Metrics: Track issue ? PR ? merge ? deploy timings with bottleneck detection
- Monte Carlo Forecasting: Probabilistic ship date predictions with P50/P85/P95 confidence levels
- Cycle Time Analytics: P50/P85 trends, throughput tracking, and outlier detection
- Improvement Hub: Track hypotheses, measure ROI, and validate process changes
- Ceremony Packs: Auto-generated planning and retro materials based on actual delivery data
- Secure Integrations: OAuth-based Linear + GitHub integrations with webhook support
Quantypace handles both issues with and without GitHub PRs - cycle time is measured from Linear status transitions, while GitHub data adds code-to-deploy granularity. This makes it suitable for teams with mixed workloads (feature development, config changes, documentation, planning).
Alternative to LinearB, Screenful, and Swarmia with per-team pricing ($29/mo) instead of per-user pricing.





