Monte Carlo forecasting for Jira teams

Monte Carlo takes the real throughput of your team — how many tickets you actually finished each week — and uses it to simulate thousands of possible futures. The output isn't a single date. It's a probability distribution: 50% chance we're done by May 12, 85% chance by May 28.

The forecast is based on what your team has actually delivered, not on what someone estimated. No story points, no velocity averages — just real throughput data. If the team has been delivering between 4 and 12 tickets per week for the past three months, the simulation samples from that reality.

Cylenivo reads your ticket history from Jira and calculates weekly throughput. Then you can ask it two questions:

• "How many tickets can we ship in N weeks?" — returns a probability distribution of outcomes.
• "When will N tickets be done?" — returns a date distribution with confidence levels.

No extra configuration beyond the Jira connection. The throughput data comes from the same status transitions that feed cycle time and lead time — if you've set those up, forecasting works out of the box.