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Sprint Burndown Sprint 23 · 6 days left
⚠ Behind ideal pace
Cycle Time
3.8d
↑ from 2.1d
PSI Score
61
↓ Watch zone
Delivery
78%
↑ +6%
AI
3 tickets in Code Review 14+ days — may block sprint goal. Suggest rotating reviewers.
Sprint ended — nobody knows why tasks didn't ship 45 min in Jira to answer "are we on track?" Risk surfaced at sprint review — not before Team load invisible until someone burns out Cycle time crept up for 3 weeks — nobody noticed Standup was 40 minutes and answered nothing Sprint ended — nobody knows why tasks didn't ship 45 min in Jira to answer "are we on track?" Risk surfaced at sprint review — not before Team load invisible until someone burns out Cycle time crept up for 3 weeks — nobody noticed Standup was 40 minutes and answered nothing
The problem

Small teams don't need a PM.
They need answers.

When you're a CTO or engineering lead at an early-stage startup, Jira is a graveyard of data nobody reads. Until something breaks.

Manual status hunting

Every Monday you pivot through Jira, cross-reference due dates, filter by sprint — just to answer "is the project on track?" 45 minutes. Every single week.

⚠️

Risks surface too late

Cycle time crept up over three weeks. A task was quietly reassigned twice. Nobody noticed until the sprint review.

👥

Team load is invisible

Some contributors are blocked, others overloaded. You find out during 1:1s. By then, delivery accuracy has already taken a hit.

Features

Not just a dashboard.
A Jira co-pilot.

See what's happening with your delivery — and act on it. No forms, no clicks, no PM needed.

PSI · 0–100

Project Stability Index

A single health score computed from Jira transitions — no setup. Below 40 is Critical. mFlow reads changelog data and recalculates continuously.

≥80 Stable ≥60 Watch <40 Critical
Zero setup

Auto-tracked delivery metrics

Cycle Time, Throughput, Reopen Rate, Delivery Accuracy — all derived from Jira changelog. No tags, no custom fields, no config.

Cycle Time Throughput Reopen Rate
Project + task level

Risk flags before they escalate

mFlow scans every project for backlog growth, cycle time regression, stale tasks, and repeated reassignments. Surfaces them before they become your problem.

Backlog growth Stale tasks Overdue
Not a generic chatbot

AI with full delivery context

The AI knows your cycle times, blockers, and contributor load. Ask "what is slowing us down?" and get a data-backed answer — not a generic tip.

Project view Team view Individual
AI assistant

An AI that knows
your actual data.

Ask questions in plain English and get data-backed answers specific to your team — not generic advice. No prompting guides needed.

mFlow AI · Alpha-Backend
What is slowing us down? Who is overloaded? Biggest risks?
Y
What is slowing us down?
AI
Cycle time on Alpha-Backend increased from 2.1d to 3.8d over the last 3 sprints — mainly driven by tasks stuck in Code Review (avg 1.4d). 3 tasks have been in-progress for 14+ days without a transition. Consider reducing review queue or rotating reviewers.
How it works

Three steps.
Zero spreadsheets.

From Jira connection to delivery insights in under five minutes.

01

Connect Jira

Click "Connect Jira." An OAuth popup opens — no tokens to copy, no API keys. Authorize mFlow in your Atlassian account and close the popup.

OAuth 2.0 · Atlassian-verified
02

Select projects + history

Choose which Jira projects to include and how far back to sync — from 1 month to 2 years. First sync is full; after that, mFlow only fetches changes.

1 month → 2 years · Incremental sync
03

Get answers instantly

PSI scores, delivery metrics, and risk flags appear immediately. Open the AI assistant and ask anything — it has full context of your data.

Real-time · No dashboards to configure

Your Jira already has the answers.
mFlow just reads them.

Free to start. Connects in under 2 minutes. No PM required.

Connect Jira — it's free →

Free tier · No credit card · Cancel anytime