Delivery risk, computed from capacity + dependencies.

Turn a PRD/RFP/SOW into a delivery model that shows who becomes the bottleneck, what slips, and why — with scenarios to keep the date.

No login required. Works with rough scope. You can use placeholder capacity.

See a real Motionode output

Download a sample Risk Intelligence Report generated from a real Delivery Risk analysis.

Download example report (PDF)

Paste scope

Paste scope

Paste a PRD/RFP/SOW excerpt (rough is fine). Next you’ll set a target date + team capacity to see the risk model.

Motionode delivery risk intelligence view

Most PM tools track work. They don’t compute outcomes.

You can build a roadmap in Jira or Asana, but delivery still becomes debate because the system isn’t modeling capacity at the level you need and how dependencies consume the same people across parallel work.

Backed by public conversations in Reddit’s Jira threads and Atlassian Community around individual vs team-level capacity.

Real comments from teams trying to model capacity.

These are pulled from public Reddit and Atlassian Community threads about Jira capacity planning.

Source: Reddit · Jira capacity thread
“Jira doesn't seem to have capacity tracking capabilities at an individual level.”
Source: Reddit · Jira roadmap
“Resource management: allocate tasks… how much availability does each person have?”
Source: Atlassian Community
“Capacity… in Advanced Roadmaps is only possible on team level, not on individual level.”

A delivery model that treats people-time as the constraint.

Motionode turns scope into a dependency-aware plan, then applies role capacity and member throughput to compute timelines and risk. When scope changes, it recomputes the cascade—because the same people can’t be in two critical paths at once.

  • Bottleneck detection: shows which role/member saturates first and what it delays.
  • Risk intelligence: highlights “date at risk” work items before they hit late-stage crunch.
  • Scenario simulation: add headcount or overtime and see the new projected date and effort.

Atlassian’s own guidance says realistic plans depend on estimation units, dependencies, and scheduling rules. Motionode is essentially that engine, grounded in per-member throughput instead of static guesses.

Dependency-aware delivery model showing bottlenecks and risk

Outputs you can take into a status meeting.

  • Delivery timeline computed from capacity + dependencies.
  • Bottleneck map: what’s blocking what, and by how much.
  • Risk list: top items most likely to slip the date.
  • Scenario comparison: “hold date” vs “slip date” with required hours and headcount.

Exports available for sharing and internal documentation.

Forecast view of delivery risk and timelines

Pricing built for delivery teams.

Pilot (recommended)

  • Per-project pricing (first project free).
  • Includes setup and weekly working sessions.
  • Best for teams who want the model to match how they actually ship.

Self-serve

  • Per-project pricing (first project free).
  • Use placeholder capacity to explore quickly.
  • Upgrade to Pilot when you want org-wide rollout.
See pricing

Risk stays accurate because it learns from your team’s actual pace.

This isn’t a one-time plan. As work moves, Motionode updates throughput per role and member and recomputes delivery risk automatically.

Most “capacity plans” die the moment reality changes. Motionode stays current because the team works from the plan: when steps move, durations complete, or priorities change, the model recalculates bottlenecks and date risk in real time.

Start with placeholder capacity to explore. To get live risk intelligence, the team needs to run work through Motionode.

Team workflow
  1. Work from the pipeline (tickets/steps).
  2. Mark step starts and completions.
  3. Motionode updates pace + delivery risk automatically.

FAQ

Do we need Jira integration?
No. Start by modeling delivery from your scope and team capacity. Export exists if you want it later.
How is “speed” measured?
From actual completion patterns over time (by role and member), then applied to future work.
Is this just AI estimation?
No. AI helps structure scope; the timeline is computed from dependencies and capacity constraints.
Can we run this without real data?
Yes — use placeholder capacity to see the model first. When you’re ready, connect your real team and let Motionode learn from live work.

See your delivery risk in 2 minutes.

Paste scope → set target date + capacity → get a computed risk view (no login).

First project is free (limited scope). No credit card.