What each Avium Signal detects
Avium Signals is the deterministic engine that reads your real data and surfaces what's at risk — every claim grounded in a real signal, never invented. Here's what each one catches.
Stop finding out at sprint review. Avium Signals reads your Jira data — or any work management tool — and forecasts which sprints are about to miss — and why.
Velocity is the metric every VP asks about and no team trusts. Avium Signals tells you when it's actually shifting — and whether the shift is structural or noise.
Half your team is at 80%. Two engineers are at 130%. Your burndown chart can't tell you who.
Half your sprint is fine. A few tickets have been quietly stuck for a week. Avium tells you which ones — by age, with the reason — before standup.
Your sprint ticket is waiting on a ticket that isn't in your sprint. It's not on your board, so nobody's watching it — until the commitment slips. Avium watches it for you.
'We committed to X, we shipped Y' is half the conversation. 'Here's what got added on day 6 and what got dropped on day 8' is the other half. Avium has it.
Your forecast is reading from your data. If your data is broken, the forecast is too. Avium scores the gap.
The percent of your Done column that doesn't stay done. Tells you whether your team is shipping work or shipping work twice.
A ticket takes 8 days to ship. Two of those days are someone working on it. Six are waiting. Avium tells you which is which.
A ticket assigned to one person ships fast. A ticket that's been reassigned three times takes 4× longer and reopens 2× as often. Avium counts every hand-off.
Your Jira workflow on paper has 6 statuses. In practice it has 23 transitions, 4 of them backwards. Avium draws the picture nobody else does.
Some tickets go forward. Some go in circles. Avium tells you which.
Your team isn't slow. Your tickets are sitting somewhere. Avium tells you which somewhere.
"How long does work take here?" should have a real answer, not a shrug. Avium measures lead time from the gate you actually commit at — through to done — across every ticket.
Lead time answers "how long from commit to done." Cycle time answers "how long once we actually start." Avium measures both from your real history — no guessing.