Make software delivery predictable.
Prove it to leadership.

Nave is a flow analytics platform that helps you find where delivery is slowing down, forecast when work will be done, and show how delivery changes over time.

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Detected by natural process limits

Nave Process Improvement for the Payments API team: cycle time is unstable at 28 days, above its natural process limits

AI Investigator Urgent

18 items are stuck in Ready for SIT — a downstream dependency or capacity constraint has collapsed flow

Process Improvement

Know when to act, and what happened next.

Delivery metrics move all the time. Not every change means something needs fixing. Nave helps you separate meaningful signals from normal variation, investigate what is driving them, make a targeted change, and use the data to see what happened next.

Detect

Natural process limits determine whether a change in your delivery metrics is a real signal or normal variation. No AI decides what counts as a signal.

Nave Process Improvement cards for the Payments API team: Cycle Time unstable, above its natural process limits, next to Throughput stable, within them — The signal comes from your data, not an AI interpretation. Natural process limits are calculated from your delivery history.

Investigate

Nave’s AI investigator does the investigation for you. It reads your metrics, identifies the stage and the work items behind the problem, shows you the evidence, and gives you the one thing to act on.

The numbers are computed, not generated. The AI only reads them, so swap the model and the numbers don’t change.

Nave AI Investigator evidence: Ready for SIT holds 18 items against a period average of 3.86, its top 5 items have spent 18 to 20 days there, arrivals exceed throughput by 30%, and SIT processes only 0.45 items a day

Intervene

Use the evidence to choose a targeted intervention, instead of changing the whole process because a metric moved up or down.

Urgent

18 items are stuck in Ready for SIT — a downstream dependency or capacity constraint has collapsed flow

Next steps

Immediately investigate what limits SIT intake — is it environment availability, test team capacity, or a batching policy? The answer determines the fix.
If SIT capacity cannot be increased short-term, throttle upstream: reduce new work entering In Development until the Ready for SIT queue drains below 5 items, restoring flow balance.

Measure

See what happens after the intervention. When a shift holds, Nave recalculates the natural process limits around the new level, showing whether the process has stabilized somewhere different.

Nave value stream dashboard for Digital Payments: cycle time at the 85th percentile for 7 to 20 September 2026 is 17 days for Payments API, Payments Mobile and Payments Web, down 19% to 45% against the earlier periods

Continuous Forecasting

Know what you can commit to.

Stop turning estimates into promises. Nave forecasts from your team’s actual throughput to show what you can realistically deliver and by when.

Nave Monte Carlo delivery date forecast for 42 items, based on the Payments API team's throughput from 3 August to 25 September 2026: 50%, 85% and 95% confidence lines; 85% of simulated outcomes finish in early December 2026

How much can we deliver by December 1?

See the probability of delivering different amounts of work.

When will these 42 items be done?

See the dates associated with different confidence levels.

No story points. No estimates.

The forecast comes from how your team actually delivers.

Executive visibility

Show leadership what’s actually changing.

Leadership needs to know whether delivery is becoming more predictable, where performance is improving, and where attention is needed.

Nave portfolio view for Retail Banking: throughput and work in progress age trends from July to September 2026, comparing the Digital Payments and Mobile Banking services; Digital Payments peaks in August and then drops

Compare performance over time Show whether delivery is improving across 1, 3 and 6-month periods.
See where attention is needed Use consistent thresholds to identify which teams and services need investigation.
Move from the organization to the evidence Start with the executive view, then drill into the underlying delivery data when someone asks why.