Navigara
All Organizations

UiPath — Engineering Performance

UiPathEngineering capacity
Navigara
+4Eff. engineering capacity added

32 engineers now deliver what 36 would have in Apr 2025.

Effective engineersReal engineers
Apr 2025Dec 2025Sep 2026
Where the work wentBiggest shift: Tests up 8 points
30%
Features
7%
Maint.
42%
Tests
10%
Docs
11%
Fixes

Performance snapshot

Today's rolling 90-day reading for UiPath, compared with the start of the series. Pick a window to move that comparison point.

Avg. perf / dev / mo

−64.1%

2.90 → 1.04 ETV

Active engineers

+3100.0%

1.0 → 32.0

Features

−35.0pp

64.5% → 29.5%

vs. 500 OSS index

0.33x

3.2x → 0.33x · −67% below

Engineering capacity

Effective engineers behind UiPath, against its pre-AI baseline. Each subject has its own: UiPath's is 0.92 ETV / dev / mo, its first reading in April 2025. Per-engineer ETV divided by that gives a capacity multiple, and that multiple applied to the engineers active in the trailing 90 days turns it into engineer-equivalents. The line is the real headcount, so the gap between line and area is what the leverage is worth. Because each baseline is its own, every subject opens at 1.0x on its first day: multiples measure improvement and are not comparable between subjects.

Effective engineers
36engineer-equivalents
+4 engineers above real headcount
Real engineers
32engineers
active in the trailing 90 days
Capacity vs pre-AI
1.1x
per engineer, vs 0.92 pre-AI

UiPath vs. 500 OSS Performance Index

Per-engineer ETV for UiPath against the pooled 500 OSS Performance Index. Both lines are 90-day rolling averages scaled to a 30-day month, so they share one axis and can be read against each other at any point. Pick a window to zoom the chart to it. Latest reading: UiPath is 67% below the index (1.04 vs 3.11 ETV/dev/mo). At the start of the tracked period the gap was 216% above.

UiPath
1.04ETV / dev / mo
+0.03 (+3.0%) past 90d
500 OSS Performance Index
3.11ETV / dev / mo
+0.93 (+42.7%) past 90d

Behind the numbers

Aug

Written summary of the work completed each month.

During the 2026-08 period, the team recorded steady delivery with 214 commits, focused heavily on design system standardizations in apollo-wind and apollo-react alongside SDK maintenance. Key efforts included standardizing form validation semantics, accessibility (ARIA) compliance, and Storybook layout patterns. Total output reached 35 across tracked categories, remaining in line with the recent run rate compared to the 5-month average.

Highlights

Observations

Based on 214 commits19.2 ETVUpdated Sep 8, 2026, 4:01 PM

Performance Composition

Each month's output split by type of work: Features (new value), Maintenance (sustaining systems), Tests, Docs, and Fixes (rework). The yellow line is output per engineer, so when it rises each engineer is delivering more, whatever the team size did. Unit: Engineering Throughput Value (ETV).

Cost per Performance Unit

+178%

If performance per engineer dropped 64%, each unit of engineering performance now costs approximately 178% more than at the baseline 90-day window (ending 2025-04-01). Treat this as a direction, not a price: the exact figure depends on fully-loaded engineer cost, but which way it moved is not in doubt.

Effective Capacity Lost

−21 engineers

At today's productivity, the current 32-person team delivers the performance equivalent of 11 engineers at the baseline 90-day rolling window (ending 2025-04-01). Per-engineer productivity has dipped below the baseline, leaving the team roughly 21 engineers behind that pace.

CapEx vs OpEx

Each month's work split two ways. CapEx (capitalizable investment) is the work that builds the asset: Features, plus the Tests that prove it works and the Docs that explain it. OpEx (operating expense) is keeping it running: Maintenance and Fixes. The yellow line is the CapEx share, so a rising line means more of the month went into building new rather than sustaining what exists. Unit: Engineering Throughput Value (ETV).

Hours per Repository

Trailing 90-day window (64 working days). Org-level capacity is allocated to each repo by its share of org performance, then split CapEx / OpEx by that repo's own Features + Tests + Docs vs Maintenance + Fixes mix.

uipath-integrations-python99.2%0.8%
skills80.6%19.4%
uipath-langchain-python79.6%20.4%
uipath-python79.3%20.7%
apollo-ui76.5%23.5%
Total81.4%18.6%

Feature Contribution

Who shipped each month's new feature work, as a share of that month's total. Bands of similar width mean new value is coming from across the team; one band that stays wide means most of it rests on the same person. Named engineers shipped the most Features over the period. Everyone else is grouped as Others.

Quarterly Summary

Engineers and the Features / Maintenance / Tests / Docs / Fixes mix for each quarter. Cost / Perf Unit is what one unit of performance costs against Q2'25. Eff. Capacity Added is measured against this org's own pre-AI baseline instead, its first reading in the index, so it agrees with the capacity tile and chart above.

Quarter
Q2'2570%+3 engineers
41% Features
Q3'2515+33%0 engineers
57% Features
+61%
Q4'2527−3%+11 engineers
41% Features
+145%
Q1'2635+18%+6 engineers
33% Features
+7%
Q2'2634+17%+6 engineers
32% Features
−2%