INTELLIGENT AUTOMATION

Root cause and approved fixes for failed automations

When bots fail, teams sift through job logs, change records, incidents and runbooks to find out why. Wexa reads all of them, names the root cause with evidence, proposes one corrective action and hands it back to the automation platform after a second person approves.

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automations and 18,120 jobs in scope
failed jobs traced to a single field rename
pieces of evidence behind the root cause
approval: requester can never approve

CLIENT: Enterprise automation centre of excellence, with a leading RPA vendor
REGION: Global
WHEN: 2026
ENGAGEMENT: Partner build
WEXA COMPONENTS: Wexa · context graph · knowledge base · 4-agent process flow · four-eyes approval · A2A hand-off

01Case 22

The challenge

A single application change silently breaks many bots
Evidence spread across logs, changes, incidents and runbooks
Fixes applied without review

What Wexa built

Four agents in one flow: failure triage, change correlator, incident matcher, root-cause analyst
Graph of applications, automations, jobs, failures, changes and incidents; runbooks and postmortems in the knowledge base
One proposed corrective action, held for an approver above the requester
Approved action handed to the automation platform; the outcome recorded as a new incident and postmortem for next time

02Case 22

How it runs on Wexa

FigureHow this use case runs on Wexa: client systems connected, ontology discovered, context graph in the Wexa memory layer, agents and process flows, and governance. Highlighted components are central to this use case.

03Case 22

Results

Measure	Before / without Wexa	With Wexa
Hours to triage each failed automation (~6,000 failures a year)	3 hours	0.5 hours
Annual cost of the process	$1.1M	$180K
Time to implement the AI solution	6 months	2 weeks
AI build cost (one-time)	$480K	$15K
AI operating cost per year (models, infrastructure, upkeep, platform)	$312K	$166K
Total AI cost in year 1	$792K	$180K