- Get started
- Best practices
- Capabilities
- Automation discovery (Preview)
- Artifact review (Preview)
- Operate
- Troubleshoot
- Skills
- CLI
- Examples
- Examples overview
- Recipe: build an agent
- Recipe: automate with RPA
- Recipe: enter data into a web app
- Recipe: extract data from a desktop app
- Recipe: refactor and test a workflow
- Recipe: a queue-based process with REFramework
- Recipe: build a Maestro Flow
- Recipe: build a Maestro Case
- Recipe: coded app and API workflow
- Recipe: build a coded function
- Recipe: verify a release with Test Manager
- Recipe: extract data from documents with IXP
- Advanced
- Help
Automation discovery capability that mines messaging channels, email, wikis, and business systems for repetitive work and produces a prioritized automation backlog.
Before you build a specific automation, you need to know what to automate. With a coding agent, you point it at your organization's messaging channels, email, wikis, and systems of record; it investigates how people actually work and returns a prioritized backlog of automation opportunities, each backed by evidence rather than opinion.
What it does
The agent mines Slack or Teams channels, email patterns, wikis, CRM/ERP/HRIS systems, and issue trackers for manual work, repeated questions, stalled approvals, and swivel-chair data entry. It looks specifically for:
- Single points of failure — roles that are the sole responder for a process, pseudonymized by default unless you authorize naming individuals.
- Proven replicable models — an automation already working in one team that could extend to others. These are treated as the highest-value finding.
- Strategic gaps — automation opportunities tied to the company's documented priorities (revenue growth, cost reduction, compliance, and similar), drawn from public or internal strategy sources.
It produces a four-tier prioritized report — replicable models first, then single points of failure, then evidenced opportunities, then strategic gaps — with every finding backed by a specific source, metric, and affected role or team. On request, it also sizes the build effort for each opportunity (complexity band, estimated hours, contingency), using effort-estimation references you supply.
Privacy and authorization
Before mining anything, the agent confirms you're authorized to analyze the systems and data involved, avoids private channels, direct messages, and special-category HR data unless you explicitly approve it, and asks about jurisdiction constraints such as GDPR or works-council requirements. Individuals are referred to by role or pseudonym by default.
The skill behind it
This work is powered by the uipath-automation-discovery skill, which mines your systems, analyzes the findings, and hands off each opportunity to the UiPath skill that builds it — RPA, a Maestro Flow, an agent, a human-in-the-loop step, or an integration. You can see it in the Skills catalog.
A typical starting prompt
A first request might look like this:
"Suggest the highest-value processes we could automate."
The agent will ask what systems it can access and how broad a scan you want before it starts mining.
More prompts to try
- Run a deep-dive automation audit across Finance and Support, and flag any single points of failure.
- We already automated invoice matching in Procurement — find out if the same pattern shows up manually elsewhere in the company.
- Size the build effort for the top 5 opportunities in the report.
Go deeper
For where discovered opportunities get tracked and prioritized as a delivery pipeline, see the Automation Hub documentation.