Use case library

Show me the jobs it can actually handle.

Most people just want to know what it can do, what stays human, and how it is controlled.

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Interactive chooser

What work can it take off your plate?

Pick the area where the busywork is piling up. Get a practical fit score, a simple setup read, and the first employee worth putting in place.

Support Ops AI Employee

Clear routine support work before it reaches the team.

Queue volume is up, first response is slow, and good support people are stuck sorting repeat requests.

AI employee fit score92
Strong first employee
SetupLow-medium
OversightHuman review for exceptions
Time back10-20 hours/week per busy queue
ConfidenceHigh
Work the AI employee can handle
  • Classify tickets by topic, urgency, customer type, and likely owner
  • Draft first replies from approved policy, help docs, and account context
  • Pull order, subscription, or account details into the response
  • Route exceptions with a clean summary for the human owner
  • Create a daily queue report showing repeats, blockers, and misses
What stays human
  • Refund approvals
  • Angry or sensitive customers
  • Policy exceptions
  • New issues with no approved answer
Faster first response
Fewer manual touches
Cleaner escalation notes
Repeat issues visible every week
First KPI to watchFirst-response time + manual touches per ticket
Best first stepStart with one queue category that appears every day.
See this fitExplore this use case

Start with the problem the owner can actually feel.

CapacityBench is easiest to buy when the owner can point at a queue, inbox, report, checklist, or admin loop and say: that work should probably not need another hire.

Buyer

COO / Head of Ops

Reduce repetitive handoffs and keep work moving without adding another coordinator.

Buyer

Support leader

Clear common queue work faster while keeping escalations controlled.

Buyer

RevOps leader

Stop losing leads to slow follow-up and messy CRM records.

Buyer

Finance owner

Cut manual chasing and surface exceptions instead of babysitting routine admin.

The pattern is the same across teams.

AI employees work best where the task is repeated, the inputs are known, the rules can be written down, and a human can own exceptions.

1. IntakeRead the request, record, ticket, email, form, or document.
2. Decide the next stepClassify, route, draft, update, chase, summarize, or escalate.
3. Execute safelyAct inside approved boundaries with review and escalation rules.
4. Report backShow what happened, what failed, and what should improve next week.

Real starting points.

Each use case below is framed around the work absorbed, the budget owner, the outputs, and the line where a human stays in control.

Customer Support

Support inbox AI employee

Queues grow, customers wait, and experienced support people spend their day sorting repetitive requests.

Explore this use case
Budget ownerSupport Director / COO
What it can take over
  • Classify incoming tickets
  • Draft replies from approved policy
  • Pull order/account context
  • Route exceptions
  • Summarize escalations
Typical outputs
  • Cleaner queue
  • Faster first response
  • Fewer repetitive touches
What stays humanRefund decisions, angry customers, policy exceptions, and anything that needs judgment.
First KPI to watchFirst-response time and manual touches per ticket
Not a fit ifEvery ticket is bespoke, emotional, or policy-ambiguous.
Sales & RevOps

Inbound qualification AI employee

Leads arrive, nobody replies fast enough, context is missing, and sales spends time cleaning up instead of selling.

Explore this use case
Budget ownerRevOps / Sales Ops / Founder
What it can take over
  • Respond to inbound interest
  • Ask qualifying questions
  • Enrich lead records
  • Prepare handoff notes
  • Trigger follow-up tasks
Typical outputs
  • Faster speed-to-lead
  • Cleaner CRM
  • Better sales handoffs
What stays humanDiscovery calls, pricing judgment, negotiation, and closing.
First KPI to watchLead response time and qualified handoff rate
Not a fit ifYour qualification rules change daily or nobody owns the sales process.
Finance & Admin

Invoice and admin AI employee

People chase missing details, copy data between systems, and babysit routine admin instead of controlling the business.

Explore this use case
Budget ownerController / Finance Ops / COO
What it can take over
  • Extract invoice/request details
  • Check missing fields
  • Match records
  • Chase approvals
  • Prepare weekly exception list
Typical outputs
  • Fewer admin loops
  • Cleaner records
  • Less back-and-forth
What stays humanApprovals, vendor disputes, unusual exceptions, and cash decisions.
First KPI to watchCycle time per routine request
Not a fit ifThe process is undocumented and every step needs manual interpretation.
Operations

Request intake AI employee

Internal requests arrive through email, Slack, forms, and calls. Work gets routed late or not at all.

Explore this use case
Budget ownerHead of Ops / GM
What it can take over
  • Capture request context
  • Categorize work
  • Create tasks
  • Route to owners
  • Send routine status updates
Typical outputs
  • Cleaner handoffs
  • Less coordination drag
  • Fewer dropped tasks
What stays humanPrioritization, trade-offs, resourcing, and escalations.
First KPI to watchRequest-to-owner assignment time
Not a fit ifThere is no stable owner or team responsible for the workflow.
People Ops

Onboarding and policy AI employee

New hires and employees ask the same questions while HR chases forms, documents, and routine updates.

Explore this use case
Budget ownerHR / People Ops / COO
What it can take over
  • Answer policy-backed questions
  • Collect missing paperwork
  • Update onboarding checklists
  • Schedule routine steps
  • Escalate sensitive issues
Typical outputs
  • Smoother onboarding
  • Less HR repetition
  • Better policy consistency
What stays humanSensitive employee issues, exceptions, performance matters, and policy interpretation.
First KPI to watchOnboarding completion rate and HR manual touches
Not a fit ifPolicies are not documented or legally sensitive issues dominate the queue.
Reporting

Weekly reporting AI employee

Managers need recurring updates, but nobody wants to pull data, chase comments, and turn messy notes into a clean report.

Explore this use case
Budget ownerCOO / Department Lead / Founder
What it can take over
  • Collect weekly inputs
  • Summarize activity
  • Highlight blockers
  • Draft status reports
  • Maintain recurring documentation
Typical outputs
  • Better visibility
  • Less reporting admin
  • Cleaner operating rhythm
What stays humanInterpreting meaning, making calls, and deciding priorities.
First KPI to watchReport production time and blocker visibility
Not a fit ifThe inputs are unavailable, unreliable, or politically sensitive.

Not sure which use case fits?

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