Cycle time becomes measurable by workflow, role, source system, and agent action.

Use-case library
Choose the first workflow an enterprise agent should own.
Start with work that repeats, crosses systems, has a named owner, and can be measured. Then define the read scope, proposed writes, approval path, and failure behavior.
Compare workflows by boundary, control, and result.
The library shows where S/Runtime fits, how governance applies, and which outcome metrics prove value. Percentage ranges are illustrative 30-day pilot targets, not guaranteed results.
Recruiting agent
Unify role criteria and permitted candidate context so talent teams can organize review and coordinate interviews while consequential decisions remain behind human approval.
Enterprise search and answers
Give employees a single place to ask questions across documents, tickets, records, policies, and data while preserving source permissions and citations.
Governed agent workflows
Move from chat responses to approved work execution with context packs, tool allowlists, policy filters, approvals, and full run traces.
Customer operations
Unify account, order, policy, support, contract, usage, and billing context so customer teams and agents can act faster without exposing sensitive data.
IT service and operations
Connect tickets, runbooks, monitoring, deployments, ownership, assets, and communications so IT and engineering agents can triage safely.
Revenue intelligence
Connect CRM, calls, emails, support, usage, contracts, product notes, and risk signals into governed account intelligence.
Procurement and vendor risk
Bring supplier history, contracts, security reviews, purchase orders, quality events, and business owners into a governed review workflow.
Compliance and audit readiness
Connect controls, owners, systems, policies, incidents, approvals, and agent activity so regulated teams can answer evidence requests faster.
Knowledge and policy operations
Make policies, SOPs, playbooks, training, ownership, and institutional memory accessible to people and agents with freshness and authority controls.
Set the baseline before the pilot starts.
Each use case ties to a practical before-and-after metric so the buyer sees operational value, not just an AI demo.
Search effort becomes measurable by workflow, role, source system, and agent action.
Exception rate becomes measurable by workflow, role, source system, and agent action.
Architecture session
Bring one consequential workflow. Leave with a governed agent blueprint.
We will map the context, systems, decisions, controls, actions, and success measures together.