Use Cases
These aren't hypothetical. They're the shapes of agents BeeKeeper was built for — scoped, governed, and connected to the systems where the work actually lives.
A support agent connects to your Zendesk knowledge base, ticket history, and Slack support channel. It deflects routine tickets, drafts replies for the harder ones, and escalates with full context when a human is required.
A new AE joins. The onboarding agent has read your Confluence playbooks, recent Salesforce deals, and product docs. It answers questions about pricing, sequences, and competitive positioning — and hands off to a senior AE the moment the question gets nuanced.
Employees ping the IT agent in Slack — or call the voice line. It answers from your IT runbook, opens Jira tickets for things it can't do directly, and triggers password resets through your IdP via a scoped tool.
A widget on your docs site that answers in your product's voice. It uses your published docs, internal Confluence, and recent GitHub releases — so it knows about features that shipped this morning.
A sales-ops agent receives "what's at risk this quarter?" and orchestrates three sub-agents: contract risk (reads MSAs), renewal forecaster (reads CRM), and upsell scout (reads usage data). Each returns structured findings; the orchestrator writes the summary.
Sales gets a 200-question security questionnaire on Friday afternoon. The agent reads your compliance docs, prior responses, and current control posture — drafts answers with citations, flags anything that needs Security review, and hands the doc back ready for sign-off.
Bring it to a demo. We'll wire up a working version against a sandbox of your data in the call.