Use Cases
Production AI agents across real workflows
Start with one workflow that matters. Expand across teams as agents prove their value with full observability and governance.
Sales & CRM Operations
Turn CRM from a manual system of record into an intelligent execution layer.
- Create and update Salesforce leads
- Enrich account information
- Summarize account history
- Prepare meeting briefs
- Update CRM fields after calls
- Identify pipeline risks
- Automate follow-ups
- Detect stale opportunities
Customer Support
Resolve faster while keeping humans in control of complex cases.
- Classify tickets
- Suggest responses
- Escalate complex cases
- Update support systems
- Summarize customer history
- Trigger internal workflows
- Detect SLA risks
- Create knowledge articles
Engineering Productivity
Specialized agents for the inner-loop and developer workflows.
- PR review agent
- Code quality checks
- Jira ticket summarization
- Release readiness checks
- Incident response assistant
- On-call investigation
- GitHub issue triage
- Engineering status updates
On-Call & Incident Management
Reduce investigation time without removing human judgment from the loop.
- Read alerts
- Check logs
- Query observability tools
- Summarize incident context
- Suggest next actions
- Create incident reports
- Notify stakeholders
- Track resolution steps
Project Management & Scrum
Keep teams aligned with high-signal updates and clean backlogs.
- Scrum master agent
- Sprint summary generation
- Jira hygiene checks
- Blocker identification
- Standup summaries
- Risk detection
- Release notes
- Stakeholder updates
Real Estate Sales
An AI sales operations layer for high-velocity property teams.
- Lead capture from web/WhatsApp
- Create Salesforce leads
- Qualify buyers
- Route leads to sales teams
- Project Q&A
- Schedule site visits
- Follow up with prospects
- Sync data with CRM
Finance & Accounting
Support accounting workflows with structured agent execution.
- Invoice analysis
- Receipt classification
- Form preparation
- Compliance checklist automation
- VAT reconciliation support
- Exception flagging
- Reviewer queues
Custom Enterprise Workflows
Bespoke agents wired to your internal systems and policies.
- Internal approvals
- Cross-system orchestration
- Domain-specific workflows
- Bring-your-own tools
- Bring-your-own model
- Private deployment options
FAQ
Frequently asked questions
How teams scope, pick, and ship their first production AI agent.
- What are the most common AI agent use cases for business?
- The workflows teams automate first are support ticket triage, CRM data hygiene and lead enrichment, pull request review, on-call alert enrichment, sprint reporting, and finance reconciliation — read-heavy work with targeted writes, where an agent saves hours daily and every action can be audited.
- How do I pick the first workflow to automate with an AI agent?
- Pick a workflow that is frequent, rule-describable, and painful — and where a mistake is recoverable. Support triage and CRM updates fit well because approval gates catch errors before they reach customers or systems of record.
- How long does it take to get a first agent into production?
- A first pilot typically ships in days, not months: configure the agent in the visual builder, test it in sandbox with full traces, add approval gates for risky actions, then promote to production once the team trusts its output.
- Do these agents replace people?
- No — they remove the repetitive layer of the work. Every reference design here keeps humans in the loop for judgment calls: approvals before external actions, escalation paths for complex cases, and review queues for exceptions.