Use cases
Concrete examples across teams and industries. AI agents work best for repetitive, clearly defined tasks where data is available and goals are measurable.
Customer Support & Ticket Handling
AI customer support answers common questions during agreed service hours, routes tickets and escalates complex cases. The implementation can include source citations, intent classification and knowledge-gap tracking.
Target agreed from the measured baselineDocument Search & Internal Wiki
AI knowledge assistant indexes all internal documents (handbooks, policies, technical documentation) and answers questions with source citations. Employees find information in seconds instead of searching for hours. Onboarding speeds up significantly.
Visible sources and access controlsIT Operations & Incident Response
AI assistant handles internal IT requests (e.g., password reset, VPN instructions, software installation), escalates serious incidents, and tracks status. Integrates with AD, ticketing systems, and monitoring. Saves IT team time from routine questions.
Time savings measured during the pilotScheduling & Calendar Management
AI agent handles bookings, checks availability from calendar, sends reminders, and reschedules meetings as needed. Works in multiple languages and integrates with Google Calendar, Outlook, or other calendar systems. Reduces back-and-forth emails.
Real-time availabilityReporting & Data Analysis
AI agents collect data from various sources, clean it, merge it, and generate reports automatically. Dashboards update in real-time. Teams can ask in natural language (e.g., "What was Q4 sales?") and get an immediate answer with visualizations.
Speed and quality measured during the pilotSales Lead Qualification & Follow-up
AI agent qualifies leads by asking the right questions, prioritizes them based on scoring, and schedules meetings automatically. Integrates with CRM and updates lead status in real-time. Reduces manual work and improves conversion.
3x more conversionsIndustries
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