Customer support automation
The problem: repetitive tickets and questions consume a disproportionate share of your support team's time.
The result: an AI assistant resolves routine requests directly and routes anything ambiguous or sensitive to a person, with full context attached.
Email & inbox automation
The problem: shared inboxes fill faster than anyone can triage, and important messages get buried.
The result: incoming mail is classified, prioritized, and drafted for reply automatically, with routine messages handled end to end.
Document & data processing
The problem: contracts, invoices, and forms still get read and re-keyed by hand into other systems.
The result: documents are read, structured, validated, and pushed into the right system automatically, with exceptions flagged for review.
Internal knowledge assistants
The problem: answers to common internal questions live scattered across docs, wikis, and people's heads.
The result: an internal assistant answers from your actual policies and documentation, with sources cited so people can verify.
Lead qualification
The problem: inbound leads sit unqualified while sales spends time on prospects that were never a fit.
The result: incoming leads are scored and enriched automatically, and qualified ones are routed to the right rep with context.
CRM automation
The problem: reps spend hours a week on manual data entry instead of selling.
The result: calls, emails, and meetings are logged and summarized in your CRM automatically, keeping records current without the busywork.
Scheduling & task coordination
The problem: coordinating meetings and handoffs across teams and time zones eats up time that should go to the work itself.
The result: an assistant proposes times, books meetings, and tracks handoffs across your calendar and task tools automatically.