Autopilot: AI Resolution Loop That Improves Itself

Autopilot continuously reads your real cases and chat transcripts and surfaces two kinds of gaps: workflow gaps, where customers ask something your AI has no defined procedure for, and knowledge gaps, where an intent has no supporting article. Each gap is ranked by the number of tickets behind it, so your team always fixes the highest-impact issue first.

Most tools hand you a report and leave the work to you. Autopilot closes the loop. For every gap it finds, it drafts the fix automatically: an AI-recommended Smart Operating Procedure for workflow gaps, and an AutoKB knowledge article for knowledge gaps.

Two fix types means full coverage, both "we have no article" and "we have no defined way to handle this." Every draft waits for your approval before it ships, so you stay in control while the manual backlog disappears.

Before anything reaches a customer, the Chatbot Playground replays each new procedure or article against simulated conversations. Reviewers see the improved answer side by side with the old one and approve with confidence. No guessing, no risk to live traffic, no surprises after launch.

Approved fixes flip from recommended to live and deploy across every channel your customers use. Impact analytics measures the result, deflection, resolution rate, and escalations avoided, then feeds the next cycle. The busier your queue, the faster Autopilot finds and closes its own gaps, so your AI keeps getting better instead of plateauing.