Resolve support inquiries from knowledge base
Power your knowledge base chatbot with an AI customer service agent that searches internal documentation, adds web research when the docs fall short, and returns consistent answers without escalation.
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When a customer sends a question through [chatbot/live chat platform], an AI agent determines how to resolve it, querying [internal knowledge base] to find relevant documentation, and deciding when the available knowledge is insufficient and a search via [web search tool/API] is needed to enrich its response. The agent adapts its research approach based on the nature and complexity of each inquiry rather than following a fixed lookup sequence, then replies to the customer in [chatbot/live chat platform].
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Problem
Customer support teams spend significant time manually searching internal knowledge bases to answer repetitive inquiries. When documentation is incomplete or outdated, agents must perform their own research or escalate tickets unnecessarily, leading to slow response times and inconsistent answers across the team.
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Solution
When a customer sends a question through the support chatbot, an AI agent determines how to resolve it, querying the internal knowledge base to find relevant documentation, and deciding when the available knowledge is insufficient and a web search is needed to enrich its response. The agent adapts its research approach based on the nature and complexity of each inquiry rather than following a fixed lookup sequence, then replies to the customer in the chat.
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Impact
Customers get dependable answers without waiting on a human, and support staff spend their time on complex cases instead of digging through documentation.
Benefits
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Faster inquiry resolution
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Reduced manual research
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Consistent accurate responses
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Lower escalation rates
Who is this for?
Success stories
Adapt at speed with visual-first automation and AI
Make drives efficiencies, solves problems, and speeds innovation by breaking down silos across your business.
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When a new ticket arrives from any channel, the automation captures the ticket content and customer context, uses AI to categorize the issue type and complexity level, routes the ticket to the appropriate team or agent using predefined assignment rules, then uses AI to analyze the ticket against the knowledge base and previous resolutions to suggest the most relevant articles or solutions that match the issue, delivering these suggestions directly to the assigned agent.
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Collect satisfaction feedback on resolved tickets
When a support ticket's status changes to resolved in the helpdesk, the automation reads the customer's name, email, ticket ID, and assigned support agent, then emails the customer a satisfaction survey with a link tied to that ticket. It records the survey send on the ticket and adds a row to a feedback tracking sheet with the ticket details and send date.