AI customer support grounded in how your business works
A support agent should know the product and policy, but also the customer's history, previous promises and the edge cases that require a person.
Beyond a support chatbot
A basic chatbot matches a question to help-center content. A company-aware support agent retrieves relevant documents, conversation history and operating rules to prepare a response for the specific situation.
What it can help with
- Draft answers to product and account questions.
- Surface the correct policy or troubleshooting document.
- Recognize previous promises and avoid contradictory replies.
- Suggest an appropriate resolution within defined boundaries.
- Escalate uncertainty, risk or exceptions to a person.
Knowledge quality determines answer quality
Support AI cannot repair conflicting policies by guessing. Current sources need clear ownership, and contradictions should be placed in a review queue. A company AI knowledge base should preserve sources and distinguish approved rules from informal examples.
Use draft-first deployment
Start by preparing replies for agents or founders to review. Measure factual accuracy, escalation quality and correction patterns—not just response speed. Only expand automation when a narrow class of requests is reliably bounded.
Preserve customer trust
Customers should not have to repeat context that the company already holds, but access must remain permissioned. Permanera is designed around explicitly connected data, visible assumptions, deletable workspace information and no training of shared models on workspace data.