Customer Service AI OS

Most service platforms treat every conversation as a self-contained event. What the customer already told you, how an agent handled a similar case, and the policies that constrain a valid answer all scatter the moment the ticket closes. The real cost is not the individual reply — it is rebuilding the same understanding over and over.

• Enterprises operating service across multiple brands or business units
• Operations teams with high interaction volume and fast-changing knowledge
• Regulated industries that require audit trails and access control

1. 01 Consolidate interaction history into customer memory that can be reused
2. 02 Ground AI responses in a managed knowledge base and capture gaps as they surface
3. 03 Constrain what AI is allowed to decide through explicit policy gates
4. 04 Hand off to a human agent when judgement is required

• Organizations, members and role-based permissions
• Brand workspaces
• Customer identity, conversations and customer memory
• Cases and tickets
• Knowledge base
• AI responses and agent copilot
• Knowledge gap capture
• Policy gates
• AI governance and audit direction
• Human handoff
• LINE OA and web chat
• Multi-tenancy and deployment model design

This product is in development and early access. The list above describes product direction that we are willing to state publicly — not a claim that every item is production-ready. Feature-level maturity is verified individually, and we do not use overall product direction to imply that any single capability is ready.

• ✕ We do not claim every item above is production-ready
• ✕ We do not claim any security certification
• ✕ We do not disclose customer names or adoption numbers