Support teams want AI to draft replies, summarize threads, and suggest next actions. Leadership wants to know that customer PII isn’t leaking into provider training sets, that every AI action is attributable, and that cost doesn’t spiral out of control.
SchneeAI gives you both. The Gateway routes support requests through the right model for the workload. PII scanning runs before content leaves your perimeter, masking or blocking sensitive fields per policy. The Vault keeps an encrypted record of every prompt and response, with retention controls that match your DPA. And structured audit events tie every AI action back to the agent, tenant, and ticket that produced it.
What you ship
- Reply suggestions — drafts grounded in the conversation, sent back to the agent for review before any customer sees them.
- Ticket summarization — structured summaries written into your help desk, with the model call recorded for audit.
- Triage and routing — classify intent and priority at ingestion, with budget controls so spend stays predictable.
What SchneeAI handles
| Concern | Platform support |
|---|---|
| PII in prompts and responses | 17 categories scanned pre-call; flag, mask, or block per policy |
| Audit trail | Structured events for every call — agent, tenant, ticket, model, cost |
| Cost control | Budget counters per team, feature, or tenant with threshold actions |
| Provider failover | Routing strategies across OpenAI, Anthropic, Gemini, and Groq |
| Raw retention | Encrypted Vault with legal hold and configurable retention windows |
| Tenant isolation | Per-tenant scope enforced across cache, logs, and storage |
How it fits
A support ticket arrives. Your backend calls the Gateway with a registered prompt and the thread context. SchneeAI resolves the active prompt version, applies the tenant’s routing and limit policies, scans the rendered prompt for PII, calls the provider, records the structured usage and raw payload to the Vault, and returns the response. Your agent reviews the draft, edits, and sends. Every step is an audit event.
That’s the difference between bolting AI onto a support tool and operating it.