Deflection that does not damage the relationship
Routine questions get a specific, correct answer drawn from your own articles rather than a search page or a bot that loops the customer back to the start.
AI Customer Service Agents
AI Agents for Customer Service Teams
Resolve the repetitive half of your ticket volume across email, chat, and portal, route the rest with the context already gathered, and keep every answer traceable to an approved article.
1Agent for deflection, triage, and resolution
4Channels served from one knowledge base
CitedEvery answer traced to an approved article
On-premCustomer conversations stay in your estate
Enterprise controls
Answers constrained to approved knowledge contentConfidence threshold below which it routes to a humanRefunds and account changes require explicit approvalCustomer conversation data stays on your infrastructure
Category overview
Customer service agents for queues that grow faster than headcount
Most support volume is a small number of questions asked in a large number of ways. VDF customer service agents resolve that repeating share directly from your documented knowledge, and make the remainder cheaper by arriving at a human already summarised, categorised, and matched to prior cases.
One behaviour across every channel
Email, live chat, the self-service portal, and messaging get the same grounded answer, so the response no longer depends on which door the customer used.
Escalations that arrive ready to work
When a case needs a person, it lands with the history summarised, the account context pulled, the category set, and the likely cause proposed.
Customer Service Agents
Explore the customer service agents catalog
Each agent has its own SEO page with use cases, governance notes, expected outputs, FAQs, and related tools.
Operating model
A support workflow from inbound message to closed ticket
Support agents are only as good as the knowledge behind them and the systems they can act in. VDF grounds them in your help centre and ticket history, then gives governed write access to the tools where resolution actually happens.
Ingest across channels
Messages from email, chat, the portal, and connected messaging platforms are normalised into one queue with the customer record attached.
Classify and retrieve
Intent, product area, urgency, and sentiment are determined, then candidate answers are retrieved from help articles and resolved historical tickets.
Resolve or route
High-confidence cases are answered and closed with the source article cited; the rest are routed to the right queue with a diagnosis attached.
Learn from the gaps
Questions with no supporting article are collected as knowledge-base gaps so the documentation improves where deflection is failing.
Governance & deployment
Support AI that will not invent a policy
A support agent speaks to customers in your name, which makes a confident wrong answer more expensive than no answer. VDF constrains responses to approved content, records the article behind each reply, and keeps refunds, credits, and account changes behind a person.
Answers constrained to approved knowledge contentConfidence threshold below which it routes to a humanRefunds and account changes require explicit approvalCustomer conversation data stays on your infrastructure
FAQ
Questions about customer service agents
What are AI customer service agents?
AI customer service agents are specialized agents that read inbound customer messages, answer the ones your documentation already covers, and route the rest with context, working across email, chat, and portal.
How much ticket volume can realistically be deflected?
It depends almost entirely on documentation coverage rather than model quality — teams with a maintained help centre typically deflect a substantial share of tier-one contacts, and the gap report shows where the remainder is going.
What stops it giving customers a wrong answer?
Responses are generated only from retrieved approved content with the source recorded, and any case scoring below the configured confidence threshold is handed to a person instead of answered.
Keep exploring
Related agent categories and resources
Put customer service agents to work on your own infrastructure
See these agents applied to your operations — governed, on-premise, and orchestrated together.