AI Agents for Customer Support

Every support queue has the same shape: a handful of repeat questions, a long tail of edge cases, and a few tickets that genuinely need a human. AI agents for customer support work best when they respect that shape — deflecting the repeat questions with grounded answers, and routing everything else to your team with full context.

Ticket triage that doesn't guess

A Support Ticket Agent reads incoming requests, classifies intent, and decides what happens next — answer directly, pull in a specialist agent, or hand off to a person. Pair it with a dedicated FAQ Agent for the recurring "how do I reset my password" volume, and an Escalation Agent that recognizes frustration, urgency, or policy exceptions before they become complaints. All three come pre-built and are available from the Free plan, so you can start triaging without a procurement cycle. Browse the full set in AI agent templates and adapt them to your ticket categories.

Grounded answers, not confident guesses

The biggest risk in support automation isn't a wrong answer — it's a confident wrong answer sent to a customer. AgentWorks agents answer only from your connected knowledge: upload PDFs, DOCX, TXT, or CSV files, or connect URLs, Notion, and Confluence, and every response is retrieved via semantic search over pgvector and cites the source it came from. If the answer isn't in your knowledge base, the agent says "I don't know" instead of inventing one. That single behavior — cite or decline — is what makes deflection safe enough to trust. Set this up once through knowledge base & RAG and every agent in your workspace draws on it.

PII protection at the gateway

Support tickets carry account numbers, addresses, and order details — data you don't want flowing unfiltered into a third-party model. AgentWorks masks PII at the gateway before any request reaches an LLM, so sensitive fields never leave your environment in the clear. This runs automatically for every agent, every conversation, without extra configuration on your part.

Human escalation, by default

No agent sends a refund, updates a CRM record, or replies on your behalf without a person checking first. Any state-changing action pauses for human approval, and the reviewer sees the full context — the ticket, the retrieved sources, the proposed reply — and can edit it before it goes out. This isn't a fallback for when the AI fails; it's the standard operating mode for anything irreversible. Read more about how this works under human-in-the-loop & compliance.

An audit trail you can actually show

Every interaction — what the customer asked, what was retrieved, what the agent proposed, who approved it — is logged immutably. Combined with per-agent risk classification and EU data residency, this gives support and compliance teams a record they can produce on request, not one they have to reconstruct after the fact. AgentWorks is built EU AI Act-ready: agents are classified by risk, and customers see an AI transparency label ("you are talking to an AI") wherever an agent is answering directly.

Multi-channel, one workspace

Support rarely lives in one inbox. Connect Slack, Microsoft Teams, Gmail, HubSpot, and Zendesk-style workflows through MCP or REST API and webhooks, and let inbound events trigger agent runs automatically — a new ticket, a Slack mention, a form submission. Your team keeps working from the chat workspace, where every agent, escalation, and source citation shows up in one place instead of scattered across tools.

Choosing the right model for the job

Not every ticket needs your most expensive model. AgentWorks runs GPT-5, Claude (Opus, Sonnet, Haiku), Gemini (Pro, Flash), and Mistral Large side by side, and the AUTO router picks the cheapest model capable of handling a given request — switching mid-conversation if a ticket escalates in complexity. For multi-step support workflows — triage, retrieval, drafting, approval — you can chain agents together as multi-agent pipelines instead of building one oversized prompt.

What it costs to get started

You can build and test your first support agents on the Free plan (€0, €5 in credit, 50+ agents, up to 3 integrations, personal knowledge base). Pro (€39/mo plus €10/mo balance) adds custom agents, workflows, and scheduled runs; Team (€49/seat/mo plus €10/mo balance) adds shared chat and shared knowledge across your support team; Enterprise covers advanced agents, self-hosting, SSO, and SLAs. Token usage is billed at cost plus 10% from a prepaid € wallet, so there's no surprise markup. Full breakdown at transparent pricing.

Summary: AI agents for customer support work when they're grounded in your own knowledge, cite their sources, mask PII automatically, and pause for human approval before anything irreversible — all logged in an immutable audit trail. AgentWorks gives you Support Ticket, FAQ, and Escalation agents from the Free plan, connected to your existing channels, with EU AI Act-ready governance built in.

Frequently asked questions

Will the AI agent ever send a reply without a human checking it?

No. Any state-changing action — sending a reply, issuing a refund, updating a CRM record — pauses for human approval. The reviewer sees the full context and can edit the response before it's sent.

How does the agent avoid making up answers?

Every answer is retrieved via semantic search over your connected knowledge base (documents, URLs, Notion, Confluence) and cites its source. If the answer isn't in your knowledge base, the agent says "I don't know" rather than guessing.

Which channels can I connect a support agent to?

Slack, Microsoft Teams, Gmail, HubSpot, and Zendesk-style workflows via MCP or REST API and webhooks, so inbound tickets or messages can trigger an agent run automatically.