Customer service agents for phone and chat
My card was declined in Madrid. Can you fix it before my flight?
Found it: a travel block on your card ending 4417. I have lifted it for Spain until your return on October 14.
Perfect, thank you.
In short
A customer service agent answers inbound phone calls and chat messages, looks up the customer's account, order or policy in your systems, and resolves routine requests inside the rules you set. Phone lines are answered by Voice Agents on the numbers you already own, with every call recorded, transcribed and measured turn by turn. When a request needs judgment, chats hand off to a person with the transcript and calls transfer to your team, and every version is tested against simulated conversations before it ships.
The problem
Support and care teams answer the same requests all day, on the phone and in chat: balance checks, order status, password resets, plan changes, claim updates. Phone queues spike at peak hours, menu-based IVR sends callers in circles, answers vary from one person to the next, and a customer who gets transferred often has to repeat everything. A rules engine alone cannot hold a natural conversation, and a model alone cannot be trusted to act on an account without a rule to check first.
What it moves
- Average handle time
- How long a routine request takes from open to resolution.
- First-contact resolution
- The share of requests the agent resolves without a transfer or callback.
- Escalation rate
- How often a conversation needs a person, and why.
- Customer satisfaction
- Post-conversation ratings, tracked by channel and request type.
How the agent works
Step 1
Call or chat opens
A customer calls a number you already own and a voice agent answers over SIP, or opens chat on your site or app. The agent starts from its instructions and decision tree.
Step 2
Understand and verify
The agent works out what the customer needs from each turn, transcribed live on calls, asks a clarifying question when the request is unclear, and verifies the customer against your records where your policy requires it.
Step 3
Look up and act
It looks up the account, order or policy through HTTP tools or MCP servers and answers from the live record, or performs an allowed action, such as resetting a password or updating a plan.
- Human review
Step 4
Hand off with context
Disputes, complaints, anything outside its rules, or a customer who asks for a person go to a person: a phone transfer on calls, a handoff to your support team in chat. The transcript stays in the trace.
Step 5
Record and measure
Calls can be recorded with their transcript and per-turn latency, and every chat is traced, so a supervisor can review exactly what the agent said and did.
Step 6
Test before it ships
Each new version runs against simulated callers and a dataset of real conversations, scored by an LLM judge, before it reaches customers.
Controls
Deploy on Dynamiq Cloud, or self-host in your own AWS, Azure, GCP, IBM Cloud, OpenShift or Kubernetes environment. Phone numbers stay with your carrier and connect over SIP from Twilio, Telnyx or your own trunk, and chat deploys as a widget or through the Runs API. Our engineers configure the decision tree, tools and transfer destinations with your team and run simulations before the agent takes real conversations.
- Guardrails on chat input
- Chat messages are screened for PII and prompt injection before they reach the model, and flagged messages route to a refusal or a person.
- Escalation as a gate
- Disputes, account changes and anything the agent is unsure of are routed to a person rather than resolved automatically.
- Inbound only
- Voice Agents answer inbound calls on numbers you own. There is no outbound dialer, so every conversation starts with the customer.
- Scoped access
- Access keys can be scoped to one project and set to expire, so a leaked key exposes only that deployment.
- Full audit trail
- Every run is traced and replayable, with the recording or transcript, every lookup and every tool call attached.
Systems it connects to
- Phone numbers you own, over SIP (Twilio, Telnyx or your own carrier)
- Web and app chat, and browser voice over WebRTC
- CRM (Salesforce, HubSpot)
- Helpdesk and ticketing (Zendesk, Jira Service Management)
- Slack and Microsoft Teams for escalation
- Account and billing systems, over API
- Policy and product knowledge (Confluence, Notion, Google Drive, SharePoint)
- MCP servers for internal tools
Built with
- Voice AgentsVoice Agents answer calls on the phone, the web or your own backend, reason with an LLM, and speak back, with every turn measured.
- AI CoworkerHand it a task in plain language. It plans the work, browses, runs code in its own cloud sandbox and uses the apps you connect.
- Agent BuilderDesign an agent on a visual canvas or in the open-source Python SDK. Both compile to the same engine, so what you build ships either way.
- EvalsScore an agent on a dataset before you ship, then keep scoring a sample of its live traffic after you deploy.
- IntegrationsConnect a workflow to 2,100+ app integrations, or point it at your own databases, warehouses and MCP servers.
Industries
- Financial servicesBack-office automation, customer service by phone and chat, and KYC and AML work, on one governed platform your compliance team can audit.
- InsuranceAnswer policyholders by phone and chat, prepare claims and underwriting files, and keep an adjuster or underwriter approving every decision.
- TelecommunicationsAnswer subscriber calls and chats in their own language, reconcile billing, and give support and network teams answers with a citation attached.
- HealthcarePatient intake, referral and document review, and clinical knowledge assistants, with PII and prompt injection screened before a model reads anything.
- Government and public sectorCitizen services, benefits and permit review, and program reporting, with a person in the loop and your agency in control of the infrastructure.
Questions and answers
Can an AI agent answer our customer service calls and chats?
Yes. Voice Agents answer inbound calls on the numbers you already own, and a deployed App or AI Coworker answers chat. Both share the same knowledge base and backend tools.
What happens when the agent cannot help?
It hands the conversation to a person through a phone transfer on calls, or a paused run a support engineer answers in chat, and the transcript stays in the trace.
Can it call our own systems?
Yes, through HTTP tools, MCP servers or direct API calls, so it can look up an account or perform an action rather than just answer questions.
Does Dynamiq support outbound calling?
No. Voice Agents handle inbound calls only.
How is the agent tested before customers use it?
Voice agents run against simulated callers scored by an LLM judge, and every version is scored against a dataset of real conversations before it ships, so a change is measured rather than guessed.
How fast does the voice agent respond?
Every call shows per-turn latency by stage, transcription, end-of-turn detection, model time to first token and speech synthesis, so you can tune the slowest stage. Speech-to-text models with native end-of-turn detection remove a stage entirely.
See this agent on your data.
Talk to our team. We will walk through how it works in your environment, with your systems.