Resolve routine customer requests end to end, and give your team the rest with context attached.
An AI agent answers from your help content and the customer's own account, takes actions such as order changes or refunds within set limits, and passes anything outside policy to an agent with the conversation and a suggested next step.
- 01Receive and identify
- 02Classify intent
- 03Answer or act within limits
- 04Hand off with context
- 05Review and update
The workflow
Customer service teams handling email, chat and in-app messages, and the team leads who manage queues, quality and escalations.
- Most tickets are the same dozen questions, answered by hand every day.
- Customers wait in a queue for answers that are already in the help center.
- Agents switch between four tools to check an order before they can reply.
- Answers vary by agent, and policy changes take weeks to reach every reply.
Receive and identify
SystemThe message arrives through chat, email or the help center, and the customer's account and recent orders are looked up.
Classify intent
AIThe agent identifies what the customer wants, whether it is in scope, and any signs of urgency or frustration that should go straight to a person.
Answer or act within limits
AIFor in-scope requests, the agent answers from approved content and account data, or takes an allowed action such as rebooking a delivery or issuing a credit below a set amount.
Hand off with context
PersonOut-of-scope, sensitive or over-limit requests go to a support agent with a summary, the data already checked and a suggested reply.
Review and update
PersonTeam leads review a sample of automated conversations each week and update policies, content and limits based on what they find.
Where people stay in control
Customers can reach a person at any point. Actions above set limits, complaints, account security issues and anything the agent is unsure about go to the team. Leads review a weekly sample of resolved conversations, and every action the agent takes is logged against the ticket.
- Share of conversations resolved without handoff, checked against reopen rate
- Customer satisfaction on automated versus handled conversations
- Time to first response and time to resolution
- Quality score from the weekly review sample
Data and integrations
- Help center articles and internal support policies
- Help desk platform access, such as Zendesk, Intercom or Salesforce Service Cloud
- Order, billing or booking system APIs for lookups and actions
- Past tickets with resolutions for evaluation
Realistic boundaries
- Requests that need judgment, exceptions or empathy beyond policy go to people by design.
- Actions are limited to what the connected systems allow and what you approve; the agent cannot override policy.
- Quality depends on help content being accurate; gaps found in review need an owner to fix them.
How we build it
- AI AgentsAgents that take approved actions across your tools, with permissions, review points and monitoring built in.
- AI ChatbotsText chat assistants for customer support, internal help desks and product experiences, grounded in your knowledge and connected to your systems.
- AI Voice Agents & ReceptionistsPhone agents that answer calls, understand callers in natural speech, book, route and take messages — and transfer to a person when needed.
- AI IntegrationConnect AI models and assistants to your CRM, ERP, databases, knowledge stores and APIs — with identity, logging and fallbacks that production systems need.
- Retail & CommerceCustomer service, catalog operations, demand planning and personalization — connected to the commerce platforms and order systems you already run.
- Travel & HospitalityGuest service across channels and languages, disruption handling, property operations and personalization — connected to reservation and operations systems.
- Technology & SaaSAI features inside your product, developer tooling, support operations and platform engineering — built by a team that ships software, not just prototypes.
- InsuranceClaims intake, underwriting submissions, policy knowledge and fraud signals — AI that prepares the file so adjusters and underwriters decide with the evidence in front of them.
Questions buyers ask
Yes. We recommend stating it clearly at the start of the conversation and making it easy to ask for a person. Being clear about this also sets the right expectations for what the agent can do.
The same policies, data connections and limits can sit behind a voice agent. Voice adds latency and speech-recognition considerations, so we usually start with text channels.
Map this workflow with us.
Tell us about the workflow or product. We reply with questions, a suggested first step and who would work on it.