Support
Deflect the questions that never needed a person
Support automation is judged on deflection rate, which is the wrong measure. A deflected customer who did not get their answer is a worse outcome than a ticket.
Quick answer
What can AI customer support handle?
AI customer support handles documented, repetitive questions — order status, delivery times, returns policy, account and billing basics, how-to questions covered by existing documentation. It escalates anything involving a decision, a complaint, an exception or information it cannot verify, passing the conversation context to a person.
The problem
What this actually fixes
The same questions are answered dozens of times a week.
Support is only staffed during working hours and customers are not.
Response times are slow because volume exceeds capacity.
Escalated conversations arrive without context, so customers repeat themselves.
Documentation exists and customers cannot find the answer in it.
Your team spends time on order status instead of on genuine problems.
Scope
What's included
Every engagement is scoped to what you actually need. This is the full deliverable list.
Deliverable 01
Knowledge base grounding
Answers drawn from your documentation, with explicit limits on what may be stated when the answer is not there.
Deliverable 02
Order and account lookups
Live data retrieved during the conversation, so status questions get real answers rather than a link.
Deliverable 03
Escalation with context
Handoff carrying the full conversation, so the customer never starts again and your agent begins informed.
Deliverable 04
Escalation triggers
Explicit rules for what must reach a person — complaints, refunds, exceptions, anything uncertain.
Deliverable 05
Multi-channel coverage
Web chat, WhatsApp and email handled by the same agent against the same knowledge base.
Deliverable 06
Gap reporting
Questions the agent could not answer, surfaced as documentation to write rather than lost.
How it works
From first call to running system
- Step
Analyse ticket history
What is actually asked and how often. Deflection targets follow the data rather than assumption.
- Step
Define the boundary
What the agent answers and what it must escalate, decided before build.
- Step
Build and connect
Agent grounded in documentation and wired to order and account data.
- Step
Review and expand
Transcripts reviewed, documentation gaps filled, scope widened carefully.
Measure resolution, not deflection
The metric a support automation vendor will show you is deflection rate. It is easy to move and it can go up while your support gets worse.
An agent that confidently answers a question wrongly deflects the ticket. So does one that frustrates a customer into giving up. Both look like success on that dashboard.
The measures worth tracking are resolution rate — did the customer’s problem actually get solved — and what happens after an escalation. If escalated conversations arrive with full context and your team resolves them faster than before, the automation is working. If deflection is high and your reviews are getting worse, it is not, regardless of the number.
Stack
What this connects to
- OpenAILanguage models for qualification, summarisation and reply drafting.
- GoHighLevelCRM, pipelines, funnels, calendars and workflows — the system of record.
- WhatsApp BusinessTwo-way messaging on the channel much of the world actually uses.
- StripePayments, subscriptions and SaaS-mode billing.
- Webhooks & REST APIsCustom integrations for anything without a native connector.
Questions
AI Customer Support — common questions
What percentage of tickets can be deflected?
It depends entirely on your ticket mix and we would not quote a figure without seeing it. Businesses with a high proportion of status and policy questions deflect a lot; those with complex or bespoke support deflect little. Analysing ticket history is the first step for exactly this reason.
Is deflection the right measure?
Not on its own, and treating it as the goal produces bad support. A customer who was deflected without getting their answer is a worse outcome than a ticket — they are now annoyed and still have the problem. Resolution rate and escalation quality matter more than volume avoided.
What should always escalate?
Complaints, refund and cancellation decisions, anything involving an exception to policy, anything the agent cannot verify, and any customer who asks for a person. That last one is absolute — refusing to hand off is the fastest way to turn a minor issue into a serious one.
Can it access order data?
Where your systems expose an API, yes — and it substantially improves the experience, because "your order shipped Tuesday and arrives Thursday" is a real answer where "check your tracking email" is a deflection.
What happens to questions it cannot answer?
They escalate, and they are logged as documentation gaps. That reporting is genuinely useful: it tells you what customers ask that you have never written down, which improves support whether or not you keep the agent.
Related services
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One agent, consistent across every channel
Conversational AI is software that holds natural dialogue with people across channels — web chat, messaging apps, SMS and voice. Built properly it uses one knowledge base and one set of behavioural rules across all of them, so a customer receives consistent answers regardless of how they made contact.
WhatsApp automation on the channel people actually reply to
WhatsApp automation uses the WhatsApp Business API to send and receive messages programmatically. Outbound messages outside an active conversation must use templates pre-approved by Meta. Once a customer replies, a 24-hour window opens in which free-form messages are allowed, which is when automated conversations and AI replies can run.
Turn Instagram DMs into booked appointments
Instagram DM automation uses Meta's messaging API to respond automatically to direct messages, comment triggers and story replies. Messages can be answered instantly, qualified conversationally, and converted into CRM contacts and booked appointments, subject to Meta's 24-hour messaging window rules.
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