AI Customer Support
AI Customer Support That Knows the Order, Not Just the FAQ
Most support automation fails because it can only read a help centre. We connect the AI to your order system, CRM and knowledge base, so it answers with the customer’s actual situation — and hands to a person the moment it should.
What is AI customer support automation?
AI customer support automation is software that reads an incoming customer message, works out what the customer actually wants, retrieves the relevant facts from the systems that hold them — order records, CRM, shipping, billing, knowledge base — and either resolves the request or routes it to the right person with the context already attached. The difference between this and a chatbot is data access: a chatbot answers from a script, an AI support system answers from your live records, and is allowed to take actions only inside rules you define.
Capabilities
What the system actually does
Not a feature list for its own sake — each of these exists because it removes a specific piece of repeated work.
Customer chat
Live chat on your website or app, answering with real account and order data instead of canned replies.
Email automation
Reads inbound email, classifies intent, drafts or sends the reply, and files it against the right case.
Ticket understanding
Turns a messy free-text message into a structured intent, priority and required action.
Customer history
Pulls previous contacts, orders and open issues so the customer never repeats themselves.
Order information
Live status, delivery estimates, payment state and item availability from your commerce system.
Knowledge retrieval
Grounded answers from your policies and documentation, with a citation trail to what it used.
Human escalation
Confidence and policy rules decide when a person takes over, with full context handed across.
Sentiment detection
Frustration, churn risk and legal-sensitive language route straight to a human.
Case creation
Opens, updates and closes cases in your helpdesk with the right fields already populated.
Support copilot
For teams that want AI drafting instead of AI sending — the agent stays in control.
How it works
What actually happens when a message arrives
Every step is inspectable. Nothing is a black box, and every action the system takes is logged against the customer record.
Guardrails
AI when it can. Humans when it should.
Automation that traps a customer is worse than no automation. Escalation is a designed feature, not a fallback.
- A customer can always reach a person — the request to speak to a human is treated as a valid instruction, not an objection to overcome.
- Low confidence, an unknown policy, or an unrecognised situation escalates instead of guessing.
- Anger, distress, complaint and legal language route to a person immediately.
- Money movement — refunds, credits, goodwill — sits behind approval thresholds you set.
- The agent who takes over receives the summary, the retrieved facts and the conversation, so the customer does not start again.
Reference architecture
How it fits your existing systems
We do not replace what you run on. The automation layer sits alongside it and is bound by what each system permits.
Channels
Where customers actually contact you.
Orchestration
Intent, routing, policy, confidence scoring, escalation rules and audit logging.
Knowledge + retrieval
Grounded answers from your material, not the open internet.
Systems of record
The systems that hold the truth. The AI reads them; it writes only where permitted.
Governance
What was done, by whom, on what basis.
Reference architecture, not a screenshot of a specific client deployment. Actual components depend on the systems you already run.
Before / after
What changes operationally
- Every enquiry read by a person, including the 40th “where is my order” of the day
- Agents alt-tabbing between helpdesk, admin panel and courier site
- Answers vary by whoever picked up the ticket
- Out-of-hours messages wait until morning
- No reliable view of what customers are actually contacting you about
- Repetitive intents resolved without a person touching them
- One screen: the context is already attached to the case
- The same policy answer every time, traceable to the source document
- Overnight and weekend enquiries answered or triaged on arrival
- Every contact classified — you can see what to fix upstream
Operational changes, not performance claims. Any numbers we publish come from a measured deployment and are named as such.
Where it applies
Common starting points
The best first deployment is narrow, high-volume and measurable. These are the ones that usually qualify.
Score your own workflowsOrder status and delivery enquiries
The single highest-volume intent in most retail and ecommerce operations, and the easiest to resolve from live data.
Returns and refund requests
Eligibility checked against policy and order state, with refunds above a threshold routed for approval.
Account and billing questions
Invoice copies, payment state, plan details — answered from the billing system rather than guessed.
Product and availability questions
Answered from the catalogue and stock position, including alternatives when an item is unavailable.
Triage for a small support team
Where you do not want AI replying at all — it classifies, prioritises and drafts, and a person sends.
Integrations
Systems we connect to on this work
Platforms and technologies we have built against. Not an endorsement or partnership claim.
FAQ
Questions we get asked
Related solutions
Relevant industries
Work out the numbers
Give us one repetitive problem.
Tell us about one workflow that keeps reaching a person when it should not. We will come back with how we would automate it, what stays human, and what it takes to build.