Customer Service Automation
Automate the work,
not just the reply.
Your support team shouldn't spend the majority of their time looking up return policies, checking order eligibility, and drafting responses to requests that follow a predictable pattern. We build AI systems that handle those workflows end to end.
The structural problems that more agents don't solve
These aren't resourcing problems. They're process problems, and they compound as volume grows.
The majority of inbound tickets are repetitive and low-complexity
Returns, refund requests, address changes, and order status queries typically represent 60–80% of support volume. They follow consistent, predictable patterns.
Each ticket requires a policy check before it can be answered
Agents look up the order, find the relevant policy, check eligibility, and then write a response. That manual lookup cycle happens hundreds of times a week.
Response quality varies based on who handles the ticket and when
Without structured automation, how a return is handled depends on the agent's experience, the shift, and whether the latest policy version was consulted.
Escalation logic is informal and inconsistently applied
Urgent requests like billing failures, time-sensitive cancellations, and high-value customers surface based on whoever spots them rather than structured rules.
A system that handles the full workflow
Not a chatbot layer. Not a FAQ widget. A structured workflow system that processes customer requests from first message to resolved action.
Classifies every request on arrival
Before a human sees the ticket, the system identifies the request type, urgency level, and required action path based on what the customer actually said.
Retrieves the relevant policy and order context
Fetches the applicable policy section and the customer's order record. Applies eligibility checks automatically, using your rules.
Drafts an accurate response from your policy
Writes a response using your actual policy language, then queues it for agent review or sends it automatically based on your settings.
Executes actions in connected systems
Issues refunds, updates shipping records, generates return labels, closes tickets. The response and the operation happen in the same workflow, not as separate manual steps.
Control
Co-pilot mode or full automation. You set the boundary.
Both modes run on the same system and the same rules. Most teams start with reviewed drafts and expand automation as they verify the output.
The system classifies, retrieves, and drafts. Every response and action is queued for agent review before anything is sent or executed. Full visibility, minimal risk.
- Initial deployment and calibration
- High-value or policy-ambiguous requests
- Complex cases requiring agent judgment
- Any workflow where you want a human in the loop
The system handles the full workflow end to end. Responses sent, actions executed, tickets closed. Human review is triggered only when an exception or threshold rule applies.
- Standard return requests within policy
- Address changes before dispatch cutoff
- Order status and delivery queries
- Low-value refund approvals within defined limits
What the system actually does, step by step
These are the same workflow patterns we build for ecommerce support teams. The specifics vary; the structure is consistent.
Return request, eligible and within policy
Customer submits return request via email or helpdesk
System classifies as a standard return, retrieves order #5812 and your 30-day return policy
Order placed 18 days ago, within the return window. No exceptions apply.
Return label created in Shopify. Fulfilment status updated.
Confirmation email sent with return instructions. Ticket closed.
Return request outside the policy window
Customer requests return on an order placed 52 days ago
System retrieves the order and the return policy. 30-day window applies, no active extension rule.
Request falls outside policy with no exception criteria met.
Drafts a denial response using the policy language. Flags for agent review before sending.
Agent reviews, approves, or adjusts response. Sent.
Shipping address change before dispatch
Customer requests address change via support email
System checks dispatch status. Order not yet shipped.
Authenticates customer identity against order record
Updates shipping address in connected fulfilment system
Confirmation sent to the customer. Ticket closed, no agent needed.
What to expect
Indicative outcomes after deployment
Results depend on workflow complexity, policy consistency, and integration completeness. These figures reflect realistic deployment patterns, not theoretical maximums.
60–80%
Routine tickets handled without agent involvement
Returns, order changes, policy lookups: the majority of inbound volume on eligible workflows. Exact rates depend on policy consistency and integration completeness.
< 3 min
Automated resolution time for eligible requests
From classification to confirmation. Compared to 15–40 minutes for manual handling with policy lookup included.
100%
Responses built from your own policy docs
Every response is generated from the policy sections you wrote, not guesswork.
Consistent handling regardless of volume or shift
The same rules apply at 9am on a Monday and 11pm on a Friday. No variance from fatigue, different interpretations, or outdated policy knowledge.
Structured audit trail for every resolved ticket
What was retrieved, what eligibility check ran, what action was taken, and whether a human approved it. Reviewable at any time.
Controlled expansion of automation scope
Start with the workflows where risk is lowest and volume is highest. Expand scope as you verify the results match your standard.
Ready to automate your highest-volume support workflows?
Tell us what your team handles every day. We'll show you what can be automated and what the rollout looks like.