Solution
Customer Operations
Customer Operations That Answer Faster and Escalate Better
The goal is not to deflect customers away from humans. It is to make sure the human conversations are the ones that actually need a human — and that they start with context instead of a cold read.
“Support costs rise every time we grow, and the questions are always the same ones.”
How you know
You probably have this problem if…
- A small set of questions accounts for most of your ticket volume
- First response time is measured in hours, not minutes
- Agents open four tabs before they can answer anything
- You cannot staff weekends and customers notice
The change
What the workflow looks like before and after.
Amber marks a step the system performs. Solid ink marks one a person still performs. The count above each column is how many steps still need someone's attention.
Today
3 human steps- Performed by Customer
Asks where the order is
- Performed by System
Ticket queued
Behind 40 others
- Performed by A person
Agent picks it up
3 hours later
- Performed by A person
Looks up the order
In a separate system
- Performed by A person
Types the answer
- Performed by Customer
Replies with a follow-up
Cycle repeats
After
1 human step- Performed by Customer
Asks where the order is
- Performed by Automated
Identifies customer and order
From the live system
- Performed by Automated
Answers with real status
Seconds, any hour
- Performed by Automated
Offers the next action
Notify on dispatch, reschedule
- Performed by A person
Handles the genuine exception
With full context
- Performed by System
Logs the gap if it failed
- Automated
- A person
- System
- Customer
The system
What this looks like running in a business.
The same components we build with.
- Contacts today
- 1,284
- Resolved unattended
- 876
- Escalated warm
- 408
68%
with full context
| Contact | Type | Source read | Routing |
|---|---|---|---|
| Where is my order | Status | Order system | Resolved |
| Change delivery address | Amendment | Order + address rules | Resolved |
| Return outside window | Policy exception | Returns policy | To agent |
| Damaged on arrival | Complaint | — | Immediate handover |
Weekly gap report — questions the system could not answer
- Policy not covered in source material23Added to the knowledge base this week
- Product data missing an attribute11Raised with merchandising
34 items awaiting a person, grouped by cause so one decision clears a class rather than a case.
Deflection rate flatters the system. Contacts per hundred orders counts the conversations it prevented.
The work does not disappear. It moves — and the steps left are the ones that needed a person.
Koderead · scope of authority
What we build
Four things, in this order.
A grounded answer layer
Answers are drawn from your actual policies, product data and order state — not from a model's general knowledge. If the source does not cover it, the system says so.
Status and self-service actions
Where is my order, change my appointment, update my address, send me the invoice. These are the bulk of volume and they are all resolvable without a person.
Warm escalation
When it reaches an agent, the agent sees the full thread, the customer record, what was already tried, and a suggested next step.
A gap report
Every question the system could not answer becomes a weekly list. That list is how your knowledge base finally gets accurate.
Boundaries
What stays with a person.
Agreed in writing before the build, not discovered afterwards.
- Complaints, cancellations and anything with legal exposure route to a person
- The system never guesses at a policy it cannot cite
- Customers can always reach a human, and that route is never hidden
- Vulnerable-customer signals trigger immediate human handover
Integrations
We connect to what you already run.
Replacing a working system mid-transformation adds risk without adding value. If the existing tool genuinely cannot support the workflow, we say so at assessment rather than three months into a build.
- Zendesk
- Freshdesk
- Intercom
- HubSpot Service
- WhatsApp Business
- Shopify
- WooCommerce
- Twilio Voice
More specific
Narrower services under this capability.
If you arrived looking for one of these by name, each page answers it directly — including where the honest answer is that you need something else.
Questions we get
Asked and answered.
Will customers know they are talking to AI?
Yes. We disclose it, every time. Attempting to pass an AI off as a person is both an ethical problem and, increasingly, a regulatory one — and it fails the moment the conversation gets difficult.
What deflection rate should we expect?
It depends entirely on your ticket mix, and anyone quoting you a number before reading your tickets is guessing. What we do first is classify a month of real volume, which tells you the ceiling before you commit to a build.
Do we have to cut support headcount to justify it?
No, and most clients do not. The common outcome is the same team covering more volume with faster response and less burnout. If headcount reduction is your goal, say so at the assessment and we will model it honestly.
Where this lands hardest
Industries feeling this most.
Next step
Find out whether this is actually your highest-value fix.
Eleven questions, scored in your browser, with the arithmetic shown. It may well tell you that a different area matters more.
Start the assessment