klaxify builds a private, tenant-scoped resolution plan before it prepares or sends a customer response. Use the interactive product view below to follow the same five stages shown inside the inbox.
My package is late, and can I still change the delivery address?
Separate every requested outcome
klaxify identifies a delayed-shipment question and an address-change request instead of collapsing the message into one broad intent.
Collect the facts that change the answer
Approved knowledge, Shopify order state, tracking, verified customer memory, conversation history, permissions, and channel rules are checked together.
Build the complete resolution plan
klax IQ matches safe learned skills first, decides which next steps apply, and routes ambiguity to outside AI only when local intelligence is not enough.
Apply current policy and eligibility
The address can be changed because fulfillment has not started. The configured policy determines whether that action runs automatically or needs review.
Complete the approved work
klaxify updates the order, sends a complete response, records the audit trail, and captures the approved outcome as supervised learning evidence.
klaxify builds a private, tenant-scoped resolution plan before it prepares or sends a customer response. The plan is used across email, live chat, social messaging, and review workflows. Each channel keeps its own tone, length, privacy, and handoff rules.
What klaxify checks
For every new customer message, klaxify:
- Reads the current message together with the recent conversation history.
- Separates every distinct question or requested outcome so multi-part messages are not reduced to one intent.
- Identifies the current topic and detects when the customer changes topics.
- Selects the relevant approved procedure, tenant knowledge, verified customer memory, product information, and current Shopify context.
- Records which sources support each part of the response and which information is missing.
- Applies channel privacy rules, AI-agent approval settings, and commerce-action guardrails before allowing a response to be sent.
The AI guidance card in the inbox shows how many customer requests are covered. Select View plan to inspect the individual requests, verified sources, procedure steps, delivery eligibility, and any reasons a response is blocked.
Channel behavior
- Email: complete threaded responses that explicitly address every request.
- Live chat: shorter conversational responses that ask for one missing detail at a time.
- Facebook and Instagram: public-safe responses that move order or account details into a private conversation.
- Reviews: concise acknowledgements with personal resolution details handled privately.
klaxify does not expose order, account, or other private customer details on a public channel.
How the system improves
Human decisions are treated as supervised coaching signals. When a team member accepts or edits AI guidance and sends the final response, klaxify records the outcome against the exact resolution plan, channel, covered requests, and verified context. Consistent successful outcomes can reinforce tenant playbooks and response skills. Rejected, materially changed, unsafe, or incomplete guidance does not silently gain authority.
Automatic sending remains controlled by the AI employee's approval setting, confidence threshold, current knowledge, channel rules, and action policies. A learned response pattern never bypasses a live Shopify check or authorizes a commerce mutation by itself.
How to coach a response
Open View plan from the AI guidance card when a response is incomplete or inaccurate. The improvement section shows the appropriate correction based on what the plan is missing:
- Choose Correct this response when the facts are available but the wording, order, tone, or conclusion is wrong. Edit the response in the normal reply box and send it. The recommendation and your final response are saved together as a supervised coaching example.
- Choose Update the AI agent's instructions for a behavior that should apply repeatedly, such as brand voice, required disclaimers, escalation rules, or how the agent should structure an answer.
- Choose Add missing knowledge when klaxify does not have an approved policy, product answer, or support article to cite. Updating one reply does not make an unsupported fact authoritative.
- Choose the Shopify, product, customer-memory, or procedure option when the plan reports that context as missing. This repairs the source rather than teaching the AI to guess around it.
Sending an unchanged recommendation records an acceptance. Sending an edited recommendation records the correction and how much it differed. Recurring, successful corrections can strengthen the tenant's learned response skill, but automatic sending only increases when the AI employee's approval settings and guardrails allow it.