GENAI CUSTOMER INTERACTION
Conversational Commerce by Workwise uses generative AI to manage customer interactions across digital channels—seamlessly, at scale, and in real time.
Records every surface the assistant answers on, and what it is permitted to say and do on each one.
Holds one customer’s thread across channels and across weeks, so a returning question arrives with everything already asked attached to it.
Reads price, availability and entitlement from the ERP, inventory and CRM systems that own them, at the moment the customer asks.
Carries a chosen item from the message that named it through to a placed order, and keeps an unfinished basket open until the customer comes back.
Keeps what the assistant said, which system it read to say it and what the customer agreed to, so an order placed in a chat can be reconstructed later.
How it works
This enterprise-grade solution empowers organizations to increase engagement, lower service costs, and unlock better outcomes across retail, finance, and consumer industries.
A customer who opens a question in a messaging app, checks one detail on the website and then rings the contact centre tells the same story three times. Each of those channels was built by a different team against a different system, so each one starts from nothing. The business pays for that twice: once for the person who re-establishes what the company already knew, and again for the purchase abandoned by someone who had already decided to buy.
Conversational Commerce puts one assistant behind all of those surfaces. The channel registry records each surface it answers on — web chat, the mobile app, a messaging thread, an outbound notification — and what it may say and do on each, because what is safe to tell a signed-in customer is not what is safe to tell an unverified number. The assistant does not change identity between channels; only its permissions do.
Conversation memory holds the thread rather than the session. A customer who asked about a delivery on Tuesday and comes back on Saturday through a different channel arrives with that question attached, and the assistant answers the follow-up instead of the opening question a second time. That continuity is also what makes an outbound message useful rather than intrusive: a note about a plan the customer is outgrowing lands in the thread where they were already discussing it.
The assistant answers out of the systems that own the answer. The catalogue bridge reads price, availability and entitlement from the ERP, the inventory system and the CRM as the question is asked, so what the assistant quotes is what the business will honour rather than what a copy of the catalogue said when it was last exported. What it recommends follows from what this customer has asked for and bought, not from a segment they were sorted into. Where there is no answer, it says so and hands the thread to a person with the whole conversation attached.
Buying happens inside the conversation. The checkout runner carries a chosen item from the message that named it through to a placed order, confirming the address, the plan or the payment method in the thread itself. A basket left unfinished stays open, so a customer who stops resumes where they stopped rather than starting again from the top.
Every exchange is recorded. The transcript ledger keeps what the assistant said, which system it read to say it, and what the customer agreed to, so an order taken in a chat can be reconstructed months later and checked against the record. That is the difference between an assistant a retailer is willing to try and one a bank is willing to put in front of its customers.
None of this arrives as one switch. A team can put the registry, the memory and the bridge on a single channel, prove the answers there, and leave checkout until it trusts them. Nor does the commercial case rest on a cheaper exchange: one assistant answers every thread that arrives at once, so volume does not queue, a question answered where it was asked never becomes a call, and a purchase completed in the thread never becomes a basket somebody has to chase.
Capabilities
What it runs on
Engagement shape
Conversational Commerce starts as a scoped engagement, not a licence. We agree which channel goes live first, which questions the assistant may answer there, and which ones it must hand to a person. The pod builds against your own catalogue and your own systems of record, proves the answers on a narrow set of intents before a customer sees any of them, and hands over the transcripts along with the runbook that operates it. Scope widens one intent and one channel at a time, and you decide the next one after reading what the assistant actually said.
Tell us which decision this product would have to improve to be worth running. We will scope the engagement against that, and nothing else.