A conversation layer on the official WhatsApp Business API that qualifies the lead, writes what it learns to your CRM, offers real booking slots, routes to the right branch, and hands judgment calls to a named person with the thread attached.
WhatsApp AI automation runs first-touch conversations on the official WhatsApp Business API. It qualifies the lead, updates your CRM as the conversation happens, offers real booking slots, and escalates to a named person when the request needs judgment. Luminous builds these on Claude and GPT, with the escalation and routing rules agreed before anything sends. Fixed price from $999 to $15,000, delivered in 2 to 24 weeks depending on scope.
| If you need | Use |
|---|---|
| You need qualification, booking, and CRM updates inside one chat thread | WhatsApp AI automation |
| You need the same qualification and routing on inbound phone calls | Voice AI |
| Your pipeline, fields, and ownership rules need rebuilding first | CRM and GoHighLevel automation |
| You want a fixed script that never departs from it | Workflow automation is cheaper and more predictable |
The AI handles the predictable part of a conversation and stops where judgment begins. Pricing, complaints, and anything unusual reach a person with the thread attached.
The assistant asks the qualifying questions, records the answers, and judges whether it can finish the conversation. Ambiguity, complaints, and price negotiation go to a person instead of a guess.
Name, need, urgency, location, and source are extracted as the customer types and pushed to the CRM by API or webhook, so the record is current before the reply goes out.
The assistant checks live availability, books the appointment, confirms it, and follows up when a customer goes quiet, inside the thread the conversation started in.
Conversations are matched to the branch or team that can act on them, with language, timezone, and business-hours logic applied per conversation rather than per account.
The escalation points, message templates, CRM fields, and routing rules are agreed and tested before the assistant answers a real customer.
We read existing WhatsApp threads, support messages, and sales objections to find where conversations stall, repeat, or need a person.
System prompt, approved knowledge, tool access, CRM field mapping, routing table, and the conditions that end the automated part of the conversation.
WhatsApp Business API, CRM, calendar, and reporting are wired to a test number and run against real past conversations before any customer sees it.
One country or one branch goes live first. Escalation rate, booking completion, and CRM accuracy are reviewed before the assistant takes more of the volume.
Templates get rejected, prices change, branches open, and model behavior shifts. A live WhatsApp assistant needs an owner and a review cycle.
Platform choices follow your existing CRM, calendar, ad accounts, support structure, and the countries you actually operate in.
Luminous implements the conversation, routing, CRM, and booking workflow. You remain responsible for the WhatsApp Business account, the opt-in basis, message content approval, and the commercial commitments the assistant is allowed to make.
WhatsApp limits what can be sent outside the customer service window and requires opt-in for template messages. Review your message categories, opt-in records, retention, and cross-border data transfers with qualified advisors before launch.
Use these guides and services to evaluate the surrounding website, search, advertising, intake, and measurement work.
The API approval process, template rules, and what the build involves.
The supervised-agent foundation the conversation layer is built on.
Pipelines, ownership, and reporting the WhatsApp thread writes into.
Apply the same qualification and routing rules to inbound calls.
How qualification and scoring decisions get defined and reviewed.
An official WhatsApp Business API connection rather than an unofficial workaround, an assistant that decides when to escalate rather than following a fixed script, and infrastructure that holds up across concurrent conversations in several time zones.
Ask any vendor how the escalation decision is made. Script triggers are brittle at volume; judgment-based handoff is what holds up.
Yes, when they share one conversation state. Bolting a separate reminder tool onto a separate chatbot creates gaps: the customer replies to a reminder and the bot does not recognize the context. Keeping the question, the booking, the reminder, and the follow-up in one thread with shared state avoids that.
It extracts the details it is configured to look for, such as name, need, urgency, location, and source, then pushes them to the CRM by API or webhook as the conversation happens rather than in an overnight batch. The sales team sees a current record within seconds of a reply.
Intake, routing to the branch that can act, confirmation once the job is done, and the review request afterwards. A system that stops after intake and routing leaves the team chasing confirmations and reviews by hand, which is usually where the value leaks out.
Three parts: WhatsApp conversation charges billed by Meta on usage, the build itself, and ongoing tuning. Our build is fixed price from $999 to $15,000, delivered in 2 to 24 weeks depending on scope.
Messaging volume tends to matter more than build cost once several countries or branches are live, so price it against your expected conversation volume rather than an entry tier.
There is no universal number, and a vendor quoting one is guessing about conversations they have not seen. The workable standard is that routine conversations (standard questions, standard bookings) resolve or route without a person, while anything ambiguous escalates instead of guessing.
The useful metric is how reliably the assistant recognizes the conversations it should not handle.
Yes. The conversation layer handles the languages named during scoping, and language is one of the routing inputs, so a conversation that escalates reaches someone who can continue it in the same language.
We will help define the sensible next step, including when a smaller intervention is better than a full build.
