Illustrative data · ElevaSolutions' own bilingual enquiry and qualification assistant
WhatsApp Enquiry Assistant
WhatsApp enquiries become structured business context for human follow-up.
Open WhatsApp and try the assistantThe assistant handles enquiries about Eleva's services. Press Send in WhatsApp to start the conversation. You can request a person.
If WhatsApp doesn't open, copy the number and start a chat from the app.
Context
For whom
Built for ElevaSolutions' own public enquiry process, this project demonstrates how a business can connect incoming WhatsApp conversations to its internal follow-up workflow.
- An approachable first conversation in English or Spanish
- The business problem and current tools captured together
- A person able to continue with the context already collected
The starting point
Why it was needed
An initial message rarely contains everything needed to understand a business process. Gathering that context manually requires repeated questions and a separate hand-off into the enquiry workflow.
- The same introductory questions recur across enquiries
- Business needs can remain scattered through a chat thread
- A request for a person needs to become an actionable follow-up
What changed
The solution
Eleva built an assistant that responds when someone starts a WhatsApp conversation. It interprets the message, gathers relevant facts through controlled questions and connects the enquiry to the internal workflow. Visitors can request human attention.
- English and Spanish conversations with approved replies
- Questions about the process, current tools, desired outcome, people involved and urgency
- Answers to approved questions about how Eleva works
- Structured enquiry information connected to the internal lead inbox
- Human follow-up requests and opt-out handling
Workflow comparison
Before and after
Before
- Each new chat needed someone to collect the initial business context.
- The process, tools and desired improvement had to be assembled from individual messages.
- Moving a conversation into follow-up required a separate hand-off.
After
- The assistant gathers relevant context through a guided conversation.
- Business facts remain connected to the enquiry record.
- A visitor can request a person, and the workflow records the follow-up request.
Evidence in context
Project walkthrough
01 · Understand the initial enquiry
A fictional enquiry shows the assistant asking approved questions about the business process. This is an illustration of the flow, not a customer conversation.
02 · Keep the business context together
The illustrative brief explains the information gathered for follow-up. It represents the data flow rather than a screenshot of the private lead inbox.
03 · Make the next step a human conversation
In this example, the visitor accepts an offer of human follow-up. Scope, pricing and delivery commitments remain part of a separate conversation with Eleva.
Fit before fashion
Technology and why
WhatsApp Business Platform
- Requirement
- Receive and respond to customer-initiated WhatsApp enquiries
- Why it fits
- The official Cloud connects the WhatsApp channel to Eleva's application workflow.
- Resulting benefit
- Visitors can begin in a familiar channel while the business keeps the enquiry connected to its systems.
OpenAI and controlled response rules
- Requirement
- Interpret different descriptions of business needs while keeping responses within the approved scope
- Why it fits
- AI extracts information from the message; application rules validate the next step and select approved questions and replies.
- Resulting benefit
- Flexible message interpretation supports a consistent conversation without allowing the assistant to invent commercial commitments.
Next.js and TypeScript
- Requirement
- Connect the public messaging channel to a maintained business application
- Why it fits
- Server-side routes and typed workflow contracts connect message handling, enquiry records and follow-up.
- Resulting benefit
- The assistant fits into the same application that supports Eleva's business processes.
Supabase and Vercel Queues
- Requirement
- Retain conversation state and process incoming work with recovery controls
- Why it fits
- Durable records, queued processing and duplicate checks keep message handling separate from the initial receipt.
- Resulting benefit
- The workflow can track processing, recover eligible interrupted work and preserve enquiry context.
Illustrative data
Security and privacy
This is ElevaSolutions' own operational assistant. Every image uses fictional enquiry data and illustrates the workflow; none exposes a customer conversation or the private lead inbox.
- Fictional public examples with no customer names or contact details
- Private conversation records remain on protected server boundaries
- Signed incoming requests and duplicate-message checks
- Human hand-off and opt-out controls
Outcome
A first enquiry with a clearer next step
The assistant is in public use for Eleva's own services. It connects an incoming conversation to organised business context and a route to a person. A person can continue the discussion with the business need and current tools already recorded.
- Bilingual first contact
- Structured business context
- Human follow-up
A similar process?
Connect your enquiries to the work that follows
Tell us how your business handles incoming enquiries and what your team needs before following up. We can explore an assistant shaped around that process.
I want something similar for my business