1
Website inquiry
Software: saves the form. Your team reviews and links the contact.
How Avance works
Inquiries, conversations, appointments and follow-up are organized around the customer. AI assists with reception and drafts; your team continues the work with context.
Two entry paths, a team with context
2
Messaging conversation
AI: configured reception gathers the request and preferences.
3
Reception continues
Team: reviews details and arranges the appointment or next action.
4
Reviewed follow-up
AI: prepares the draft. Team: reviews, adjusts and sends.
Conversations become useful information for your team.
Only information shared by the customer and fields configured for your business.
What the customer says, ready to continue
AI gathers the information the customer shares. Based on your business configuration, those details are organized with the contact so the team can continue reception.
- Request: dental consultation.
- Preference: Thursday afternoon.
- For reception: review an available time.
Illustrative example with fictional data. Diagram of gathered information; not a CRM screenshot.
AI to move work forward. People to make decisions.
Your team receives the context and can continue the conversation.
The conversation continues with context
Your team can continue the conversation with the request and preferences already gathered. When a person replies, human-takeover controls prevent AI from continuing to answer on its own.
- Reception reviews the request and prepares its reply.
- The team keeps control of reception.
- Requests to stop receiving messages activate configured suppression.
Real conversation composer; context and reply prepared with fictional data. The capture ends before sending.
AI gathers the request. Your team arranges the appointment.
From an appointment request to a calendar managed by reception.
Reception creates the calendar appointment
The timing preference helps reception continue, but the calendar still needs review. Reception chooses an available time and records the appointment. Reminders and notices are configured separately.
- 1. Customer: requests a consultation.
- 2. AI: gathers the timing preference.
- 3. Reception: reviews the calendar and arranges the appointment.
- 4. Software: shows the appointment recorded by the team.
Real interface; fictional data. Demonstration changes do not reach a clinic. Example of a calendar managed by reception; not an autonomous AI booking.
From an open inquiry to a reviewed message
An open request
Valeria requested a consultation and the next step still needs arranging.
Prepares a draft
A message with context helps continue the conversation.
Reviews and sends
Adjusts the message if needed and decides when to send it.
AI prepares the follow-up. Your team reviews and sends it.
When an inquiry remains open, AI can prepare a message with context. Your team reviews it, edits it if needed and decides when to send it.
Draft awaiting review
Review the AI suggestion and edit it if needed. Preparing the message brings it into the composer to continue.
Real interface; fictional data. The capture ends before sending.
Your team decides when to send it
The prepared text appears in the composer. Your team can adjust it and decide when to use the send control.
Real interface; fictional data. The capture ends before sending.
AI also works with audio, images and documents.
What the customer sends can provide context for continuing.
From the original message to text for review
Audio can become a transcript; an image or PDF can become text for the conversation. The original message remains available and your team can review the extracted text before using it.
- Audio: transcription of the incoming message.
- Images and PDFs: extraction of readable text.
- Context for reception; it does not create a clinical record or validate clinical information.
Illustrative example with fictional data. The displayed text is a prepared example.
An AI-assisted second look at your campaigns.
Another task for the team: review campaigns with AI assistance.
From a search term to a decision with context
AI helps the campaign management team analyze Google Ads campaigns and prioritize recommendations. A search for dentistry courses may not fit a dental consultation campaign. The proposal includes a reason; the team reviews the context and decides which change to apply.
- Analyze search terms, ads and landing pages.
- Propose copy improvements and specific changes with an explanation.
- Review the proposal before applying supported Google Ads actions.
Recommendation prepared for the example. Awaiting review; it shows no applied change.
Why this matters
Less manual chaos
Fewer handoffs, fewer workarounds, and fewer things falling through the cracks.
Faster response
Customer context stays connected so follow-up can move with less friction.
Cleaner follow-up
The next step stays visible instead of living only in someone’s memory.
Better visibility
Website activity, conversations, and outcomes make sense as parts of the same system.
Compared with tool sprawl
Why this beats adding more tools
The gain is not another app — it is one connected customer record and less operational friction.
One connected customer record
Context does not break every time a customer switches channels.
Better operating intelligence over time
The system gets more useful as more of the business runs through it.
Automation that improves with real usage
Workflows get smarter when the underlying setup is actually connected.
Less software sprawl
You do not need a separate stack for every customer-facing task.
Start small
Start with one piece and grow later
Begin where the pain is urgent, then expand. Every starting point is the same platform — you're choosing where to begin, not which product to buy. Compare plans on `/pricing`.
Communication
Start here if replying and following up is the first urgent problem to solve.
Website
Start here if you need clear pages, recorded inquiries and a process for reviewing and publishing updates.
Ads
Start here if your team wants to review Google Ads campaigns with AI recommendations and an agreed management scope.
Expand later
Add more modules once the next operating pain becomes clear.
Broad proof
Our own businesses already run this model
Proof across more than one industry
Avance runs our own businesses — MyVisaUSA (immigration services) and Sigma Sensors (industrial supply) — and is now live in its first external dental clinic. The pattern is consistent: presence, response flow, follow-up, and organization work better in one system.
MyVisaUSA and Sigma Sensors
Our own operations — plus the first external clinic
Contexts
Immigration services, industrial supply, and dental (in pilot)
Model
Website, communication, and follow-up connected
Next layer
Deeper stories by industry as real numbers land