The platform that runs your sales and support operation — an operational intelligence platform.
Full CRM, WhatsApp and other channels, campaigns and AI agents in one place. Your team stays in command; the intelligence steps in where it makes sense.
For those who sell through WhatsApp, through the website — or both: abandoned cart, inactive customer, repurchase, campaigns by buying behavior, Shopify, Bling, WhatsApp via Meta’s official API.
By conversation, by e-commerce — or both. It’s the same Platform; what changes is where it enters your operation.
The lead arrives, someone answers, qualifies, makes a proposal and closes — often on WhatsApp. Clinics, services, manufacturers, carriers, B2B with a sales team.
Prospecting → Lead → Conversation → Proposal → Closing → Post-sale
The customer chooses, pays and receives. The sale is the checkout; the work is answering fast, not losing carts and bringing the customer back.
Product → Cart → Payment → Post-sale → Repurchase
Sell both ways? The Platform sees the store and support in the same place.
Not sure where AI fits into your company? We figure it out with you ↓Before.The abandoned cart just sat there. Nobody had time to chase it down.
A stalled cart and a pending payment enter a message sequence through the official number — and what came back shows up on the scoreboard, in reais.
Sales recovery · Scoreboard in R$
Before.Whoever bought once, nobody reached out to again.
When the product is running low at the customer’s home, they get a message on the right day — and the AI talks with them if they reply.
Post-sale and repurchase · Company Brain
Before.A message after hours waited until the next day.
The customer is answered in seconds, at any hour, and the lead becomes a deal in the funnel without anyone typing.
AI-powered support · CRM
Before.The salesperson wrote everything from scratch, off the top of their head.
The salesperson writes; the intelligence corrects, answers questions about the company and delivers the customer’s history on the spot.
Assistive AI — proofreader, Ask the Agent
Before.To know how support went, someone read conversation by conversation.
Every conversation gets a score; mass problems are swept up; an aging queue triggers an alert.
AI supervision
Before.Follow-up depended on someone remembering.
Work that depended on memory now runs on triggers: when X happens, do Y.
Campaigns & Automations
Follow-up nobody did, a customer nobody called back, a cart nobody recovered — none of that shows up in your costs. But it costs.
There’s no single way to use BANMO. In every part of the operation, the intelligence can help, execute or observe — and within one company these ways coexist. Pick a mode and watch the same minute play out three ways.
11:40 System
Customer writes: "my order hasn’t arrived, it’s been 12 days now". The conversation opens with the order, the tracking and the history alongside.
11:41 Person
Renata reads the ready-made reply suggestion — delivery time, tracking, an apology —, adjusts the tone and sends. Nothing went out without her.
11:41 System
The proofreader checks the writing. It’s on record who handled it: Renata.
11:52 Person
Renata resolves it and closes the ticket.
No autonomous agent. The AI prepares; the person decides and sends.
Illustrative scenario. Every piece — suggestion, proofreader, agent, handoff situation, sequence, dashboard — exists in the Platform.
In all three modes, the decision was your team’s. What changed was how much work reached them.
You can use BANMO in the first mode only — with no autonomous agent at all. The CRM, the support and the automations come whole just the same.
Knowledge, limits and handoff situations belong to the company. When you correct a rule, the correction holds for the next conversations — not just one.
8 capabilities on a single core. No separate module.
Dozens of ready-made strategies — recovery, repurchase, handoff situations — switched on with a single toggle. You don’t write from scratch: you switch on what you want.
Explore the PlatformA CRM stores. A chatbot replies. The Platform operates — it senses what happened, decides within the rules, acts, measures what came back and uses that in the next decision.
In most systems, artificial intelligence is a button stuck on top. Here it’s the layer through which the data, the decisions and the everyday work pass.
Learning, here, is operational: history, results and validated knowledge come to make up the context of the following decisions. No AI model is retrained on your data.
09:02 · a cart stalled in the store, with R$ 189.90 inside. The Platform knows, because the order comes from Shopify.
The core cross-references what it already knows: it’s the first purchase, the product is a restock item, the customer didn’t ask to stop receiving messages.
09:20 · the first message in the sequence goes out, through the official number. If the customer replies, the agent takes over knowing the cart and the link.
16:27 · order paid. R$ 189.90 goes onto the scoreboard — it only counts money that came in.
The result feeds back into the context: which angle worked for that profile weighs on the next decision. No model is retrained on your data.
A demo sale, from cart to scoreboard. Data → intelligence → action → result → learning — and the learning loops back to the start.
The Platform connects right from the screen. But the most common way to start is assisted rollout: BANMO sets up channels, CRM, Shopify or Bling, imports the database, builds lists, campaigns, automations and rules — and trains the team.
Those who want to go deeper hire IAtização — redesigning the operation by deciding, piece by piece, what the system does, what your team does and where the AI helps. It can end with your team doing everything, with the AI alongside.
01Diagnosis
We map the operation and where intelligence generates results first.
02Design
What the team does, what the system executes, where the AI helps, what to measure.
03Rollout this is where you come in
Channels, CRM, Shopify or Bling, database, lists, campaigns, rules — with your team alongside.
04Operation
Track, measure and adjust. The corrected rule holds for the next conversations.
Fictional demo data. Real interface, untouched.
The scoreboard only counts money that came in — order paid, not order created. Revenue attributed to a message is what happened within the window; we don’t claim the message was the only cause.
A 30-minute conversation to understand how your company sells — and to show what the Platform changes in your context. No sales script.
If you’re not sure where to start, request a diagnosis: we find out with you where the intelligence comes in first.