Cases No 01 2026
Autoflow A debt-collection platform for a Brazilian credit company.
Built for a consumer-credit company in Brazil. The team had been managing collections across spreadsheets, WhatsApp, and a legacy CRM. We consolidated the workflow into one interface and used AI to reduce repetitive operational work.
Numbers
- i ~50% of a collector's day used to be operational work. Most of that time is now available for customer conversations.
- ii 2 days minutes Invoice issuance used to take the team two days each cycle. It now runs automatically.
- iii ~3x Target cases per collector with AI handling repetitive work. The system is tracking toward that target.
No 01
The problem
When we started, the team's day was approximately half negotiation and half operations. The operational half included issuing boletos, copying contract numbers between systems, reading inbound messages to identify next steps, and updating statuses afterwards. Many collection teams operate this way.
The brief was to give them the operational half back.
No 02
What the AI does
AI is embedded in four workflow steps, rather than presented as a standalone chatbot.
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i
Triage
Inbound messages on WhatsApp and SMS are tagged by intent: payment, negotiation, no response, question, complaint. The triage view groups them by tag so collectors can process high volumes without constant context switching.
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ii
Reply
When a collector opens a conversation, a suggested response is drafted from the relevant contract context. Instalment numbers and payment details are pulled at draft time.
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iii
Contract read
Each contract gets a short summary: what happened, what is overdue, and the recommended next action. This was the first capability requested by the team managers.
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iv
Flows
A no-code builder for SMS, WhatsApp, and voice campaigns. Flows can be triggered by time, calendar, or contract events such as invoice issuance, payment receipt, or days overdue. Managers can run campaigns without engineering support for each change.
No 03
Where it's going
We planned the product in three stages. The first stage is in production today. The next two define the roadmap for the coming year.
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01
Shipping
Copilot
Where we are today. AI drafts the reply; the collector reviews it, edits if needed, and sends. A human remains in every loop.
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02
In progress
Assisted
AI handles repeatable patterns such as reminders and simple promise-to-pay confirmations, then asks for approval when negotiation or discount rules are involved.
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03
Planned
Autopilot
Most routine cases can close without manual review. The exceptions queue stays small enough for the team to handle carefully.
No 04
The stack
- Surfaces
- Dashboard, contract view, conversation triage, flow builder, team monitor.
- AI
- Intent classifier, reply drafter, contract summariser, decision branches inside flows, AI voice for outbound calls.
- Channels
- WhatsApp, SMS, and AI voice, all running through the same flow engine.
- Data
- The platform talks to the company's credit system in real time. Nothing the AI sees is more than a few seconds stale.
- Live today
- Two AI agents in production. Four automated flows running.