Incoming requests, handled by agents that explain the reasoning behind every step.

EngiAIFlow reads every request that arrives by email, WhatsApp or Teams, identifies the customer, acts in the company's systems and replies. It proceeds on its own when it is certain, consults the team when it is not and justifies every decision.

EngiAIFlow · Artificial Intelligence Agents

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EngiAIFlow connections screen, with the input channels and the connected systems.
Product screenshot, using demonstration data.
WHAT IT DOES

It handles what is clear, asks about what is not and learns from every decision.

Unambiguous requests proceed automatically, from receipt to the reply to the customer. The team only receives the cases that require a decision, already prepared and with the necessary information.

Every value with its source

Every piece of data taken from a message comes with the sentence it was extracted from. Without that reference, the data only moves on once it has been validated.

What was confirmed, in plain view

The agent states what it has confirmed and what remains to be confirmed, such as the sender's domain or the tax identification number. No conclusion appears without a justification.

Calculations and rules handled by the platform

The artificial intelligence model interprets the message. Calculations and company rules are applied by the platform and always produce the same result.

Progressive autonomy

Each agent starts as Apprentice, moves to Supervised and reaches Autonomous, at the pace the team sets. Rules are written in plain language, such as “before replying to the customer, ask for approval”.

Visible learning

What the team confirms is recorded on the agent's page, where each learned item can be reviewed and switched off. When the team links a sender to a customer, later messages from that sender arrive already identified.

Reply through the original channel

The reply to the customer goes out through the channel the request came in on, whether email, WhatsApp or Teams.

HOW IT WORKS

Three steps, no programming.

1
Set up

Input channels, such as the email inbox, the WhatsApp number, the Teams channel or the API, are set up just once, as are outgoing email and the company's systems, from the ERP to other applications. From then on, they are available to every agent.

2
Describe

Each agent is described in plain language, the way you would explain the job to a new colleague. EngiAIFlow proposes the steps, from reading the request to replying to the customer, and the team adjusts them in writing.

3
Work

Requests appear as conversations with the agent, which shows what it did, why, and what it needs from the team. The team's decisions then guide the requests that follow.

WHERE IT WORKS

The requests that take up your team's time today.

Requests recorded in company systems

It identifies the customer and what is being requested, applies the company's rules, records it in the ERP or another system and replies through the same channel.

Shared inbox triage

It reads every incoming message, identifies the subject and routes it to the right agent.

Complaints

It classifies the severity, hands the case to the person who decides and replies to the customer through the channel the complaint came in on.

INTEGRATION AND SECURITY

On top of the systems already in place.

It integrates with the ERP, email and the other tools, with the control that operations demand.

Input channels

IMAP and Microsoft 365 mailboxes, WhatsApp Business, Microsoft Teams, requests from other systems through the API, and scheduled tasks.

Integration with company systems

It looks up data such as customers, items or stock, and records information in the ERP and other systems with an API. Each agent's actions are configured system by system.

Documents and languages

It reads PDF attachments and, when enabled, scanned documents. Each user works in Portuguese, English or Spanish.

Profiles and audit trail

Three profiles, Operator, Manager and Administrator, each with its own permissions. Every action is logged, and sensitive data is masked in the case history.

Simulation and approvals

Agents can be tested with sample data, with no effect on live systems. Above the defined limits, steps with an external impact require approval.

On your infrastructure or in the cloud

Each company has its own installation. The artificial intelligence model can run locally, so that requests never leave the company, or on Azure OpenAI.

Bring us a process.

In 20 minutes, we show you an agent handling a request similar to yours and set out precisely what can proceed automatically and what should stay with your team.

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