Setting up a WhatsApp number for support with AI requires three things: an account on the platform, a WhatsApp number, and a Facebook Business (Meta) account. In Jestor, that setup via the WhatsApp Business API (Meta) usually takes less than 5 minutes, with the AI Agent configured afterward. What'
The future of automation with AI is heading toward increasingly autonomous agents inside processes the company itself defines, with no need for technical development. In Jestor, that direction already shows up in AI Agents and Agent Builder, built on a no-code foundation. Where is business automation headed? The trend
Automating vendor support with AI starts by connecting the contact channel — usually the WhatsApp Business API (Meta) — to a structured Pedidos de Compra (Purchase Orders) process. In Jestor, an AI Agent answers common vendor questions, like order status or payment date. Why vendor support tends to be overlooked? Automation focus
AI and automation together cover different types of tasks: traditional automation handles fixed rules, and AI comes in when content needs to be interpreted. In Jestor, that means native automations handling predictable triggers, with AI Agents and BPMS covering what requires judgment. What's the difference between what automation
An AI pilot project works best when it starts from a single, well-defined process, not the whole operation at once. In Jestor, the starting point is usually an adjusted starting template, with an AI Agent configured through Agent Builder for that specific process. Why a narrow scope makes the
Today, AI agents for financial operations can already read documents, fill in records, and classify requests — but they don't decide approvals on their own. In Jestor, AI Agents work inside Gestão Financeira alongside Edição de Registros por IA, always with a human decision on the approval itself. How
To identify bottlenecks with real-time data in an approval workflow, the way to go is checking the process dashboard and directly asking about the observed pattern. In Jestor, Chat with Data queries Approvals indicators in natural language, with no need to wait for a ready-made report. Why approval
AI applied to HR helps mainly in two areas: screening candidates and filling in data during onboarding. In Jestor, the RH e Recrutamento module organizes job openings and applications on a Kanban board, and AI Agents support prioritization, with Edição de Registros por IA filling in fields automatically. Why manual
Connecting AI agents to internal systems depends on two things: having data already centralized, and an open way to exchange information between systems. In Jestor, Agent Builder uses the company's own Tables as its base, and the open API integrates with internal systems the company already uses. Why
Before adopting AI in process automation, the starting point is mapping the current process and checking whether it's repetitive enough to justify an agent. In Jestor, that evaluation happens before configuring AI Agents or using Agent Builder, usually supported by BPMS to design the flow first. Why evaluate
Building operational reports with AI means asking about the data in natural language, instead of manually building a spreadsheet. In Jestor, Chat with Data queries each process's dashboard indicators and answers based on generative AI, with no technical knowledge required. Why does building an operational report manually take
To implement AI in operations management, the most effective path starts with one specific process, not the whole company at once. In Jestor, that means configuring a first AI Agent through Agent Builder, measuring the result, and only then expanding with App Builder com IA to other processes. Why starting