Saipos Focuses on Data Integration and AI While Maintaining Independence from iFood
October 9, 2026 · 2 min read
Saipos is implementing a technological strategy centered on the use of artificial intelligence in operations and development, alongside the integration of consumption data into restaurant management.
Marcelo Roveri Clementino, the head of technology at Saipos, stated that the company has maintained its technical autonomy and its integrations with other delivery platforms despite a closer relationship with iFood. He noted that this relationship has not altered the company's development routines or integration architecture. Clementino clarified that there is no data sharing between the two companies, as the processed information belongs to the restaurants.
Restaurants using the platform have access to order and customer data, as well as reports on sales volume and the cost of goods sold. The company ensures that data handling follows the General Data Protection Law, including the deletion of data after contracts end.
Saipos is developing a customer relationship management system that integrates natively with the point of sale to capture real time consumption history from delivery, pickup, and dine in services. This tool uses recency, frequency, and monetary value analysis to segment customers into groups such as loyal or at risk. Marketing campaigns are sent via WhatsApp using the official Meta API with coexistence technology to prevent phone number banning. The system tracks revenue, conversion rates, and return on investment.
Another active feature is the Multi CNPJ tool, which allows dark kitchens, franchisees, and restaurant groups to manage multiple tax IDs within a single account. This allows different brands to issue invoices according to their specific fiscal rules. Other available tools include a self service totem, a delivery routing system, and a customer service chatbot called SaiposBot.
Regarding artificial intelligence, the company employs AI agents across human resources, marketing, and technology, as well as in stock counting and order integration. Clementino described the company as a facilitator rather than an AI company, noting that humans still provide the final validation for all solutions. He cited a recent event, Saipos Colab, where solutions were developed in two days with significant AI support based on customer feedback.
To ensure utility across different restaurant sizes, the company uses a configurable architecture rather than static versions. As an example, the company mentioned Meu Tropeiro e Cia, which increased its volume from 950 monthly deliveries to 350 daily deliveries through kitchen and courier optimization.