AI-powered marketing intelligence platform for retail and e-commerce
BIUD builds marketing intelligence software for small and mid-market retail chains and e-commerce operators in Brazil. The tech stack reveals a data-first architecture: PostgreSQL + MongoDB for storage, Python + R + scikit-learn for analytics, and Power BI + Tableau + Looker Studio for visualization—complemented by newer generative AI tools (CrewAI, Langchain, Google Generative AI) woven into a Node.js/NestJS backend. Active projects around conversational chat automation and observability suggest the team is scaling from early-stage product (MVP evolution) toward distributed systems, while pain points centered on data quality and national-scale reliability indicate infrastructure strain typical of high-growth fintech/analytics startups.
Notable leadership hires: Tech Lead
BIUD operates a data and marketing intelligence platform tailored to small businesses, retail networks, and franchises in Brazil. The company positions itself as a precision-marketing solution, helping retailers grow through data-driven targeting and localized insights. Founded in 2018 and based in Brasília, BIUD employs 11–50 people with an engineering and data-focused structure. Current project work spans platform scaling (moving MVP to national deployment), automated messaging workflows, and ESG-related analytics—reflecting both product maturation and expanding customer use cases. The organization is headquartered in Brazil and recruits locally.
PostgreSQL, MongoDB, Python, R, scikit-learn, Power BI, Tableau, Looker Studio for core analytics; NestJS, Node.js, TypeScript, FastAPI for backend; CrewAI, Langchain, Google Generative AI for newer AI features; Docker, Azure DevOps, Git for infrastructure.
BIUD has 5 active roles with minimal recent posting velocity. Departments include engineering (2), data (1), and product (1), with a seniority mix of senior, lead, and mid-level positions. All hiring is based in Brazil.
Active projects include scaling GenChat from MVP to production, implementing automated conversational experiences, launching an ESG platform, evolving microservices architecture, and building observability—focused on national-scale retail and e-commerce deployments.
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