BIM software for building design and construction engineering in Brazil
AltoQi is Brazil's dominant software vendor for building information modeling (BIM) in construction, with a 30-year operating history and 60,000 accumulated customers. The tech stack reveals a dual-core architecture: CAD/3D rendering (C++, OpenGL, Qt) paired with modern data infrastructure (Snowflake, dbt, Airflow, Python) — indicating an internal shift toward data-driven operations. Active hiring across support, sales, and construction roles combined with pain-point focus on sales-process standardization and CRM data quality suggests the company is scaling go-to-market infrastructure alongside product development.
AltoQi develops BIM-aligned software solutions for architectural, civil, and systems engineering workflows, serving building-design firms and construction teams across Brazil. The product portfolio covers project modeling, design automation, and engineering calculations tailored to Brazilian regulatory standards. With 201–500 employees based in Florianópolis, the company operates across sales, support, design, and construction-aligned functions. Recent project activity reflects internal operational scaling: treasury dashboards, MVP development, and sales-process governance indicate expansion beyond pure product engineering into business operations and revenue optimization.
AltoQi uses C++, OpenGL, and Qt for 3D CAD rendering; Python, Snowflake, dbt, and Apache Airflow for data engineering; Node.js and Java for backend services; and HubSpot, NetSuite, and Power BI for business operations.
AltoQi has an accumulated customer base of 60,000, established over more than 30 years operating in the Brazilian construction software market.
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AltoQi's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.