DBF provides an AI‑driven generative design and spatial analytics platform that creates multiple massing and feasibility scenarios from project requirements using integrated GIS data. The cloud‑based tool evaluates key performance indicators, optimizes trade‑offs, and lets planning, architecture, and engineering teams quickly compare, refine, and export options for early‑stage design decisions.
Funding
Funding not disclosed
Founders
Product
Problem
Planning and design teams often rely on manual GIS spreadsheets and early BIM iterations to assess massing, gross floor area, site coverage, access, and sustainability metrics, which is time‑consuming, error‑prone, and leads to late‑stage feasibility surprises.
Solution
DBF offers an AI‑driven generative design and spatial analytics platform that automates the creation of multiple massing and feasibility scenarios from project requirements. By ingesting multi‑source geospatial data—including maps, satellite imagery, terrain models, road networks, and custom datasets—the system validates key performance indicators such as GFA, site coverage, height limits, accessibility, and sustainability scores within minutes. The platform presents traceable, comparable outputs that can be saved, refined, and shared, enabling rapid “what‑if” analysis and stakeholder iteration before detailed BIM modeling. Integrated multi‑objective optimization highlights trade‑offs between conflicting goals, while cloud‑based analytics provide benchmarking across scenarios. This accelerates early design cycles, reduces rework, and improves alignment across planning, architecture, and engineering teams.
Target Audience
Primary users are planning, architecture, and engineering teams in enterprise, government, and large‑scale development projects that need rapid feasibility studies and data‑driven design exploration.
Features
- AI generative design engine that produces feasible layout and massing options based on user‑defined constraints and objectives
- Spatial analytics suite that evaluates accessibility, proximity, density, reliability, and custom KPIs using diverse GIS data sources
- Multi‑objective optimization with conflict detection and trade‑off suggestions for competing design targets
- Scenario management tools for saving, comparing, refining, and exporting options, including IFC and Excel outputs
- Cloud‑hosted analytics and benchmarking across scenarios with automated reporting dashboards
- Web‑based interface optimized for Chrome, requiring no installation and supporting large‑scale urban projects