PlantingSpace

We’re building a system that represents domain knowledge as modular probabilistic models, making analysis rigorous and transparent. Users can connect these models flexibly into larger structures; the system enforces consistency across them and propagates uncertainty through each step. First applications are in finance and scientific research (e.g., equity valuation, distress monitoring, particle physics). We’re expanding across Product Software Engineering (Quantitative Modeling), Program Synthesis Engineering, Applied Category Theory Research, Bayesian Software Engineering, and Finance Operations (Accounting, Analytics & Workforce). We’re also looking for Domain Experts to collaborate on high-value use cases—identifying and validating opportunities, shaping them into working solutions with engineers, and taking pilots to production with real users. Relevant expertise includes valuation models, quantitative default-probability models, or interest-rate prediction models.