Project controls for solar and battery storage, run as one integrated model.
flowpmo.ai is building an AI-integrated project controls stack for utility-scale solar and BESS: one coding structure linking schedule, cost, scope, risk and resources, with AI that answers from the project's own data and shows its sources.
What we're building
One integrated model
Schedule, cost, scope, risk and resources share one work breakdown, one set of codes and one set of rules of credit, so every number reconciles.
Built on Oracle Primavera Cloud
Oracle Primavera Cloud is the system of record. Configuration is scripted and verified, so a project is set up the same way every time.
AI that shows its working
Answers and forecasts come from the project's own data, with the source behind every figure. AI proposes; deterministic code calculates.
Approach
The method follows recognised project-controls practice, including AACE International's Total Cost Management framework, and is written for the physics of solar and storage construction: feeders, blocks, quantities installed, and systems commissioned.
For owners and developers, it means assurance and early warning against a schedule built to a clear specification. For EPC contractors, it means daily progress capture, productivity and forecasting from the same model.
Contact
flowpmo.ai is founded by James Gillies, a planning and project-controls practitioner with twenty years across oil and gas and renewables, based in Dubai.