P2AgentX

P2AgentX is an Australian renewable-energy technology company focused on advancing autonomous solar-farm operations through AI, data analytics and robotics. Founded by researchers from UNSW’s School of Photovoltaic and Renewable Energy Engineering (SPREE), the company combines over a decade of applied research in PV performance, modelling, field operations and AI-driven optimisation.

Our flagship products, P2Chat and P2Dingo, address critical operational challenges faced by utility-scale solar farms.

• P2Chat is an AI-powered asset-management platform that transforms SCADA and sensor data into actionable insights, automates performance reporting, detects faults and supports workflow and maintenance planning.
• P2Dingo is a quadruped robotic inspection system that performs visual, thermal and connector inspections to reduce manual field work, improve safety and enable autonomous operations over time.

P2AgentX works closely with asset owners, operators and EPCs to integrate advanced modelling, predictive diagnostics and robotics into existing O&M processes. The company is collaborating with large Australian solar farms to validate, scale and commercialise autonomous inspection and analytics technologies.

With a strong foundation in research, industry partnerships and practical field deployment, P2AgentX is committed to reducing O&M costs, increasing renewable energy value and accelerating Australia’s transition to safe, reliable, digitally enabled solar operations.

How we enable AI adoption:
P2AgentX helps solar asset owners, operators and EPCs adopt AI through practical, field-validated tools that integrate seamlessly into existing workflows. Our approach focuses on reducing complexity and lowering barriers for AI adoption in large-scale renewable-energy assets.

• P2Chat uses physics-based performance models and AI agents to translate raw SCADA and sensor data into clear, actionable insights. Businesses use P2Chat to automate reporting, identify performance issues earlier, quantify energy losses, generate maintenance workflows and support data-driven decision-making without needing in-house data-science capability. Its conversational interface removes the need for specialised dashboards or training, making AI accessible to engineers, asset managers and executives.
• P2Dingo combines autonomous navigation, computer vision and thermal analytics to enable AI-driven field automation. It supports visual and thermal inspections, MC4 connector detection and condition monitoring – reducing manual workload, improving safety and capturing high-quality datasets used to train and refine predictive models.

We work closely with businesses through pilots, co-design sessions and integration support to ensure AI solutions align with operational requirements. This collaborative model accelerates adoption, builds organisational confidence in AI-driven workflows and helps the renewable-energy sector transition toward safer, more efficient autonomous operations.